The use of geographical information systems in climatology and meteorology
Identifieur interne : 000412 ( Istex/Corpus ); précédent : 000411; suivant : 000413The use of geographical information systems in climatology and meteorology
Auteurs : Lee Chapman ; John E. ThornesSource :
- Progress in Physical Geography [ 0309-1333 ] ; 2003-09.
Abstract
The proliferation of ‘commercial off-the-shelf’ geographical information systems into the scientific community has resulted in the widespread use of spatial climate data in a variety of applications. This paper presents a review of the role of geographical information systems in climatology and meteorology by (i) discussing methods used to derive and refine spatial climate data and (ii) reviewing the bespoke application of GIS and spatial climate datasets in agriculture, ecology, forestry, health and disease, weather forecasting, hydrology, transport, urban environments, energy and climate change.
Url:
DOI: 10.1191/0309133303pp384ra
Links to Exploration step
ISTEX:EEF0CFD3C80B325195625B25FF7451D0516FC525Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">The use of geographical information systems in climatology and meteorology</title><author wicri:is="90%"><name sortKey="Chapman, Lee" sort="Chapman, Lee" uniqKey="Chapman L" first="Lee" last="Chapman">Lee Chapman</name><affiliation><mods:affiliation>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: l.chapman@bham.ac.uk</mods:affiliation></affiliation></author><author wicri:is="90%"><name sortKey="Thornes, John E" sort="Thornes, John E" uniqKey="Thornes J" first="John E." last="Thornes">John E. Thornes</name><affiliation><mods:affiliation>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: l.chapman@bham.ac.uk</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:EEF0CFD3C80B325195625B25FF7451D0516FC525</idno><date when="2003" year="2003">2003</date><idno type="doi">10.1191/0309133303pp384ra</idno><idno type="url">https://api.istex.fr/document/EEF0CFD3C80B325195625B25FF7451D0516FC525/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000412</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000412</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">The use of geographical information systems in climatology and meteorology</title><author wicri:is="90%"><name sortKey="Chapman, Lee" sort="Chapman, Lee" uniqKey="Chapman L" first="Lee" last="Chapman">Lee Chapman</name><affiliation><mods:affiliation>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: l.chapman@bham.ac.uk</mods:affiliation></affiliation></author><author wicri:is="90%"><name sortKey="Thornes, John E" sort="Thornes, John E" uniqKey="Thornes J" first="John E." last="Thornes">John E. Thornes</name><affiliation><mods:affiliation>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: l.chapman@bham.ac.uk</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Progress in Physical Geography</title><idno type="ISSN">0309-1333</idno><idno type="eISSN">1477-0296</idno><imprint><publisher>Sage Publications</publisher><pubPlace>Sage CA: Thousand Oaks, CA</pubPlace><date type="published" when="2003-09">2003-09</date><biblScope unit="volume">27</biblScope><biblScope unit="issue">3</biblScope><biblScope unit="page" from="313">313</biblScope><biblScope unit="page" to="330">330</biblScope></imprint><idno type="ISSN">0309-1333</idno></series><idno type="istex">EEF0CFD3C80B325195625B25FF7451D0516FC525</idno><idno type="DOI">10.1191/0309133303pp384ra</idno><idno type="ArticleID">10.1191_0309133303pp384ra</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0309-1333</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The proliferation of ‘commercial off-the-shelf’ geographical information systems into the scientific community has resulted in the widespread use of spatial climate data in a variety of applications. This paper presents a review of the role of geographical information systems in climatology and meteorology by (i) discussing methods used to derive and refine spatial climate data and (ii) reviewing the bespoke application of GIS and spatial climate datasets in agriculture, ecology, forestry, health and disease, weather forecasting, hydrology, transport, urban environments, energy and climate change.</div></front></TEI><istex><corpusName>sage</corpusName><author><json:item><name>Lee Chapman</name><affiliations><json:string>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</json:string><json:string>E-mail: l.chapman@bham.ac.uk</json:string></affiliations></json:item><json:item><name>John E. Thornes</name><affiliations><json:string>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</json:string><json:string>E-mail: l.chapman@bham.ac.uk</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>bespoke system</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>climatology</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>digital terrain model</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>geographical information system</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>meteorology</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>weather forecasting</value></json:item></subject><articleId><json:string>10.1191_0309133303pp384ra</json:string></articleId><language><json:string>eng</json:string></language><originalGenre><json:string>research-article</json:string></originalGenre><abstract>The proliferation of ‘commercial off-the-shelf’ geographical information systems into the scientific community has resulted in the widespread use of spatial climate data in a variety of applications. This paper presents a review of the role of geographical information systems in climatology and meteorology by (i) discussing methods used to derive and refine spatial climate data and (ii) reviewing the bespoke application of GIS and spatial climate datasets in agriculture, ecology, forestry, health and disease, weather forecasting, hydrology, transport, urban environments, energy and climate change.</abstract><qualityIndicators><score>6.008</score><pdfVersion>1.2</pdfVersion><pdfPageSize>469.134 x 668.976 pts</pdfPageSize><refBibsNative>true</refBibsNative><abstractCharCount>604</abstractCharCount><pdfWordCount>8308</pdfWordCount><pdfCharCount>54389</pdfCharCount><pdfPageCount>18</pdfPageCount><abstractWordCount>84</abstractWordCount></qualityIndicators><title>The use of geographical information systems in climatology and meteorology</title><genre><json:string>research-article</json:string></genre><host><volume>27</volume><publisherId><json:string>PPG</json:string></publisherId><pages><last>330</last><first>313</first></pages><issn><json:string>0309-1333</json:string></issn><issue>3</issue><genre><json:string>journal</json:string></genre><language><json:string>unknown</json:string></language><eissn><json:string>1477-0296</json:string></eissn><title>Progress in Physical Geography</title></host><categories><wos><json:string>science</json:string><json:string>geosciences, multidisciplinary</json:string><json:string>geography, physical</json:string></wos><scienceMetrix><json:string>economic & social sciences</json:string><json:string>social sciences</json:string><json:string>geography</json:string></scienceMetrix></categories><publicationDate>2003</publicationDate><copyrightDate>2003</copyrightDate><doi><json:string>10.1191/0309133303pp384ra</json:string></doi><id>EEF0CFD3C80B325195625B25FF7451D0516FC525</id><score>0.05110343</score><fulltext><json:item><extension>pdf</extension><original>true</original><mimetype>application/pdf</mimetype><uri>https://api.istex.fr/document/EEF0CFD3C80B325195625B25FF7451D0516FC525/fulltext/pdf</uri></json:item><json:item><extension>zip</extension><original>false</original><mimetype>application/zip</mimetype><uri>https://api.istex.fr/document/EEF0CFD3C80B325195625B25FF7451D0516FC525/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/EEF0CFD3C80B325195625B25FF7451D0516FC525/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a" type="main" xml:lang="en">The use of geographical information systems in climatology and meteorology</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>Sage Publications</publisher><pubPlace>Sage CA: Thousand Oaks, CA</pubPlace><availability><p>SAGE</p></availability><date>2003</date></publicationStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a" type="main" xml:lang="en">The use of geographical information systems in climatology and meteorology</title><author xml:id="author-1"><persName><forename type="first">Lee</forename><surname>Chapman</surname></persName><email>l.chapman@bham.ac.uk</email><affiliation>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</affiliation></author><author xml:id="author-2"><persName><forename type="first">John E.</forename><surname>Thornes</surname></persName><email>l.chapman@bham.ac.uk</email><affiliation>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</affiliation></author></analytic><monogr><title level="j">Progress in Physical Geography</title><idno type="pISSN">0309-1333</idno><idno type="eISSN">1477-0296</idno><imprint><publisher>Sage Publications</publisher><pubPlace>Sage CA: Thousand Oaks, CA</pubPlace><date type="published" when="2003-09"></date><biblScope unit="volume">27</biblScope><biblScope unit="issue">3</biblScope><biblScope unit="page" from="313">313</biblScope><biblScope unit="page" to="330">330</biblScope></imprint></monogr><idno type="istex">EEF0CFD3C80B325195625B25FF7451D0516FC525</idno><idno type="DOI">10.1191/0309133303pp384ra</idno><idno type="ArticleID">10.1191_0309133303pp384ra</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>2003</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>The proliferation of ‘commercial off-the-shelf’ geographical information systems into the scientific community has resulted in the widespread use of spatial climate data in a variety of applications. This paper presents a review of the role of geographical information systems in climatology and meteorology by (i) discussing methods used to derive and refine spatial climate data and (ii) reviewing the bespoke application of GIS and spatial climate datasets in agriculture, ecology, forestry, health and disease, weather forecasting, hydrology, transport, urban environments, energy and climate change.</p></abstract><textClass><keywords scheme="keyword"><list><head>keywords</head><item><term>bespoke system</term></item><item><term>climatology</term></item><item><term>digital terrain model</term></item><item><term>geographical information system</term></item><item><term>meteorology</term></item><item><term>weather forecasting</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2003-09">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/EEF0CFD3C80B325195625B25FF7451D0516FC525/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="corpus sage not found" wicri:toSee="no header"><istex:xmlDeclaration>version="1.0" encoding="UTF-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//NLM//DTD Journal Publishing DTD v2.3 20070202//EN" URI="journalpublishing.dtd" name="istex:docType"></istex:docType><istex:document><article article-type="research-article" dtd-version="2.3" xml:lang="EN"><front><journal-meta><journal-id journal-id-type="hwp">spppg</journal-id><journal-id journal-id-type="publisher-id">PPG</journal-id><journal-title>Progress in Physical Geography</journal-title><issn pub-type="ppub">0309-1333</issn><publisher><publisher-name>Sage Publications</publisher-name><publisher-loc>Sage CA: Thousand Oaks, CA</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.1191/0309133303pp384ra</article-id><article-id pub-id-type="publisher-id">10.1191_0309133303pp384ra</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group></article-categories><title-group><article-title>The use of geographical information systems in climatology and meteorology</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Chapman</surname><given-names>Lee</given-names></name><aff>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK, <email xlink:type="simple">l.chapman@bham.ac.uk</email></aff></contrib></contrib-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Thornes</surname><given-names>John E.</given-names></name><aff>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK, <email xlink:type="simple">l.chapman@bham.ac.uk</email></aff></contrib></contrib-group><pub-date pub-type="ppub"><month>09</month><year>2003</year></pub-date><volume>27</volume><issue>3</issue><fpage>313</fpage><lpage>330</lpage><abstract><p>The proliferation of ‘commercial off-the-shelf’ geographical information systems into the scientific community has resulted in the widespread use of spatial climate data in a variety of applications. This paper presents a review of the role of geographical information systems in climatology and meteorology by (i) discussing methods used to derive and refine spatial climate data and (ii) reviewing the bespoke application of GIS and spatial climate datasets in agriculture, ecology, forestry, health and disease, weather forecasting, hydrology, transport, urban environments, energy and climate change.</p></abstract><kwd-group><kwd>bespoke system</kwd><kwd>climatology</kwd><kwd>digital terrain model</kwd><kwd>geographical information system</kwd><kwd>meteorology</kwd><kwd>weather forecasting</kwd></kwd-group><custom-meta-wrap><custom-meta xlink:type="simple"><meta-name>sagemeta-type</meta-name><meta-value>Journal Article</meta-value></custom-meta><custom-meta xlink:type="simple"><meta-name>search-text</meta-name><meta-value> The use of geographical information systems in climatology and meteorology Lee Chapman* and John E. Thornes Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK Abstract: The proliferation of 'commercial off-the-shelf' geographical information systems into the scientific community has resulted in the widespread use of spatial climate data in a variety of applications. This paper presents a review of the role of geographical information systems in climatology and meteorology by (i) discussing methods used to derive and refine spatial climate data and (ii) reviewing the bespoke application of GIS and spatial climate datasets in agriculture, ecology, forestry, health and disease, weather forecasting, hydrology, transport, urban environ- ments, energy and climate change. Key words: bespoke system, climatology, digital terrain model, geographical information system, meteorology, weather forecasting. I Introduction The early origins of geographical information systems (GIS) can be traced to the influx of microcomputers into North America in the early 1960s (Bernherdson, 1992). Early GIS such as Canadian GIS (CGIS) and McIDAS (the US equivalent) were used to provide a simplified view of the real world by displaying digital spatial information as dynamic electronic maps. As GIS has developed, the definition of GIS as a spatial visu- alization facility is too vague as any spatial display of information such as a simple weather chart or raster satellite image could be thought of as GIS. Nevertheless, GIS has now evolved into a powerful management tool used for capturing, modelling, analysing and displaying spatial data (Worboys, 1995) and represents an amalgamation of database technology with computer assisted cartography (Bernherdson, 1992). Analysis is achieved across data layers in an object-orientated programming Progress in Physical Geography 27,3 (2003) pp. 313330 © Arnold 2003 10.1191/0309133303pp384ra *Author for correspondence: tel: 0121 414 7435; e-mail: l.chapman@bham.ac.uk 314 Use of GIS in climatology and meteorology environment allowing spatial variables to be statistically compared and thus producing new spatial datasets beneficial to range of applications. Climatological and meteorological phenomena are naturally spatially variable and hence GIS represent a useful solution to the management of vast spatial climate datasets for a wide number of applications. For the purpose of this review the use of GIS in climatology and meteorology is conceptually classified into two categories of usage. A distinction is made between the derivation of spatial climate datasets from their subsequent bespoke application (Figure 1). This dual role of GIS is discussed in more detail in following sections. II Derivation of spatial climate data 1 Remote sensing Distinctions between the two disciplines of GIS and remote sensing are sometimes difficult to determine as the two fields are intimately related. Remote sensing enables the acquisition and calibration of large-scale comprehensive datasets whereas GIS provides a means to display and spatially analyse the data. For example, remotely sensed Digital Elevation Models (DEMs) can be manipulated in a GIS to provide a baseline, synthetic climatological dataset. DEMs were traditionally derived using land- surveying techniques but are now determined remotely using radar techniques, e.g., the Shuttle Radar Topography Mission (SRTM). The SRTM was launched aboard the Figure 1 Conceptual model of the dual role of GIS in climate and meteorology. GIS is a useful tool to aid in the derivation of climate datasets that are then used in a variety of tertiary applications DATA OUT/VISUALIZATION DATA IN TERTIARY NONCLIMATOLOGICAL DATA DATA OUT/VISUALIZATION MODELLING/ANALYSIS GEOSTATISTICS DATA IN SPATIAL CLIMATE DATASET OTHER GEOGRAPHICAL DATA OTHER GEOGRAPHICAL DATA OTHER GEOGRAPHICAL DATA GIS2. CUSTOMIZATION layer 1 layer 2 layer 3 layer n DATA EXTRACTION EXTRAPOLATION RASTER GEOGRAPHICAL DATA E.G., DIGITAL TERRAIN MODELS POINT CLIMATOLOGICAL DATA E.G., WEATHER STATION OBSERVATIONS DATA ENHANCEMENT INTERPOLATION GIS1. DERIVATION space shuttle Endeavour in February 2000 and aims to provide topographic data for 80% of the land surfaces of the Earth at a resolution of up to 30 m. Comprehensive raster climate datasets can also be inferred from satellite imagery. For example, Schadlich et al. (2001) produced land surface temperature maps by combining a DEM with brightness temperatures derived from METEOSAT's thermal infrared channel. Similar approaches have been used by Verdebout (2000) and El Garounani et al. (2000) to generate surface ultraviolet maps of Europe and evapotranspiration maps of Tunisia, respectively. Such is the complexity of the image processing involved with remote sensing techniques (i.e., geometric and radiometric corrections), 'commercial off-the-shelf' (COTS) GIS products are rarely used for image analysis. Indeed, many 'pure' remote sensing applications utilizing just image data alone require no more utility from a GIS than the means of displaying obtained results. A classic example of this is provided by satellite rainfall climatology (e.g., Levizzani et al., 2001). However, the need for synergy between the two subjects becomes evident for a wide number of other applications, par- ticularly those utilizing input data from a variety of sources. Here, GIS provides a standard means of overlaying and combining data for analysis. For example, Nichol (1994, 1995) combined geographical vector data with surface temperatures derived from Landsat TM thermal imagery to explore the spatial characteristics of forest canopy temperatures with elevation and land use in Singapore. The study served as the preliminary investigation of a monitoring exercise in an attempt to conserve the remaining 5% coverage of rainforest on the island. Landsat TM data was also used by Suga et al. (1995) where it was combined with NOAA/AVHRR data to monitor sea surface temperature change in the Sea of Japan via a GIS. 2 Baseline climatologies Climate data can be displayed in a GIS in a variety of ways; lightning strikes are point features, rain radar is raster (gridded) and isolines are vector. Climate data is typically point source in nature, meaning that one of the biggest challenges facing meteorology is the extrapolation of point climate data across a wide spatial domain. The extraction or extrapolation of climate data using DEMs has enabled good estimates of an area's baseline climatology without the need for extensive consultation of weather records. For example, high elevation mountainous environments suffer from a lack of frequent observations and hence, the development of techniques to infer climates from a sparse network of weather stations is highly advantageous. Over the past decade, DEMs have become increasingly available to the degree that high resolution models of many areas of the world are available for free to the academic community. Raster DEMs are then simplified into Triangular Irregular Networks (TINs) from which the microclimate of each triangle or facet is readily calculated via a variety of simple algorithms (Bernherdson, 1992). A good, recent, example of this approach is the PRISM (Parameter-elevation Regressions on Independent Slopes Model) project in the USA, which has successfully been used to compile a series of high quality spatial datasets around the world (Daly et al., 1994, 2000). PRISM is a knowledge-based climate analysis system that generates GIS-compatible estimates of climate variables accrued from a variety of sources L. Chapman and J.E. Thornes 315 316 Use of GIS in climatology and meteorology including point climate (station) data, DEMs and other spatial datasets. By using a coordinated set of rules, decisions and calculations, extensive gridded estimates of pre- cipitation and temperature can be made with respect to the different climate regime (distance, elevation, atmospheric boundary layer, hillslope orientation and proximity to the coastline) of each DEM facet. However, PRISM is not just an empirical climate approximation tool, but is ultimately a two-layer model of the boundary layer and the free atmosphere. The depth of the boundary layer is variable to model the development of temperature inversions and the maritime influences on precipitation. Agnew and Palutikof (2000) developed a multiple regression model using a 1 km resolution DEM to analyse the variation in geographical parameters (latitude, altitude, continentality, slope, aspect and ratio of land to sea). The model was less robust than PRISM as it needed to be initialized with 248 temperature and 285 rainfall sites to infer the variation in mean seasonal temperature and rainfall across the Mediterranean basin. However, the results were encouraging, attaining a typical R2 explanation of 87% (summer) and 97% (winter). Comparable results were also attained in an independent study by Ninyerola et al. (2000) where a multiple regression analysis on topographical variables in Catalonia yielded coefficients of determination of the order 7997% for temperature and precipitation. Polynomial regression was the approach utilized by Goodale et al. (1998) who modelled monthly precipitation, temperature and solar radiation in Ireland with mean absolute errors of 515 mm for precipitation, 0.20.5°C for temperature and 615 minutes for sunshine hours. The examples discussed so far have been at a coarse scale. However, the ever- increasing resolution of modern DEMs allow the study of the impacts of terrain on climate at meso- or microscales. Examples include determination of solar radiation topoclimatologies (Moore et al., 1993; Dubayah, 1994), modelling the sensitivity and response of mountainous terrain (del Barrio et al., 1997) and development of baseline island climatologies. For example, de Azevedo et al. (1999) used advective and radiative submodels in a GIS to extrapolate climate data obtained at sea-level across the whole of small volcanic islands. 3 Climate interpolation When dealing with more spatially comprehensive climate datasets, the issue is not the inference of a 'first approximation' baseline climatology, but instead the interpolation of point station data across the landscape by geostatistical techniques (e.g., Tveito et al., 2001). Splining is a deterministic spatial regression technique that fits a mathematical function or 'rubber sheet' across irregularly spaced data. Lennon and Turner (1995) used thin plate splines determined from a DEM to model the climatic distribution of temperature in the UK. A total of 16 independent geographical variables were used in the splines and were shown to be more accurate than basic interpolation techniques such as multiple regression. Lennon and Turner concluded that just 30 temperature recording stations would be sufficient to model temperature variation in the UK. Thin plate smoothing splines were also used by Fleming et al. (2000) in the derivation of an Alaskan baseline climatology from a sparse weather station record. Kriging is another common interpolation technique used in spatial climate studies. Unlike splining, the technique is stochastic and requires some user input, but has the same aim of fitting a surface to irregularly spaced data. This is achieved by using variograms to analyse the structure of variables in given directions to build up a map of spatial variation weightings from a small sample of datapoints. Kriging was used by Hudson and Wackernagel (1994) to map mean January temperatures in Scotland and by Jeffrey et al. (2001) to interpolate daily and monthly rainfall between 4600 weather stations in Australia. However, for interpolation of other climate variables a thin plate spline was used. The accuracy of the two techniques was tested in a study by Jarvis and Stuart (2001) who interpolated minimum and maximum temperatures for 1976 at a 1 km resolution over England and Wales. They discovered that thin plate splines were more accurate than kriging, with root mean square (RMS) errors of the order of 0.8°C for minimum temperatures and 1.14°C for maximum temperatures. Finally, a relatively new method of interpolation is the application of neural networks. Antonic et al. (2001) derived an empirical model for seven climatic variables via a neural network. The model typically explained 98% of the variation in climatic parameters, which was improved further by kriging of the residuals for model correction. A feed-forward back propagation neural network was also used by Rigol et al. (2001), which considers both trend and spatial associations of climatic variables. Performance of the network was comparable with that achieved with kriging, but has the advantage that guiding variables (such as terrain) do not need to be linearly related to the interpolation data. III Applications of spatial climate data Several examples of methods in which spatial climate datasets can be derived have been discussed. The advantage of spatial climate datasets is that they can be compared in a GIS with dissimilar data accrued from many sources. Hence, GIS has enabled the environmental impact of the variation of climate to be studied for many applications at a variety of scales. This section outlines some of the many tertiary applications of spatial climate datasets. 1 Agriculture In much the same way as spatial climate datasets are derived, GIS has massive potential for agroclimatic modelling (Jurisic et al., 1999). From a GIS, maps can be produced and combined of soils, nutrients, climate, water stress, fertility and predicted yield. An early example of this capability is provided by Soderstrom and Magnusson (1995) who produced an agroclimatic assessment of an area of southwestern Sweden. Radiation mosaics were calculated using a DEM and cold air drainage modelled via a network analysis tool. This information was then combined in a GIS with kriged data from mobile temperature surveys to produce the final map. McKenney et al. (2001) used thin plate splines to model climatic gradients in Canada to determine plant hardiness zones. By using a trivariate position of latitude, longitude and elevation, maps of temperature and rainfall enabled the mapping of each variable required for plant hardiness formulae at a 1 km resolution. By incorporating temperature and aridity thresholds, agroclimatic models can be L. Chapman and J.E. Thornes 317 318 Use of GIS in climatology and meteorology logically adapted to be species specific. For example, Menkir et al. (2000) identified four potential agroecological zones for the growing of maize in West and Central Africa, whereas Panigrahy and Chakraborty (1998) used temporal remote sensing data along with spatial soil, rainfall and temperature data to derive a potato growing index for West Bengal. They discovered that currently 37% of the agricultural area is used for potato crop cultivation but concluded that a further 48% of agricultural area was suitable for potato crop intensification via a crop rotation system. GIS agroclimatic modelling is not just limited to agricultural zoning. Hill et al. (1996) use SPOT and Landsat TM satellite imagery, climate, edaphic and topographic data along with a simple bioclimatic model to analyse the pastoral limit of cattle grazing in New South Wales, Australia. The variables used to locate species can also be used to provide estimates of yields via crop simulation models. For example, Priya and Shibaski (2001) use interpolated climate data to drive their model, whereas Kravchenko et al. (2000) inferred climatic impacts from a DEM. Physiological models are particularly useful to predict yields when crops have been subjected to prolonged stress, for example, drought (e.g., Lourens and deJager, 1997), cool summers (e.g., Yajima, 1996) and disease (e.g., Hijmans et al., 2000). The success of such models can then be tested by using remote sensing techniques (e.g., Carbone et al., 1996) GIS is also used in agriculture to monitor biogenic emissions and agricultural pollution/water stress. Andronopoulos et al. (2000) modelled the transportation of biogenic volatile organic compound emissions with respect to the sea breeze for the east coast of Spain. Benjamin et al. (1997) estimated biogenic emissions in California by combining a biomass inventory with emission rates corrected by light intensity, canopy shading and temperature. A more specific example is provided by the measurement of biogenic emission from rice fields where GIS crop simulation models are coupled with daily weather data to measure methane (Knox et al., 2000; Matthews et al., 2000). Finally, rainfall data can be used to estimate leaching effects of agricultural fertilizers into water supplies (e.g., Udouj and Scott, 1999; van Wesenbeeck and Havens, 1999; Wu and Babcock, 1999). 2 Ecology In much the same way as potential crop distributions can be modelled using GIS-based agroclimatic models, ecological biodiversity can be modelled with respect to spatial climate datasets. For example, Jones et al. (1997) used latitude, longitude and altitude data coupled with long-term monthly means of rainfall and temperature to model 'bean-favouring' climates. The GIS approach to modelling biodiversity has been suc- cessfully used in many other studies: Birnie et al. (2000) modelled bracken spread in Scotland, Guisan and Theurillat (2000) used a DEM coupled with satellite data to model alpine plant distributions, Kadmon and Danin (1999) studied the distribution of plant species in Israel with respect to rainfall and Franklin (1998) predicted the distribution of shrub species in southern California with respect to bioclimatic attributes derived from terrain. Although these examples essentially concentrate on flora distributions, the same ideas can be applied to fauna. Examples include the Portuguese dung beetle (Hortal et al., 2001), the New Zealand flatworm (Boag et al., 1998), land snails (Kadmon and Heller, 1998), threatened butterflies (Weiss and Weiss, 1998) the effect of different wind speeds and directions on albatrosses (Reinke et al., 1998) and the impact of sea surface temperatures on fish distributions (Waluda et al., 2001; Zheng et al., 2001). 3 Forestry As in agriculture and ecology, GIS can be used to produce climate zones to select site suitability for afforestation (e.g., Ellis et al., 2000) or used to predict yields (e.g., Valdes et al., 1994). However, GIS is used in forest science for many other applications. For example, DEMs are used to analyse and highlight forested areas potentially exposed to wind-snap. Lekes and Dandul (2000) used a GIS containing soil and terrain data with an airflow model to evaluate the wind exposure by producing a wind damage risk clas- sification. Analysis of more extreme events has been accomplished by Pleshikov et al. (1998) who modelled the impact of a hurricane on pine stands in Central Siberia and Foster and Boose (1992) who used GIS to analyse the spatial distribution of wind damage and rank the susceptibility of particular forest types. Frost prediction is a further example of the use of GIS in topoclimatic forestry studies, which is important with respect to seedling mortality (Blennow and Lindkvist, 2000). By modelling the stagnation of cold air via a DEM coupled with forest canopy sky-view factor data, Blennow (1998) explained 89% of the spatial variation of air temperature. At the opposite end of the temperature spectrum from frost is the major hazard of fire. GIS is used to model and monitor the spread of forest fires via a combination of climate data and remotely sensed imagery (e.g., Zhu et al., 2000; Pew and Larsen, 2001; Sunar and Ozkan, 2001; Vazquez and Moreno, 2001). After fire, Belda and Melia (2000) use a GIS integrated with remote sensing techniques to model forest recovery. By analysing the influence of climatic parameters in the regeneration of forest areas, spatial variations in the amount of vegetation could be predicted. 4 Health and disease Vector-borne infections are geographically restricted by climate and topography and can be modelled effectively using remotely sensed climate datasets with GIS and global positioning system technology (Bergquist, 2001). Typical examples of application are in the developing world and include malaria (Manguin and Boussinesq, 1999; Srivastava et al., 2001), lymphatic filariasis (Lindsay and Thomas, 2000) and schistosomiasis (Bavia et al., 2001; Malone et al., 2001). 5 Weather forecasting Conceptually, visual weather forecasts combine layers of weather data in what is effectively a GIS environment. GIS has become a key management component in weather processing systems allowing instantaneous plotting, interpolation and animation of weather data across any isobaric level of the atmosphere. The synoptic situation across different levels is then gauged by a forecaster, from which GIS is used to calculate the progression of weather systems. An extreme example of this is the L. Chapman and J.E. Thornes 319 320 Use of GIS in climatology and meteorology relational positioning and monitoring of tornados and tropical cyclones, where GIS is used to issue warnings to precise locations using remote sensing signatures (Kumar et al., 1998). An alternative use of GIS is the combination of different layers of weather information in expert classification systems. For example, specific humidity is often compared with wind flow to identify areas of fog, cloud and precipitation in relation to orographic and coastal influences. Similarly, the spatial offset of rawinsonde data (normally plotted at the location where the balloons have been released), can be calculated by superimposing layers of upper wind data. As advances are made away from conventional methods of synoptic forecasting, interpolated climate datasets are used to set the boundary conditions for numerical weather prediction such as mesoscale forecast models and general circulation models. For example, Cheng and Shang (1998) use a GIS to manipulate topographic and roughness data to model wind fields using a numerical kinematic flow model. However, difficulties exist with numerical models in the assimilation of interactions between the land surface and the upper atmosphere. To some extent, GIS has greatly facilitated the incorporation of numerical weather model output into weather processing systems, onto which satellite imagery and topography can be superim- posed; an approach that greatly aids the skill of the weather forecaster. However, GIS is not just used as an end-point in weather forecasting; Gabella and Perona (1998) use a DEM coupled with geometric optics to assess the siting of weather radar, whereas Pfister and Fischer (1995) studied the influence of roughness length calculated from terrain on the vertical sounding of temperature profiles. Overall, GIS partially automates forecasting by facilitating speed and throughput of weather data in real-time as well as providing support for traditional weather processing tasks such as contouring and superposition. 6 Hydrology Hydrometeorological modelling provides a good example of how COTS GIS products can be used with meteorological and other detailed datasets to develop bespoke systems with the specific aim of the end-user in mind. The spatial measurement of pre- cipitation is an obvious starting point for many hydrometeorological models. Again, DEMs and climate interpolation techniques provide a useful means of producing rainfall datasets from point data obtained from raingauge techniques (e.g., Prudhomme, 1999; Tsanis and Gad, 2001). However, the use of interpolated gauge data is largely restricted to validation studies such as agricultural water management (e.g., Sousa and Pereira, 1999) or for studying the hydrological impact of various climatic scenarios. For example, spatial rainfall patterns derived from point data have been used to model the hydrological response to El NiñoSouthern Oscillation (ENSO) in Australia (Wooldridge et al., 2001) and the seasonal variability of the Indian monsoon (Wilk and Andersson, 2001). For hydrological forecasting purposes, the alternative and preferred methodology of data acquisition is the use of satellite data. Bell and Moore (1998) used raster radar rainfall estimates combined with diffusion models across isochrone pathways derived from a DEM for use in real-time flood forecasting. Similarly, Carpenter et al. (1999) used weather radar coupled with a DEM to model threshold flash-flood runoff. This is achieved by using a GIS to model the contributing area to stream segments categorized using the similar hydrological response unit concept (Gorokhovich et al., 2000). Radar provides real-time estimates of precipitation, but to achieve forecasts at an increased timescale, mesoscale weather forecast models need to be incorporated into the system. For example, Yarnal et al. (2000) simulated the hydrological response of the Susquehanna river basin, USA, to atmospheric forcing. This was achieved by using a linked system of a mesoscale meteorological model with grid increments of 4 km to drive the hydrological modelling system that contained information layers regarding soils, terrain and land use. A comparison of these different techniques was conducted by Taschner et al. (2001). The study in the Ammer catchment in Germany, showed that mesoscale model data and rain radar overestimated flood volume by 1536% whereas interpolated raingauge data underestimated runoff volume by 15%. Depending on the region of study, models may require additional input data to adequately model local hydrological regimes. So far, this review has concentrated on flood analysis, but the opposite extreme is that of drought. Ghosh (1997) used a GIS to investigate the distribution of drought in India by comparing albedo and vegetation derived from satellite data with isoheytal maps based on 70 years of rainfall data. In such (semi-) arid environments, an important parameter to model is potential evapo- transpiration. This is estimated by overlaying temperature and DEM-derived slope, aspect and elevation data (Shevenell, 1999). The resulting maps tend to inversely mimic topography. Topography is also important in snowy environments where there is a need to incorporate the influence of snowmelt into hydrometeorological models. The first step in estimating snowmelt is to assess variations in the distribution of snow caused as a consequence of strong winds and terrain (Bruland et al., 2001; Tappeiner et al., 2001). Lapen and Martz (1996) used a 10-m resolution DEM to show that snow depth is more closely related to relative topographic position as opposed to local morphology. Modelled results can then be validated with satellite imagery such as Landsat TM (e.g., Fily et al., 1999). Once snow distributions are clearly delineated, values of snow water equivalence are calculated. As snowmelt is dependent on available energy controlled by the elevation, aspect and shading of site, DEMs coupled with a temperature threshold can be effectively used to provide estimates (Cazorzi and DallaFontana, 1996). Examples of this approach are the studies of Bell and Moore (1999) and Cline et al. (1998) who developed models for upland Britain and the Sierra Nevada, California, respectively. Overall, hydrometeorological models provide an example of how COTS GIS can be successfully adapted into commercially viable bespoke products. However, the success of such products is extremely dependent on the ability to operate in real time, a void recently filled by the Internet, which has facilitated efficient data transfer. Indeed, Internet-based GIS software products now exist that allow spatial outputs to be viewed by an end-user who could be totally inexperienced in GIS. L. Chapman and J.E. Thornes 321 322 Use of GIS in climatology and meteorology 7 Transport Bespoke systems are also being developed to aid decision-making and to set budgets for winter road maintenance. For example, Gustavsson et al. (1998) present a technique to assess potential winter road maintenance costs to be taken into consideration when planning new road stretches. Similarly, Cornford and Thornes (1996) developed a spatial winter index by using kriging with altitude as external drift to predict spatial expenditure on winter road maintenance in Scotland. The decision whether or not to salt a road often has to be made at short notice, and hence continuous updates of how road conditions are varying around a road network are required by maintenance personnel. Hence, research is ongoing into the incorporation of mesoscale forecast models into GIS to extrapolate road conditions across a region. For example, Chapman et al. (2001) numerically model road surface temperature using weather data and a geo- graphical parameter database consisting of latitude, sky-view factor, screening, altitude, topography, road construction, surface roughness and traffic (anthropogenic heat). These parameters are combined in a numerical model that predicts up to 72% of the variation in road surface temperature across a study route to within 1.06°C RMS. Bradley et al. (2002) used a spatial analysis of topography and classified Landsat imagery to model the impact of the urban heat island on road surface temperatures in the West Midlands, UK. Winter road maintenance provides one example of how GIS can be combined with weather data to solve a logistical problem. Li and Eglese (1996) used a GIS to devise an heuristic algorithm to optimize winter salting routes with respect to minimizing the distance travelled and treated by gritters within the temporal framework of the time roads need to be treated. Similar ideas are utilized by Moore et al. (1995) and Patel and Horowitz (1994) who use GIS to develop optimal and specific routing for radioactive and hazardous materials. This is achieved by combining spatial information of meteorology, demography and dispersion (i.e., wind-speed, toxicity and size of spill) with vector road data. 8 Urban environments Pollution is a major problem in urban environments and the largest contributing factor is traffic. Hao et al. (2001) produced a GIS-based emission inventory for Beijing, China. By using a Gaussian dispersion air quality model, it was shown that vehicle sources contributed 76.5% and 68.4% of the total CO and NOx emission totals, respectively. Emissions are modelled using traffic counts and empirical equations, for example, Mensink et al. (2000) modelled CO, NOx, VOC, PM, SO2, and Pb emissions in Antwerp as a function of ambient air temperature with six road and vehicle parameters. New bespoke technologies are constantly being developed to improve the accuracy of incoming information. Global positioning systems interfaced in a GIS can now be used to monitor traffic (Taylor et al., 2000) and high performance 3D GIS models of air pollution and traffic simulation are being developed (McHugh et al., 1997; Morselli et al., 1997; Schmidt and Schafer, 1998). For example, Zakarin and Mirkarimova (2000) numerically model urban air pollution using GIS as an interface; a common approach of displaying emissions inventory data produced using dispersion models (e.g., Fedra and Haurie, 1999; Prabha and Mursch-Radlgruber, 1999). Other than traffic, further L. Chapman and J.E. Thornes 323 sources of urban pollution exist as a result of human activity. Chang et al. (1999) used a 3D diffusion model displayed in a GIS for use in risk assessment studies in industrial areas of Taiwan, whereas Romero et al. (1999) studied how rapid urban growth and surrounding topography impacted upon air pollution in Santiago, Chile. Other than pollution, climate modelling studies involving GIS in urban environ- ments are mostly all directed at studying the urban heat island phenomenon. The common approach is to integrate remote sensing data with GIS to produce an appraisal of how temperature is spatially controlled by land use (Lo et al., 1997). GIS can then be used further to monitor the impacts of urban growth. For example, Weng (2001) found that urban development in the Zhujiang Delta, China could account for increasing surface radiant temperatures by 13°C. GIS has also facilitated increased study into the vertical structure of the heat island phenomenon (Nichol, 1998), which is then used for planning applications such as climate control in high-rise buildings in tropical cities. The development of a planning tool was also the aim of Scherer et al. (1999), who used GIS to produce a series of climate maps documenting the influence of surface properties on temperature, wind fields and ventilation for Basel, Switzerland. 9 Energy Temperature and humidity are the primary factors controlling energy demand. The higher the ambient temperature, the less energy is consumed by users and hence trans- mission operators monitor the weather to efficiently manage production. Estimates of demand can be made by considering degree days (Hargy, 1997), although other envi- ronmental indicators are more commonly used for the energy planning of urban areas (Balocco and Grazzini, 2000). GIS is used to monitor the entire infrastructure of energy provision. As well as being an invaluable tool to match supply with demand (Sorensen and Meibom, 1999), real-time lightning and storm data are also incorporated into decision support systems to track potential problems along transmission lines. As fossil fuel supplies diminish, research is ongoing into the increased application of renewable energy. GIS has been used to aid the locations of wind farms by modelling wind energy potential whilst considering planning limitations (e.g., Hillring and Krieg, 1998; Baban and Parry, 2001). By linking satellite data with a GIS, optimization of other renewable resources can be achieved. For example, this technique is used to identify and monitor biomass energy resources (Phillips et al., 1992) and to estimate solar resources such as potential downward radiation, cloud regimes and albedo. Solar information is then matched with population data in a GIS to model supply and demand (Sorensen, 2001), before being used to site thermal power plants (Vandenbergh et al., 1999; Broesamle et al., 2000). Overall, the role of GIS is seen as critical in increasing exploitation of renewable energy sources, particularly biomass, which is seen as an essential component in reducing global carbon emissions from the energy sector (Schneider et al., 2001). 10 Climate change Much, if not all, of the research discussed in this review is potentially subject to the impact of climate change. GIS has become a visualization tool for the output of climate 324 Use of GIS in climatology and meteorology models such as general circulation models used to predict the global impacts of hypoth- esized climate change scenarios. Many articles exist in the scientific literature, far too numerous to list here, however good examples of potential effects modelled with GIS include changes to agricultural and ecological distributions (e.g., Eatherall, 1997; Davies et al., 1998), varying public health implications (e.g., Patz and Balbus, 1996), increases in landscape sensitivity (e.g., Collison et al., 2000; Thumerer et al., 2000) and varying pressures on hydrological resources (e.g., Strzepek and Yates, 1997). Hence, the assessment and monitoring of the effects of climate change is truly a multidisciplinary exercise of which GIS provides a pivotal unifying role (Din, 1992; Kozoderov, 1995). Although many of the predicted impacts of climate change are ultimately hypothe- sized as future events, GIS has already been used to present evidence of environmental change. For example, Chen (2001) showed that tree diversity was changing in northeast China and Jorgenson et al. (2001) demonstrated evidence of widespread permafrost degradation in Alaska. However, few monitoring studies are currently evident in the scientific literature, which perhaps indicates the alarmist tendencies of projected climate change scenarios. Continued monitoring with GIS using data from satellite Earth observation will ultimately confirm or disprove current thinking. Either way, future studies are heavily dependent on data-intensive GIS-based spatial analysis. IV Conclusions Over the last decade, research has greatly increased into the use of GIS in a variety of applications involving the processing of climatological and meteorological data. GIS can be used for deriving and enhancing point weather data by the use of DEMs, or alternatively used as a spatial input dataset to provide boundary conditions for a wide number of tertiary applications. Reasons for the upsurge in use of GIS are largely related to the fall in price of COTS GIS products, coupled with large advances in computer processing ability. Add to this the proliferation of the Internet and the result is a fast real-time bespoke solution for many end-users. Commercial interest in such products is massive, be it for risk assessment (e.g., storm tracking) or for mitigation purposes (e.g., insurance claims from flooding and fire). As computer systems become increasingly capable of handling the high resolution datasets provided by twenty-first century Earth observation techniques, the future of GIS in climatology and meteorology research is virtually assured. The advent of COTS products has facilitated the development of standard formats for spatial weather data with GIS providing the management tool. The manipulation of spatial data by meteo- rologists and climatologists has never been easier. Acknowledgements This work has been partly funded by the EU COST 719 directive to increase the use of GIS in climatological and meteorological research. L. Chapman and J.E. Thornes 325 References Agnew, M.D. and Palutikof, J.P. 2000: GIS-based construction of baseline climatologies for the Mediterranean using terrain variables. Climate Research 14, 11527. Andronopoulos, S., Passamichali, A., Gounaris, N. and Bartzis, J.G. 2000: Evolution and transport of pollutants over a Mediterranean coastal area: the influence of biogenic volatile organic compound emissions on ozone concen- trations. Journal of Applied Meteorology 39, 52645. Antonic, O., Krizan, J., Marki, A. and Bukovec, D. 2001: Spatio-temporal interpolation of climatic variables over large region of complex terrain using neural networks. Ecological Modelling 138, 25563. Baban, S.M.J. and Parry, T. 2001: Developing and applying a GIS-assisted approach to locating wind farms in the UK. Renewable Energy 24, 5971. Balocco, C. and Grazzini, G. 2000: Thermodynamic parameters for energy sus- tainability of urban areas. Solar Energy 69, 35156. Bavia, M.E., Malone, J.B., Hale, L., Dantas, A., Marroni, L. and Reis, R. 2001: Use of thermal and vegetation index data from earth observing satellites to evaluate the risk of schistosomiasis in Bahia, Brazil. Acta Tropica 79, 7985. Belda, F. and Melia, J. 2000: Relationships between climatic parameters and forest vegetation: application to burned area in Alicante (Spain). Forest Ecology and Management 135, 195204. Bell, V.A. and Moore, R.J. 1998: A grid-based distributed flood forecasting model for use with weather radar data: Part 1. Formulation. Hydrology and Earth System Sciences 2, 26581. 1999: An elevation-dependent snowmelt model for upland Britain. Hydrological Processes 13, 1887903. Benjamin, M.T., Sudol, M., Vorsatz, D. and Winer, A.M. 1997: A spatially and temporally resolved biogenic hydrocarbon emissions inventory for the California South Coast Air Basin. Atmospheric Environment 31, 3087100. Bergquist, N.R. 2001: Vector-borne parasitic diseases: new trends in data collection and risk assessment. Acta Tropica 79, 1320. Bernherdson, T. 1992: Geographic information systems. Arendal, Norway: Viak IT and Norwegian Mapping Authority. Birnie, R.V., Miller, D.R., Horne, P.L., Leadbeater, S. and Macdonald, A. 2000: The potential distribution and impact of bracken in upland Scotland: an assessment using a GIS- based niche model. Annals of Botany 85, 5362. Blennow, K. 1998: Modelling minimum air temperature in partially and clear felled forests. Agricultural and Forest Meteorology 91, 22335. Blennow, K. and Lindkvist, L. 2000: Models of low temperature and high irradiance and their application to explaining the risk of seedling mortality. Forest Ecology and Management 135, 289301. Boag, B., Jones, H.D., Evans, K.A., Neilson, R., Yeates, G.W. and Johns, P.M. 1998: The application of GIS techniques to estimate the establishment and potential spread of Artioposthia triangulata in Scotland. Pedobiologia 42, 50410. Bradley, A.V., Thornes, J.E., Chapman, L., Unwin, D. and Roy, M. 2002: Modelling spatial and temporal road thermal climatology in rural and urban areas using a GIS. Climate Research 21, 4155. Broesamle, H., Mannstein, H., Schillings, C. and Trieb, F. 2000: Assessment of solar electricity potentials in North Africa based on satellite data and a geographic information system. Solar Energy 70, 112. Bruland, O., Sand, K. and Killingtveit, A. 2001: Snow distribution at a high Arctic site at Svalbard. Nordic Hydrology 32, 112. Carbone, G.J., Narumalani, S. and King, M. 1996: Application of remote sensing and GIS technologies with physiological crop models. Photogrammetric Engineering and Remote Sensing 62, 17179. Carpenter, T.M., Sperfslage, J.A., Georgakakos, K.P., Sweeney, T. and Fread, D.L. 1999: National threshold runoff estimation utilising GIS in support of operational flash flood warning systems. Journal of Hydrology 224, 2144. Cazorzi, F. and DallaFontana, G. 1996: Snowmelt modelling by combining air temperature and a distributed radiation index. Journal of Hydrology 181, 16987. Chang, N.B., Kao, C.Y.J., Wei, Y.L. and Tseng, C.C. 1999: Comparative study of 3D numerical and puff models for dense air pollutants. Journal of Environmental Engineering 125, 17584. Chapman, L., Thornes, J.E. and Bradley, A.V. 2001: Modelling of road surface temperature from a geographical parameter database. Part 326 Use of GIS in climatology and meteorology 2: numerical. Meteorological Applications 8, 42136. Chen, X.W. 2001: Change of tree diversity on Northeast China transect (NECT). Biodiversity and Conservation 10, 108796. Cheng, E. and Shang, J. 1998: Kinematic flow model based extreme wind simulation. Journal of Wind Engineering and Industrial Aerodynamics 7778, 111. Cline, D., Elder, K. and Bales, R. 1998: Scale effects in a distributed snow water equivalence and snowmelt model for mountain basins. Hydrological Processes 12, 152736. Collison, A., Wade, S., Griffiths, J. and Dehn, M. 2000: Modelling the impact of predicted climate change on landslide frequency and magnitude in SE England. Engineering Geology 55, 20518. Cornford, D. and Thornes, J.E. 1996: A comparison between spatial winter indices and expenditure on winter road maintenance in Scotland. International Journal of Climatology 16, 33957. Daly, C., Neilson, R.P. and Phillips, D.L. 1994: A statistical-topographic model for mapping climatological precipitation over mountainous terrain. Journal of Applied Meteorology 33, 14058. Daly, C., Taylor, G.H., Gibson, W.P., Parzybok, T.W., Johnson, G.L. and Pasteris, P.A. 2000: High-quality spatial climate data sets for the United States and beyond. Transactions of the American Society of Agricultural Engineers (ASEA) 43, 195762. Davies, A., Jenkins, T., Pike, A., Shao, J., Carson, I., Pollock, C.J. and Parry, M.L. 1998: Modelling the predicted geographic and economic response of UK cropping systems to climate change scenarios: the case of sugar beet. Annals of Applied Biology 133, 13548. de Azevedo, E.B., Pereira, L.S. and Itier, B. 1999: Modelling the local climate in island environ- ments: water balance applications. Agricultural Water Management 40, 393403. del Barrio, G., Alvera, B., Puigdefabregas, J. and Diez, C. 1997: Response of high mountain landscape to topographic variables: Central Pyrenees. Landscape Ecology 12, 95115. Din, A.M. 1992: Global environmental change data and modelling. International Federation for Information Processing (IFIP) Transactions A Computer Science and Technology 13, 62534. Dubayah, R.C. 1994: Modelling a solar radiation topoclimatology for the Rio-Grande river basin. Journal of Vegetation Science 5, 62740. Eatherall, A. 1997: Modelling climate change impacts on ecosystems using linked models and a GIS. Climatic Change 35, 1734. El Garouani, A., Boussema, M.R. and Ennabli, H. 2000: Use of the Geographic Information System and remote sensing data for the estimation of real evapotranspiration at a regional scale. International Journal of Remote Sensing 21, 281130. Ellis, E.A., Nair, P.K.R., Linehan, P.E., Beck, H.W. and Blanche, C.A. 2000: A GIS-based database management application for agroforestry planning and tree selection. Computers and Electronics in Agriculture 27, 4155. Fedra, K. and Haurie, A. 1999: A decision support system for air quality management combining GIS and optimisation techniques. International Journal of Environment and Pollution 12, 12546. Fily, M., Dedieu, J.P. and Durand, Y. 1999: Comparison between the results of a snow metamorphism model and remote sensing derived snow parameters in the Alps. Remote Sensing of Environment 68, 25463. Fleming, M.D., Chapin, F.S., Cramer, W., Hufford, G.L. and Serreze, M.C. 2000: Geographic patterns and dynamics of Alaskan climate interpolated from a sparse station record. Global Change Biology 6, 4958. Foster, D.R. and Boose, E.R. 1992: Patterns of forest damage resulting from catastrophic winds in central New-England. Journal of Ecology 80, 7998. Franklin, J. 1998: Predicting the distribution of shrub species in southern California from climate and terrain-derived variables. Journal of Vegetation Science 9, 73348. Gabella, M. and Perona, G. 1998: Simulation of the orographic influence on weather radar using a geometric-optics approach. Journal of Atmospheric and Oceanic Technology 15, 148594. Ghosh, T.K. 1997: Investigation of drought through digital analysis of satellite data and geographical information systems. Theoretical and Applied Climatology 58, 10512. Goodale, C.L., Aber, J.D. and Ollinger, S.V. 1998: Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model. Climate Research 10, 3549. Gorokhovich, Y., Khanbilvardi, R., Janus, L., Goldsmith, V. and Stern, D. 2000: Spatially distributed modelling of stream flow during storm events. Journal of the American Water Resources Association 36, 52339. Guisan, A. and Theurillat, J.P. 2000: Equilibrium L. Chapman and J.E. Thornes 327 modelling of alpine plant distribution: how far can we go? Hytocoenologia 30, 35384. Gustavsson, T., Bogren, J. and Eriksson, M. 1998: GIS as a tool for planning new road stretches in respect of climatological factors. Theoretical and Applied Climatology 60, 17990. Hao, J.M., Wu, Y., Fu, L.X., He, D.Q. and He, K.B. 2001: Source contributions to ambient concen- trations of CO and NOX in the urban area of Beijing. Journal of Environmental Science and Health Part A. Toxic/Hazardous Substances and Environmental Engineering 36, 21528. Hargy, V.T. 1997: Objectively mapping accumulated temperature for Ireland. International Journal of Climatology 17, 90927. Hijmans, R.J., Forbes, G.A. and Walker, T.S. 2000: Estimating the global severity of potato late blight with GIS-linked disease forecast models. Plant Pathology 49, 697705. Hill, M.J., Donald, G.E., Vickery, P.J. and Furnival, E.P. 1996: Integration of satellite remote sensing, simple bioclimatic models and GIS for assessment of pastoral development for a commercial grazing enterprise. Australian Journal of Experimental Agriculture 36, 30921. Hillring, B. and Krieg, R. 1998: Wind energy potential in southern Sweden Example of planning methodology. Renewable Energy 13, 47179. Hortal, J., Lobo, J.M. and Martin-Piera, F. 2001: Forecasting insect species richness scores in poorly surveyed territories: the case of the Portuguese dung beetles (Col. Scarabaeinae). Biodiversity and Conservation 10, 134367. Hudson, G. and Wackernagel, H. 1994: Mapping temperature using kriging with external drift theory and an example from Scotland. International Journal of Climatology 14, 7791. Jarvis, C.H. and Stuart, N. 2001: A comparison among strategies for interpolating maximum and minimum daily air temperatures. Part II: The interaction between number of guiding variables and the type of interpolation method. Journal of Applied Meteorology 40, 107584. Jeffrey, S.J., Carter, J.O., Moodie, K.B. and Beswick, A.R. 2001: Using spatial interpolation to construct a comprehensive archive of Australian climate data. Environmental Modelling and Software 16, 30930. Jones, P.G., Beebe, S.E., Tohme, J. and Galwey, N.W. 1997: The use of geographical informa- tion systems in biodiversity exploration and conservation. Biodiversity and Conservation 6, 94758. Jorgenson, M.T., Racine, C.H., Walters, J.C. and Osterkamp, T.E. 2001: Permafrost degradation and ecological changes associated with a warming climate in central Alaska. Climatic Change 48, 55179. Jurisic, M., Hengl, T., Duvnjak, V. and Martinic, I. 1999: Agro-ecological and land information system. Storjarstvo 41, 22331. Kadmon, R. and Danin, A. 1999: Distribution of plant species in Israel in relation to spatial variation in rainfall. Journal of Vegetation Science 10, 42132. Kadmon, R. and Heller, J. 1998: Modelling faunal responses to climatic gradients with GIS: land snails as a case study. Journal of Biogeography 25, 52739. Knox, J.W., Matthews, R.B. and Wassmann, R. 2000: Using a crop/soil simulation model and GIS techniques to assess methane emissions from rice fields in Asia. III. Databases. Nutrient Cycling in Agroecosystems 58, 17999. Kozoderov, V.V. 1995: A scientific approach to employ monitoring and modelling techniques for global change and terrestrial ecosystems and other related projects. Journal of Biogeography 22, 92733. Kravchenko, A.N., Bullock, D.G. and Boast, C.W. 2000: Joint multifractal analysis of crop yield and terrain slope. Agronomy Journal 92, 127990. Kumar, K.V., Bhattacharya, A. and Subramanyam, C. 1998: Coastal morphological influence for tropical cyclone track deviation along Andhra coast: GIS and remote sensing- based approach. Current Science 75, 95558. Lapen, D.R. and Martz, L.W. 1996: An investiga- tion of the spatial association between snow depth and topography in a Prairie agricultural landscape using digital terrain analysis. Journal of Hydrology 184, 27798. Lekes, V. and Dandul, I. 2000: Using airflow modelling and spatial analysis for defining wind damage risk classification (WINDARC). Forest Ecology and Management 135, 33144. Lennon, J.J. and Turner, J.R.G. 1995: Predicting the spatial distribution of climate temperature in Great Britain. Journal of Animal Ecology 64, 37092. Levizzani, V., Schmetz, J., Lutz, H.J., Kerkmann, J., Alberoni, P.P. and Cervino, M. 2001: Precipitation estimations from geostationary orbits and prospects for METEOSAT Second Generation. Meteorological Applications 8, 2341. Li, L.Y.O. and Eglese, R.W. 1996: An interactive algorithm for vehicle routing for winter 328 Use of GIS in climatology and meteorology gritting. Journal of the Operational Research Society 47, 21728. Lindsay, S.W. and Thomas, C.J. 2000: Mapping and estimating the population at risk from lymphatic filariasis in Africa. Transactions of the Royal Society of Tropical Medicines and Hygiene 94, 3745. Lo, C.P., Quattrochi, D.A. and Luvall, J.C. 1997: Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. International Journal of Remote Sensing 18, 287304. Lourens, U.W. and deJager, J.M. 1997: A comput- erised crop-specific drought monitoring system: design concepts and initial testing. Agricultural Systems 53, 30315. Malone, J.B., Bergquist, N.R., Huh, O.K., Bavia, M.E., Bernardi, M., El Bahy, M.M., Fuentes, M.V., Kristensen, T.K., McCarroll, J.C., Yilma, J.M. and Zhou, X.N. 2001: A global network for the control of snail-borne disease using satellite surveillance and geographic information systems. Acta Tropica 79, 712. Manguin, S. and Boussinesq, M. 1999: Remote sensing in public health: applications to malaria and other diseases. Medicene et Maladies Infectieuses 29, 31824. Matthews, R.B., Wassmann, R., Knox, J.W. and Buendia, L.V. 2000: Using a crop/soil simulation model and GIS techniques to assess methane emissions from rice fields in Asia. IV. Upscaling to national levels. Nutrient Cycling in Ecosystems 58, 20117. McHugh, C.A., Carruthers, D.J. and Edmunds, H.A. 1997: ADMS and ADMS-Urban. Inter- national Journal of Environment and Pollution 8, 43840. McKenney, D.W., Hutchinson, M.F., Kesteven, J.L. and Venier, L.A. 2001: Canada's plant hardiness zones revisited using modern climate interpolation techniques. Canadian Journal of Plant Science 81, 12943. Menkir, A., Kling, J.G., Jagtap, S.S. and Aliu, B.A. 2000: GIS based classification of maize testing locations in West and Central Africa. Maydica 45, 14350. Mensink, C., De Vlieger, I. and Nys, J. 2000: An urban transport emission model for the Antwerp area. Atmospheric Environment 27, 4595602. Morselli, M.G., Calori, G., Finardi, S. and Mazzola, C. 1997: A 3-D wind and temperature pre-processor for ATD models. International Journal of Environment and Pollution 8, 48999. Moore, I.D., Norton, T.W. and Williams, J.E. 1993: Modelling environmental heterogeneity in forested landscapes. Journal of Hydrology 150, 71747. Moore, J.E., Sandquist, G.M. and Slaughter, D.M. 1995: A route-specific system for risk assessment of radioactive materials transporta- tion accidents. Nuclear Technology 112, 6378. Nichol, J.E. 1994: An examination of tropical rainforest microclimate using GIS modelling. Global Ecology and Biogeography Letters 4, 6978. 1995: Monitoring tropical rainforest micro- climate. Photogrammetric Engineering and Remote Sensing 61, 115965. 1998: Visualisation of urban surface temper- atures derived from satellite images. International Journal of Remote Sensing 19, 163949. Ninyerola, M., Pons, X. and Roure, J.M. 2000: A methodological approach of climatological modelling of air temperature and precipitation through GIS techniques. International Journal of Climatology 20, 182341. Panigrahy, S. and Chakraborty, M. 1998: An integrated approach for potato crop intensifica- tion using temporal remote sensing data. Journal of Photogrammetric Engineering and Remote Sensing 53, 5460. Patel, M.H. and Horowitz, A.J. 1994: Optimal routing of hazardous materials considering risk of spill. Transportation Research Part A. Policy and Practice 28, 11932. Patz, J.A. and Balbus, J.M. 1996: Methods for assessing public health vulnerability to global climate change. Climate Research 6, 11325. Pew, K.L. and Larsen, C.P.S. 2001: GIS analysis of spatial and temporal patterns of human-caused wildfires in the temperate rain forest of Vancouver Island, Canada. Forest Ecology and Management 140, 118. Pfister, A. and Fischer, H. 1995: Influence of the topography of the surface of the earth on vertical sounding of the temperature profile. Annales Geophysicae Atmospheres Hydrospheres and Space Sciences 13, 31829. Phillips, V.D., Singh, D., Khan, M.A. and Takahashi, P.K. 1992: Preliminary assessment of biomass energy resources in Hawaii. Energy Sources 14, 38189. Pleshikov, F.I., Ryzkova, V.A., Kaplunov, V.Y. and Usoltseva, J.V. 1998: A computer system for evaluating and predicting hurricane impact on forest. Safety Science 30, 38. Prabha, T.V. and Mursch-Radlgruber, E 1999: Investigation of air pollution distribution in Linz: case studies to evaluate a K-type diffusion model coupled with a mass-consistent wind L. Chapman and J.E. Thornes 329 model. Atmospheric Environment 33, 406780. Priya, S. and Shibasaki, R. 2001: National spatial crop yield simulation using GIS-based crop production model. Ecological Modelling 136, 11329. Prudhomme, C. 1999: Mapping a statistic of extreme rainfall in a mountainous region. Physics and Chemistry of the Earth Part B. Hydrology Oceans and Atmosphere 24, 7984. Reinke, K., Butcher, E.C., Russell, C.J., Nicholls, D.G. and Murray, M.D. 1998: Understanding the flight movements of a non-breeding wandering albatross, Diomedea exulans gibsoni, using a geographic information system. Australian Journal of Zoology 46, 17181. Rigol, J.P., Jarvis, C.H. and Stuart, N. 2001: Artificial neural networks as a tool for spatial interpolation. International Journal of Geographical Information Science 15, 32343. Romero, H., Ihl, M., Rivera, A., Zalazar, P. and Azocar, P. 1999: Rapid urban growth, land-use changes and air pollution in Santiago, Chile. Atmospheric Environment 33, 403947. Schadlich, S., Gottsche, F.M. and Olesen, F.S. 2001: Influence of land surface parameters and atmosphere on METEOSAT brightness temper- atures and generation of land surface temperature maps by temporally and spatially interpolating atmospheric correction. Remote Sensing of Environment 75, 3946. Scherer, D., Fehrenbach, U., Beha, H.D. and Parlow, E. 1999: Improved concepts and methods in analysis and evaluation of the urban climate for optimising urban planning processes. Atmospheric Environment 33, 418593. Schmidt, M. and Schafer, R.P. 1998: An integrated simulation system for traffic induced air pollution. Environmental Modelling and Software 13, 295303. Schneider, L.C., Kinzig, A.P., Larson, E.D. and Solorzano, L.A. 2001: Method for spatially explicit calculations of potential biomass yields and assessment of laud availability for biomass energy production in northeastern Brazil. Agriculture Ecosystems and Environment 84, 20726. Shevenell, L. 1999: Regional potential evapotran- spiration in arid climates based on temperature, topography and calculated solar radiation. Hydrological Processes 13, 57796. Soderstrom, M. and Magnusson, B. 1995: Assessment of local agroclimatic conditions: a methodology. Agricultural and Forest Meteorology 72, 24360. Sorensen, B. 2001: GIS management of solar resource data. Solar Energy Materials and Solar Cells 67, 503509. Sorensen, B. and Meibom, P. 1999: GIS tools for renewable energy modelling. Renewable Energy 16, 126267. Sousa, V. and Pereira, L.S. 1999: Regional analysis of irrigation water requirements using kriging Application to potato crop (Solanum tuberosum L.) at Tras-os-Montes. Agricultural Water Management 40, 22133. Srivastava, A., Nagpal, B.N., Saxena, R. and Subbarao, S.K. 2001: Predictive habitat modelling for forest malaria vector species An. dirus in India a GIS-based approach. Current Science 80, 112934. Strzepek, K.M. and Yates, D.N. 1997: Climate change impacts on the hydrologic resources of Europe: a simplified continental scale analysis. Climatic Change 36, 7992. Suga, Y., Takeuchi, S., Kimura, H. and Inanga, A. 1995: Environmental monitoring of land and sea surface using multisensors. Calibration and Application of Satellite Sensors for Environmental Monitoring 17, 97106. Sunar, F. and Ozkan, C. 2001: Forest fire analysis with remote sensing data. International Journal of Remote Sensing 22, 226577. Tappeiner, U., Tappeiner, G., Aschenwald, J., Tasser, E. and Ostendorf, B. 2001: GIS-based modelling of spatial pattern of snow cover duration in an alpine area. Ecological Modelling 138, 26575. Taschner, S., Ludwig, R. and Mauser, W. 2001: Multi-scenario flood modelling in a mountain watershed using data from a NWP model, rain radar and rain gauges. Physics and Chemistry of the Earth Part B. Hydrology Oceans and Atmosphere 26, 50915. Taylor, M.A.P., Woolley, J.E. and Zito, R. 2000: Integration of the global positioning system and geographical information systems for traffic congestion studies. Transportation Research Part C Emerging Technologies 8, 25785. Thumerer, T., Jones, A.P. and Brown, D. 2000: A GIS based coastal management system for climate change associated flood risk assess- ment on the east coast of England. International Journal of Geographical Information Science 14, 26581. Tsanis, I.K. and Gad, M.A. 2001: A GIS precipita- tion method for analysis of storm kinematics. Environmental Modelling and Software 16, 27381. Tveito, O.E., Førland, E.J., Alexandersson, H., 330 Use of GIS in climatology and meteorology Drebs, A., Jónsson, T., Tuomenvirta, H. and Vaarby Laursen, E. 2001: Nordic climate maps. DNMI Report Number 06/01. http:// www.smhi.se/hfa_coord/nordklim/report06_ 2001.pdf (last accessed 15 April 2003). Udouj, T.H. and Scott, H.D. 1999: Simulated phosphorus and sediment loadings in two rep- resentative subbasins of the Illinois River. Journal of Soil Contamination 8, 50926. Valdes, M.C., Stiff, C. and Dechert, T.V. 1994: Site quality evaluation and yield of Pinus occurpa in Honduras Central Zone. Interciencia 19, 33646. Vandenbergh, M., Neirac, F.P. and Turki, H. 1999: A GIS approach for the siting of solar thermal power plants application to Tunisia. Journal de Physique IV 9, 22328. van Wesenbeeck, I.J. and Havens, P.L. 1999: A groundwater exposure assessment for cloransulam-methyl in the US soybean market. Journal of Environmental Quality 28, 51322. Vazquez, A. and Moreno, J.M. 2001: Spatial dis- tribution of forest fires in Sierra de Gredos (Central Spain). Forest Ecology and Management 147, 5565. Verdebout, J. 2000: A method to generate surface UV radiation maps over Europe using GOME, Meteosat, and ancillary geophysical data. Journal of Geophysical Research Atmospheres 105, 504958. Waluda, C.M., Rodhouse, P.G., Trathan, P.N. and Pierce, G.J. 2001: Remotely sensed mesoscale oceanography and the distribution of Illex argentinus in the South Atlantic. Fisheries Oceanography 10, 20716. Weiss, S.B. and Weiss, A.D. 1998: Landscape- level phenology of a threatened butterfly: a GIS-based modeling approach. Ecosystems 1, 299309. Weng, Q. 2001: A remote sensing-GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China. International Journal of Remote Sensing 22, 19992014. Wilk, J. and Andersson, L. 2001: GIS-supported modelling of areal rainfall in a mountainous river basin with monsoon climate in southern India. Hydrological Sciences Journal 45, 185202. Wooldridge, S.A., Franks, S.W. and Kalma, J.D. 2001: Hydrological implications of the Southern Oscillation: variability of the rainfall runoff relationship. Hydrological Sciences Journal 46, 7388. Worboys, M.F. 1995: GIS: a computing perspective. London: Taylor and Francis. Wu, J.J. and Babcock, B.A. 1999: Metamodeling potential nitrate water pollution in the central United States. Journal of Environmental Quality 28, 191628. Yajima, M. 1996: Monitoring regional rice development and cool-summer damage. Japan Agricultural Research Quarterly 30, 13943. Yarnal, B. Lakhtakia, M.N., Yu, Z., White, R.A., Pollard, D., Miller, D.A. and Lapenta, W.M. 2000: A linked meteorological and hydrological model system: the Susquehanna River Basin Experiment (SRBEX). Global and Planetary Change 25, 14961. Zakarin, E.A. and Mirkarimova, B.M. 2000: GIS- based mathematical modelling of urban air pollution. Journal of Atmospheric and Oceanic Physics 36, 33442. Zheng, X., Pierce, G.J. and Reid, D.G. 2001: Spatial patterns of whiting abundance in Scottish waters and relationships with environ- mental variables. Fisheries Research 50, 25970. Zhu, Q.J., Rong, T.Z. and Sun, R. 2000: A case study on fractal simulation of forest fire spread. Science in China Series E Technological Sciences 43, 104U2 Suppl. </meta-value></custom-meta></custom-meta-wrap></article-meta></front><back><ref-list><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Agnew, M. D.</surname></name> and <name name-style="western"><surname>Palutikof, J. P.</surname></name><year>2000</year>: <article-title>GIS-based construction of baseline climatologies for the Mediterranean using terrain variables</article-title>. <source>Climate Research</source><volume>14</volume>, <fpage>115</fpage>-<lpage>127</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Andronopoulos, S.</surname></name>, <name name-style="western"><surname>Passamichali, A.</surname></name>, <name name-style="western"><surname>Gounaris, N.</surname></name> and <name name-style="western"><surname>Bartzis, J. G.</surname></name><year>2000</year>: <article-title>Evolution and transport of pollutants over a Mediterranean coastal area: the influence of biogenic volatile organic compound emissions on ozone concentrations</article-title>. <source>Journal of Applied Meteorology</source><volume>39</volume>, <fpage>526</fpage>-<lpage>545</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Antonic, O.</surname></name>, <name name-style="western"><surname>Krizan, J.</surname></name>, <name name-style="western"><surname>Marki, A.</surname></name> and <name name-style="western"><surname>Bukovec, D.</surname></name><year>2001</year>: <article-title>Spatio-temporal interpolation of climatic variables over large region of complex terrain using neural networks</article-title>. <source>Ecological Modelling</source><volume>138</volume>, <fpage>255</fpage>-<lpage>263</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Baban, S. M. J.</surname></name> and <name name-style="western"><surname>Parry, T.</surname></name><year>2001</year>: <article-title>Developing and applying a GIS-assisted approach to locating wind farms in the UK</article-title>. <source>Renewable Energy</source><volume>24</volume>, <fpage>59</fpage>-<lpage>71</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Balocco, C.</surname></name> and <name name-style="western"><surname>Grazzini, G.</surname></name><year>2000</year>: <article-title>Thermodynamic parameters for energy sustainability of urban areas</article-title>. <source>Solar Energy</source><volume>69</volume>, <fpage>351</fpage>-<lpage>356</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Bavia, M. E.</surname></name>, <name name-style="western"><surname>Malone, J. B.</surname></name>, <name name-style="western"><surname>Hale, L.</surname></name>, <name name-style="western"><surname>Dantas, A.</surname></name>, <name name-style="western"><surname>Marroni, L.</surname></name> and <name name-style="western"><surname>Reis, R.</surname></name><year>2001</year>: <article-title>Use of thermal and vegetation index data from earth observing satellites to evaluate the risk of schistosomiasis in Bahia, Brazil</article-title>. <source>Acta Tropica</source><volume>79</volume>, <fpage>79</fpage>-<lpage>85</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Belda, F.</surname></name> and <name name-style="western"><surname>Melia, J.</surname></name><year>2000</year>: <article-title>Relationships between climatic parameters and forest vegetation: application to burned area in Alicante (Spain)</article-title>. <source>Forest Ecology and Management</source><volume>135</volume>, <fpage>195</fpage>-<lpage>204</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Bell, V. A.</surname></name> and <name name-style="western"><surname>Moore, R. J.</surname></name><year>1998</year>: <article-title>A grid-based distributed flood forecasting model for use with weather radar data: Part 1. Formulation</article-title>. <source>Hydrology and Earth System Sciences</source><volume>2</volume>, <fpage>265</fpage>-<lpage>281</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Bell, V. A.</surname></name> and <name name-style="western"><surname>Moore, R. J.</surname></name><year>1999</year>: <article-title>An elevation-dependent snowmelt model for upland Britain</article-title>. <source>Hydrological Processes</source><volume>13</volume>, <fpage>1887</fpage>-<lpage>1903</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Benjamin, M. T.</surname></name>, <name name-style="western"><surname>Sudol, M.</surname></name>, <name name-style="western"><surname>Vorsatz, D.</surname></name> and <name name-style="western"><surname>Winer, A. M.</surname></name><year>1997</year>: <article-title>A spatially and temporally resolved biogenic hydrocarbon emissions inventory for the California South Coast Air Basin</article-title>. <source>Atmospheric Environment</source><volume>31</volume>, <fpage>3087</fpage>-<lpage>3100</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Bergquist, N. R.</surname></name><year>2001</year>: <article-title>Vector-borne parasitic diseases: new trends in data collection and risk assessment</article-title>. <source>Acta Tropica</source><volume>79</volume>, <fpage>13</fpage>-<lpage>20</lpage>.</citation></ref><ref><citation citation-type="book" xlink:type="simple"><name name-style="western"><surname>Bernherdson, T.</surname></name><year>1992</year>: <source>Geographic information systems</source>. <publisher-loc>Arendal, Norway</publisher-loc>: <publisher-name>Viak IT and Norwegian Mapping Authority</publisher-name>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Birnie, R. V.</surname></name>, <name name-style="western"><surname>Miller, D. R.</surname></name>, <name name-style="western"><surname>Horne, P. L.</surname></name>, <name name-style="western"><surname>Leadbeater, S.</surname></name> and <name name-style="western"><surname>Macdonald, A.</surname></name><year>2000</year>: <article-title>The potential distribution and impact of bracken in upland Scotland: an assessment using a GIS-based niche model</article-title>. <source>Annals of Botany</source><volume>85</volume>, <fpage>53</fpage>-<lpage>62</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Blennow, K.</surname></name><year>1998</year>: <article-title>Modelling minimum air temperature in partially and clear felled forests</article-title>. <source>Agricultural and Forest Meteorology</source><volume>91</volume>, <fpage>223</fpage>-<lpage>235</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Blennow, K.</surname></name> and <name name-style="western"><surname>Lindkvist, L.</surname></name><year>2000</year>: <article-title>Models of low temperature and high irradiance and their application to explaining the risk of seedling mortality</article-title>. <source>Forest Ecology and Management</source><volume>135</volume>, <fpage>289</fpage>-<lpage>301</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Boag, B.</surname></name>, <name name-style="western"><surname>Jones, H. D.</surname></name>, <name name-style="western"><surname>Evans, K. A.</surname></name>, <name name-style="western"><surname>Neilson, R.</surname></name>, <name name-style="western"><surname>Yeates, G. W.</surname></name> and <name name-style="western"><surname>Johns, P. M.</surname></name><year>1998</year>: <article-title>The application of GIS techniques to estimate the establishment and potential spread of Artioposthia triangulata in Scotland</article-title>. <source>Pedobiologia</source><volume>42</volume>, <fpage>504</fpage>-<lpage>510</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Bradley, A. V.</surname></name>, <name name-style="western"><surname>Thornes, J. E.</surname></name>, <name name-style="western"><surname>Chapman, L.</surname></name>, <name name-style="western"><surname>Unwin, D.</surname></name> and <name name-style="western"><surname>Roy, M.</surname></name><year>2002</year>: <article-title>Modelling spatial and temporal road thermal climatology in rural and urban areas using a GIS</article-title>. <source>Climate Research</source><volume>21</volume>, <fpage>41</fpage>-<lpage>55</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Broesamle, H.</surname></name>, <name name-style="western"><surname>Mannstein, H.</surname></name>, <name name-style="western"><surname>Schillings, C.</surname></name> and <name name-style="western"><surname>Trieb, F.</surname></name><year>2000</year>: <article-title>Assessment of solar electricity potentials in North Africa based on satellite data and a geographic information system</article-title>. <source>Solar Energy</source><volume>70</volume>, <fpage>1</fpage>-<lpage>12</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Bruland, O.</surname></name>, <name name-style="western"><surname>Sand, K.</surname></name> and <name name-style="western"><surname>Killingtveit, A.</surname></name><year>2001</year>: <article-title>Snow distribution at a high Arctic site at Svalbard</article-title>. <source>Nordic Hydrology</source><volume>32</volume>, <fpage>1</fpage>-<lpage>12</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Carbone, G. J.</surname></name>, <name name-style="western"><surname>Narumalani, S.</surname></name> and <name name-style="western"><surname>King, M.</surname></name><year>1996</year>: <article-title>Application of remote sensing and GIS technologies with physiological crop models</article-title>. <source>Photogrammetric Engineering and Remote Sensing</source><volume>62</volume>, <fpage>171</fpage>-<lpage>179</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Carpenter, T. M.</surname></name>, <name name-style="western"><surname>Sperfslage, J. A.</surname></name>, <name name-style="western"><surname>Georgakakos, K. P.</surname></name>, <name name-style="western"><surname>Sweeney, T.</surname></name> and <name name-style="western"><surname>Fread, D. L.</surname></name><year>1999</year>: <article-title>National threshold runoff estimation utilising GIS in support of operational flash flood warning systems</article-title>. <source>Journal of Hydrology</source><volume>224</volume>, <fpage>21</fpage>-<lpage>44</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Cazorzi, F.</surname></name> and <name name-style="western"><surname>DallaFontana, G.</surname></name><year>1996</year>: <article-title>Snowmelt modelling by combining air temperature and a distributed radiation index</article-title>. <source>Journal of Hydrology</source><volume>181</volume>, <fpage>169</fpage>-<lpage>187</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Chang, N. B.</surname></name>, <name name-style="western"><surname>Kao, C. Y. J.</surname></name>, <name name-style="western"><surname>Wei, Y. L.</surname></name> and <name name-style="western"><surname>Tseng, C. C.</surname></name><year>1999</year>: <article-title>Comparative study of 3D numerical and puff models for dense air pollutants</article-title>. <source>Journal of Environmental Engineering</source><volume>125</volume>, <fpage>175</fpage>-<lpage>184</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Chapman, L.</surname></name>, <name name-style="western"><surname>Thornes, J. E.</surname></name> and <name name-style="western"><surname>Bradley, A. V.</surname></name><year>2001</year>: <article-title>Modelling of road surface temperature from a geographical parameter database. Part 2: numerical</article-title>. <source>Meteorological Applications</source><volume>8</volume>, <fpage>421</fpage>-<lpage>436</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Chen, X. W.</surname></name><year>2001</year>: <article-title>Change of tree diversity on Northeast China transect (NECT)</article-title>. <source>Biodiversity and Conservation</source><volume>10</volume>, <fpage>1087</fpage>-<lpage>1096</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Cheng, E.</surname></name> and <name name-style="western"><surname>Shang, J.</surname></name><year>1998</year>: <article-title>Kinematic flow model based extreme wind simulation</article-title>. <source>Journal of Wind Engineering and Industrial Aerodynamics</source><volume>77-78</volume>, <fpage>1</fpage>-<lpage>11</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Cline, D.</surname></name>, <name name-style="western"><surname>Elder, K.</surname></name> and <name name-style="western"><surname>Bales, R.</surname></name><year>1998</year>: <article-title>Scale effects in a distributed snow water equivalence and snowmelt model for mountain basins</article-title>. <source>Hydrological Processes</source><volume>12</volume>, <fpage>1527</fpage>-<lpage>1536</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Collison, A.</surname></name>, <name name-style="western"><surname>Wade, S.</surname></name>, <name name-style="western"><surname>Griffiths, J.</surname></name> and <name name-style="western"><surname>Dehn, M.</surname></name><year>2000</year>: <article-title>Modelling the impact of predicted climate change on landslide frequency and magnitude in SE England</article-title>. <source>Engineering Geology</source><volume>55</volume>, <fpage>205</fpage>-<lpage>218</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Cornford, D.</surname></name> and <name name-style="western"><surname>Thornes, J. E.</surname></name><year>1996</year>: <article-title>A comparison between spatial winter indices and expenditure on winter road maintenance in Scotland</article-title>. <source>International Journal of Climatology</source><volume>16</volume>, <fpage>339</fpage>-<lpage>357</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Daly, C.</surname></name>, <name name-style="western"><surname>Neilson, R. P.</surname></name> and <name name-style="western"><surname>Phillips, D. L.</surname></name><year>1994</year>: <article-title>A statistical-topographic model for mapping climatological precipitation over mountainous terrain</article-title>. <source>Journal of Applied Meteorology</source><volume>33</volume>, <fpage>140</fpage>-<lpage>158</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Daly, C.</surname></name>, <name name-style="western"><surname>Taylor, G. H.</surname></name>, <name name-style="western"><surname>Gibson, W. P.</surname></name>, <name name-style="western"><surname>Parzybok, T. W.</surname></name>, <name name-style="western"><surname>Johnson, G. L.</surname></name> and <name name-style="western"><surname>Pasteris, P. A.</surname></name><year>2000</year>: <article-title>High-quality spatial climate data sets for the United States and beyond</article-title>. <source>Transactions of the American Society of Agricultural Engineers (ASEA)</source><volume>43</volume>, <fpage>1957</fpage>-<lpage>1962</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Davies, A.</surname></name>, <name name-style="western"><surname>Jenkins, T.</surname></name>, <name name-style="western"><surname>Pike, A.</surname></name>, <name name-style="western"><surname>Shao, J.</surname></name>, <name name-style="western"><surname>Carson, I.</surname></name>, <name name-style="western"><surname>Pollock, C. J.</surname></name> and <name name-style="western"><surname>Parry, M. L.</surname></name><year>1998</year>: <article-title>Modelling the predicted geographic and economic response of UK cropping systems to climate change scenarios: the case of sugar beet</article-title>. <source>Annals of Applied Biology</source><volume>133</volume>, <fpage>135</fpage>-<lpage>148</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>de Azevedo, E. B.</surname></name>, <name name-style="western"><surname>Pereira, L. S.</surname></name> and <name name-style="western"><surname>Itier, B.</surname></name><year>1999</year>: <article-title>Modelling the local climate in island environments: water balance applications</article-title>. <source>Agricultural Water Management</source><volume>40</volume>, <fpage>393</fpage>-<lpage>403</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>del Barrio, G.</surname></name>, <name name-style="western"><surname>Alvera, B.</surname></name>, <name name-style="western"><surname>Puigdefabregas, J.</surname></name> and <name name-style="western"><surname>Diez, C.</surname></name><year>1997</year>: <article-title>Response of high mountain landscape to topographic variables: Central Pyrenees</article-title>. <source>Landscape Ecology</source><volume>12</volume>, <fpage>95</fpage>-<lpage>115</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Din, A. M.</surname></name><year>1992</year>: <article-title>Global environmental change data and modelling</article-title>. <source>International Federation for Information Processing (IFIP) Transactions A - Computer Science and Technology</source><volume>13</volume>, <fpage>625</fpage>-<lpage>634</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Dubayah, R. C.</surname></name><year>1994</year>: <article-title>Modelling a solar radiation topoclimatology for the Rio-Grande river basin</article-title>. <source>Journal of Vegetation Science</source><volume>5</volume>, <fpage>627</fpage>-<lpage>640</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Eatherall, A.</surname></name><year>1997</year>: <article-title>Modelling climate change impacts on ecosystems using linked models and a GIS</article-title>. <source>Climatic Change</source><volume>35</volume>, <fpage>17</fpage>-<lpage>34</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>El Garouani, A.</surname></name>, <name name-style="western"><surname>Boussema, M. R.</surname></name> and <name name-style="western"><surname>Ennabli, H.</surname></name><year>2000</year>: <article-title>Use of the Geographic Information System and remote sensing data for the estimation of real evapotranspiration at a regional scale</article-title>. <source>International Journal of Remote Sensing</source><volume>21</volume>, <fpage>2811</fpage>-<lpage>2830</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Ellis, E. A.</surname></name>, <name name-style="western"><surname>Nair, P. K. R.</surname></name>, <name name-style="western"><surname>Linehan, P. E.</surname></name>, <name name-style="western"><surname>Beck, H. W.</surname></name> and <name name-style="western"><surname>Blanche, C. A.</surname></name><year>2000</year>: <article-title>A GIS-based database management application for agroforestry planning and tree selection</article-title>. <source>Computers and Electronics in Agriculture</source><volume>27</volume>, <fpage>41</fpage>-<lpage>55</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Fedra, K.</surname></name> and <name name-style="western"><surname>Haurie, A.</surname></name><year>1999</year>: <article-title>A decision support system for air quality management combining GIS and optimisation techniques</article-title>. <source>International Journal of Environment and Pollution</source><volume>12</volume>, <fpage>125</fpage>-<lpage>146</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Fily, M.</surname></name>, <name name-style="western"><surname>Dedieu, J. P.</surname></name> and <name name-style="western"><surname>Durand, Y.</surname></name><year>1999</year>: <article-title>Comparison between the results of a snow metamorphism model and remote sensing derived snow parameters in the Alps</article-title>. <source>Remote Sensing of Environment</source><volume>68</volume>, <fpage>254</fpage>-<lpage>263</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Fleming, M. D.</surname></name>, <name name-style="western"><surname>Chapin, F. S.</surname></name>, <name name-style="western"><surname>Cramer, W.</surname></name>, <name name-style="western"><surname>Hufford, G. L.</surname></name> and <name name-style="western"><surname>Serreze, M. C.</surname></name><year>2000</year>: <article-title>Geographic patterns and dynamics of Alaskan climate interpolated from a sparse station record</article-title>. <source>Global Change Biology</source><volume>6</volume>, <fpage>49</fpage>-<lpage>58</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Foster, D. R.</surname></name> and <name name-style="western"><surname>Boose, E. R.</surname></name><year>1992</year>: <article-title>Patterns of forest damage resulting from catastrophic winds in central New-England</article-title>. <source>Journal of Ecology</source><volume>80</volume>, <fpage>79</fpage>-<lpage>98</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Franklin, J.</surname></name><year>1998</year>: <article-title>Predicting the distribution of shrub species in southern California from climate and terrain-derived variables</article-title>. <source>Journal of Vegetation Science</source><volume>9</volume>, <fpage>733</fpage>-<lpage>748</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Gabella, M.</surname></name> and <name name-style="western"><surname>Perona, G.</surname></name><year>1998</year>: <article-title>Simulation of the orographic influence on weather radar using a geometric-optics approach</article-title>. <source>Journal of Atmospheric and Oceanic Technology</source><volume>15</volume>, <fpage>1485</fpage>-<lpage>1494</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Ghosh, T. K.</surname></name><year>1997</year>: <article-title>Investigation of drought through digital analysis of satellite data and geographical information systems</article-title>. <source>Theoretical and Applied Climatology</source><volume>58</volume>, <fpage>105</fpage>-<lpage>112</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Goodale, C. L.</surname></name>, <name name-style="western"><surname>Aber, J. D.</surname></name> and <name name-style="western"><surname>Ollinger, S. V.</surname></name><year>1998</year>: <article-title>Mapping monthly precipitation, temperature, and solar radiation for Ireland with polynomial regression and a digital elevation model</article-title>. <source>Climate Research</source><volume>10</volume>, <fpage>35</fpage>-<lpage>49</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Gorokhovich, Y.</surname></name>, <name name-style="western"><surname>Khanbilvardi, R.</surname></name>, <name name-style="western"><surname>Janus, L.</surname></name>, <name name-style="western"><surname>Goldsmith, V.</surname></name> and <name name-style="western"><surname>Stern, D.</surname></name><year>2000</year>: <article-title>Spatially distributed modelling of stream flow during storm events</article-title>. <source>Journal of the American Water Resources Association</source><volume>36</volume>, <fpage>523</fpage>-<lpage>539</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Guisan, A.</surname></name> and <name name-style="western"><surname>Theurillat, J. P.</surname></name><year>2000</year>: <article-title>Equilibrium modelling of alpine plant distribution: how far can we go?</article-title><source>Hytocoenologia</source><volume>30</volume>, <fpage>353</fpage>-<lpage>384</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Gustavsson, T.</surname></name>, <name name-style="western"><surname>Bogren, J.</surname></name> and <name name-style="western"><surname>Eriksson, M.</surname></name><year>1998</year>: <article-title>GIS as a tool for planning new road stretches in respect of climatological factors</article-title>. <source>Theoretical and Applied Climatology</source><volume>60</volume>, <fpage>179</fpage>-<lpage>190</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Hao, J. M.</surname></name>, <name name-style="western"><surname>Wu, Y.</surname></name>, <name name-style="western"><surname>Fu, L. X.</surname></name>, <name name-style="western"><surname>He, D. Q.</surname></name> and <name name-style="western"><surname>He, K. B.</surname></name><year>2001</year>: <article-title>Source contributions to ambient concentrations of CO and NOX in the urban area of Beijing</article-title>. <source>Journal of Environmental Science and Health Part A. Toxic/Hazardous Substances and Environmental Engineering</source><volume>36</volume>, <fpage>215</fpage>-<lpage>228</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Hargy, V. T.</surname></name><year>1997</year>: <article-title>Objectively mapping accumulated temperature for Ireland</article-title>. <source>International Journal of Climatology</source><volume>17</volume>, <fpage>909</fpage>-<lpage>927</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Hijmans, R. J.</surname></name>, <name name-style="western"><surname>Forbes, G. A.</surname></name> and <name name-style="western"><surname>Walker, T. S.</surname></name><year>2000</year>: <article-title>Estimating the global severity of potato late blight with GIS-linked disease forecast models</article-title>. <source>Plant Pathology</source><volume>49</volume>, <fpage>697</fpage>-<lpage>705</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Hill, M. J.</surname></name>, <name name-style="western"><surname>Donald, G. E.</surname></name>, <name name-style="western"><surname>Vickery, P. J.</surname></name> and <name name-style="western"><surname>Furnival, E. P.</surname></name><year>1996</year>: <article-title>Integration of satellite remote sensing, simple bioclimatic models and GIS for assessment of pastoral development for a commercial grazing enterprise</article-title>. <source>Australian Journal of Experimental Agriculture</source><volume>36</volume>, <fpage>309</fpage>-<lpage>321</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Hillring, B.</surname></name> and <name name-style="western"><surname>Krieg, R.</surname></name><year>1998</year>: <article-title>Wind energy potential in southern Sweden - Example of planning methodology</article-title>. <source>Renewable Energy</source><volume>13</volume>, <fpage>471</fpage>-<lpage>479</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Hortal, J.</surname></name>, <name name-style="western"><surname>Lobo, J. M.</surname></name> and <name name-style="western"><surname>Martin-Piera, F.</surname></name><year>2001</year>: <article-title>Forecasting insect species richness scores in poorly surveyed territories: the case of the Portuguese dung beetles (Col. Scarabaeinae)</article-title>. <source>Biodiversity and Conservation</source><volume>10</volume>, <fpage>1343</fpage>-<lpage>1367</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Hudson, G.</surname></name> and <name name-style="western"><surname>Wackernagel, H.</surname></name><year>1994</year>: <article-title>Mapping temperature using kriging with external drift - theory and an example from Scotland</article-title>. <source>International Journal of Climatology</source><volume>14</volume>, <fpage>77</fpage>-<lpage>91</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Jarvis, C. H.</surname></name> and <name name-style="western"><surname>Stuart, N.</surname></name><year>2001</year>: <article-title>A comparison among strategies for interpolating maximum and minimum daily air temperatures. Part II: The interaction between number of guiding variables and the type of interpolation method</article-title>. <source>Journal of Applied Meteorology</source><volume>40</volume>, <fpage>1075</fpage>-<lpage>1084</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Jeffrey, S. J.</surname></name>, <name name-style="western"><surname>Carter, J. O.</surname></name>, <name name-style="western"><surname>Moodie, K. B.</surname></name> and <name name-style="western"><surname>Beswick, A. R.</surname></name><year>2001</year>: <article-title>Using spatial interpolation to construct a comprehensive archive of Australian climate data</article-title>. <source>Environmental Modelling and Software</source><volume>16</volume>, <fpage>309</fpage>-<lpage>330</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Jones, P. G.</surname></name>, <name name-style="western"><surname>Beebe, S. E.</surname></name>, <name name-style="western"><surname>Tohme, J.</surname></name> and <name name-style="western"><surname>Galwey, N. W.</surname></name><year>1997</year>: <article-title>The use of geographical information systems in biodiversity exploration and conservation</article-title>. <source>Biodiversity and Conservation</source><volume>6</volume>, <fpage>947</fpage>-<lpage>958</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Jorgenson, M. T.</surname></name>, <name name-style="western"><surname>Racine, C. H.</surname></name>, <name name-style="western"><surname>Walters, J. C.</surname></name> and <name name-style="western"><surname>Osterkamp, T. E.</surname></name><year>2001</year>: <article-title>Permafrost degradation and ecological changes associated with a warming climate in central Alaska</article-title>. <source>Climatic Change</source><volume>48</volume>, <fpage>551</fpage>-<lpage>579</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Jurisic, M.</surname></name>, <name name-style="western"><surname>Hengl, T.</surname></name>, <name name-style="western"><surname>Duvnjak, V.</surname></name> and <name name-style="western"><surname>Martinic, I.</surname></name><year>1999</year>: <article-title>Agro-ecological and land information system</article-title>. <source>Storjarstvo</source><volume>41</volume>, <fpage>223</fpage>-<lpage>231</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Kadmon, R.</surname></name> and <name name-style="western"><surname>Danin, A.</surname></name><year>1999</year>: <article-title>Distribution of plant species in Israel in relation to spatial variation in rainfall</article-title>. <source>Journal of Vegetation Science</source><volume>10</volume>, <fpage>421</fpage>-<lpage>432</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Kadmon, R.</surname></name> and <name name-style="western"><surname>Heller, J.</surname></name><year>1998</year>: <article-title>Modelling faunal responses to climatic gradients with GIS: land snails as a case study</article-title>. <source>Journal of Biogeography</source><volume>25</volume>, <fpage>527</fpage>-<lpage>539</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Knox, J. W.</surname></name>, <name name-style="western"><surname>Matthews, R. B.</surname></name> and <name name-style="western"><surname>Wassmann, R.</surname></name><year>2000</year>: <article-title>Using a crop/soil simulation model and GIS techniques to assess methane emissions from rice fields in Asia. III. Databases</article-title>. <source>Nutrient Cycling in Agroecosystems</source><volume>58</volume>, <fpage>179</fpage>-<lpage>199</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Kozoderov, V. V.</surname></name><year>1995</year>: <article-title>A scientific approach to employ monitoring and modelling techniques for global change and terrestrial ecosystems and other related projects</article-title>. <source>Journal of Biogeography</source><volume>22</volume>, <fpage>927</fpage>-<lpage>933</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Kravchenko, A. N.</surname></name>, <name name-style="western"><surname>Bullock, D. G.</surname></name> and <name name-style="western"><surname>Boast, C. W.</surname></name><year>2000</year>: <article-title>Joint multifractal analysis of crop yield and terrain slope</article-title>. <source>Agronomy Journal</source><volume>92</volume>, <fpage>1279</fpage>-<lpage>1290</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Kumar, K. V.</surname></name>, <name name-style="western"><surname>Bhattacharya, A.</surname></name> and <name name-style="western"><surname>Subramanyam, C.</surname></name><year>1998</year>: <article-title>Coastal morphological influence for tropical cyclone track deviation along Andhra coast: GIS and remote sensing-based approach</article-title>. <source>Current Science</source><volume>75</volume>, <fpage>955</fpage>-<lpage>958</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Lapen, D. R.</surname></name> and <name name-style="western"><surname>Martz, L. W.</surname></name><year>1996</year>: <article-title>An investigation of the spatial association between snow depth and topography in a Prairie agricultural landscape using digital terrain analysis</article-title>. <source>Journal of Hydrology</source><volume>184</volume>, <fpage>277</fpage>-<lpage>298</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Lekes, V.</surname></name> and <name name-style="western"><surname>Dandul, I.</surname></name><year>2000</year>: <article-title>Using airflow modelling and spatial analysis for defining wind damage risk classification (WINDARC)</article-title>. <source>Forest Ecology and Management</source><volume>135</volume>, <fpage>331</fpage>-<lpage>344</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Lennon, J. J.</surname></name> and <name name-style="western"><surname>Turner, J. R. G.</surname></name><year>1995</year>: <article-title>Predicting the spatial distribution of climate temperature in Great Britain</article-title>. <source>Journal of Animal Ecology</source><volume>64</volume>, <fpage>370</fpage>-<lpage>392</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Levizzani, V.</surname></name>, <name name-style="western"><surname>Schmetz, J.</surname></name>, <name name-style="western"><surname>Lutz, H. J.</surname></name>, <name name-style="western"><surname>Kerkmann, J.</surname></name>, <name name-style="western"><surname>Alberoni, P. P.</surname></name> and <name name-style="western"><surname>Cervino, M.</surname></name><year>2001</year>: <article-title>Precipitation estimations from geostationary orbits and prospects for METEOSAT Second Generation</article-title>. <source>Meteorological Applications</source><volume>8</volume>, <fpage>23</fpage>-<lpage>41</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Li, L. Y. O.</surname></name> and <name name-style="western"><surname>Eglese, R. W.</surname></name><year>1996</year>: <article-title>An interactive algorithm for vehicle routing for winter gritting</article-title>. <source>Journal of the Operational Research Society</source><volume>47</volume>, <fpage>217</fpage>-<lpage>228</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Lindsay, S. W.</surname></name> and <name name-style="western"><surname>Thomas, C. J.</surname></name><year>2000</year>: <article-title>Mapping and estimating the population at risk from lymphatic filariasis in Africa</article-title>. <source>Transactions of the Royal Society of Tropical Medicines and Hygiene</source><volume>94</volume>, <fpage>37</fpage>-<lpage>45</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Lo, C. P.</surname></name>, <name name-style="western"><surname>Quattrochi, D. A.</surname></name> and <name name-style="western"><surname>Luvall, J. C.</surname></name><year>1997</year>: <article-title>Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect</article-title>. <source>International Journal of Remote Sensing</source><volume>18</volume>, <fpage>287</fpage>-<lpage>304</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Lourens, U. W.</surname></name> and <name name-style="western"><surname>deJager, J. M.</surname></name><year>1997</year>: <article-title>A computerised crop-specific drought monitoring system: design concepts and initial testing</article-title>. <source>Agricultural Systems</source><volume>53</volume>, <fpage>303</fpage>-<lpage>315</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Malone, J. B.</surname></name>, <name name-style="western"><surname>Bergquist, N. R.</surname></name>, <name name-style="western"><surname>Huh, O. K.</surname></name>, <name name-style="western"><surname>Bavia, M. E.</surname></name>, <name name-style="western"><surname>Bernardi, M.</surname></name>, <name name-style="western"><surname>El Bahy, M. M.</surname></name>, <name name-style="western"><surname>Fuentes, M. V.</surname></name>, <name name-style="western"><surname>Kristensen, T. K.</surname></name>, <name name-style="western"><surname>McCarroll, J. C.</surname></name>, <name name-style="western"><surname>Yilma, J. M.</surname></name> and <name name-style="western"><surname>Zhou, X. N.</surname></name><year>2001</year>: <article-title>A global network for the control of snail-borne disease using satellite surveillance and geographic information systems</article-title>. <source>Acta Tropica</source><volume>79</volume>, <fpage>7</fpage>-<lpage>12</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Manguin, S.</surname></name> and <name name-style="western"><surname>Boussinesq, M.</surname></name><year>1999</year>: <article-title>Remote sensing in public health: applications to malaria and other diseases</article-title>. <source>Medicene et Maladies Infectieuses</source><volume>29</volume>, <fpage>318</fpage>-<lpage>324</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Matthews, R. B.</surname></name>, <name name-style="western"><surname>Wassmann, R.</surname></name>, <name name-style="western"><surname>Knox, J. W.</surname></name> and <name name-style="western"><surname>Buendia, L. V.</surname></name><year>2000</year>: <article-title>Using a crop/soil simulation model and GIS techniques to assess methane emissions from rice fields in Asia. IV. Upscaling to national levels</article-title>. <source>Nutrient Cycling in Ecosystems</source><volume>58</volume>, <fpage>201</fpage>-<lpage>217</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>McHugh, C. A.</surname></name>, <name name-style="western"><surname>Carruthers, D. J.</surname></name> and <name name-style="western"><surname>Edmunds, H. A.</surname></name><year>1997</year>: <article-title>ADMS and ADMS-Urban</article-title>. <source>International Journal of Environment and Pollution</source><volume>8</volume>, <fpage>438</fpage>-<lpage>440</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>McKenney, D. W.</surname></name>, <name name-style="western"><surname>Hutchinson, M. F.</surname></name>, <name name-style="western"><surname>Kesteven, J. L.</surname></name> and <name name-style="western"><surname>Venier, L. A.</surname></name><year>2001</year>: <article-title>Canada’s plant hardiness zones revisited using modern climate interpolation techniques</article-title>. <source>Canadian Journal of Plant Science</source><volume>81</volume>, <fpage>129</fpage>-<lpage>143</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Menkir, A.</surname></name>, <name name-style="western"><surname>Kling, J. G.</surname></name>, <name name-style="western"><surname>Jagtap, S. S.</surname></name> and <name name-style="western"><surname>Aliu, B. A.</surname></name><year>2000</year>: <article-title>GIS based classification of maize testing locations in West and Central Africa</article-title>. <source>Maydica</source><volume>45</volume>, <fpage>143</fpage>-<lpage>150</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Mensink, C.</surname></name>, <name name-style="western"><surname>De Vlieger, I.</surname></name> and <name name-style="western"><surname>Nys, J.</surname></name><year>2000</year>: <article-title>An urban transport emission model for the Antwerp area</article-title>. <source>Atmospheric Environment</source><volume>27</volume>, <fpage>4595</fpage>-<lpage>4602</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Morselli, M. G.</surname></name>, <name name-style="western"><surname>Calori, G.</surname></name>, <name name-style="western"><surname>Finardi, S.</surname></name> and <name name-style="western"><surname>Mazzola, C.</surname></name><year>1997</year>: <article-title>A 3-D wind and temperature pre-processor for ATD models</article-title>. <source>International Journal of Environment and Pollution</source><volume>8</volume>, <fpage>489</fpage>-<lpage>499</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Moore, I. D.</surname></name>, <name name-style="western"><surname>Norton, T. W.</surname></name> and <name name-style="western"><surname>Williams, J. E.</surname></name><year>1993</year>: <article-title>Modelling environmental heterogeneity in forested landscapes</article-title>. <source>Journal of Hydrology</source><volume>150</volume>, <fpage>717</fpage>-<lpage>747</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Moore, J. E.</surname></name>, <name name-style="western"><surname>Sandquist, G. M.</surname></name> and <name name-style="western"><surname>Slaughter, D. M.</surname></name><year>1995</year>: <article-title>A route-specific system for risk assessment of radioactive materials transportation accidents</article-title>. <source>Nuclear Technology</source><volume>112</volume>, <fpage>63</fpage>-<lpage>78</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Nichol, J. E.</surname></name><year>1994</year>: <article-title>An examination of tropical rainforest microclimate using GIS modelling</article-title>. <source>Global Ecology and Biogeography Letters</source><volume>4</volume>, <fpage>69</fpage>-<lpage>78</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Nichol, J. E.</surname></name><year>1995</year>: <article-title>Monitoring tropical rainforest micro-climate</article-title>. <source>Photogrammetric Engineering and Remote Sensing</source><volume>61</volume>, <fpage>1159</fpage>-<lpage>1165</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Nichol, J. E.</surname></name><year>1998</year>: <article-title>Visualisation of urban surface temperatures derived from satellite images</article-title>. <source>International Journal of Remote Sensing</source><volume>19</volume>, <fpage>1639</fpage>-<lpage>1649</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Ninyerola, M.</surname></name>, <name name-style="western"><surname>Pons, X.</surname></name> and <name name-style="western"><surname>Roure, J. M.</surname></name><year>2000</year>: <article-title>A methodological approach of climatological modelling of air temperature and precipitation through GIS techniques</article-title>. <source>International Journal of Climatology</source><volume>20</volume>, <fpage>1823</fpage>-<lpage>1841</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Panigrahy, S.</surname></name> and <name name-style="western"><surname>Chakraborty, M.</surname></name><year>1998</year>: <article-title>An integrated approach for potato crop intensification using temporal remote sensing data</article-title>. <source>Journal of Photogrammetric Engineering and Remote Sensing</source><volume>53</volume>, <fpage>54</fpage>-<lpage>60</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Patel, M. H.</surname></name> and <name name-style="western"><surname>Horowitz, A. J.</surname></name><year>1994</year>: <article-title>Optimal routing of hazardous materials considering risk of spill</article-title>. <source>Transportation Research Part A. Policy and Practice</source><volume>28</volume>, <fpage>119</fpage>-<lpage>132</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Patz, J. A.</surname></name> and <name name-style="western"><surname>Balbus, J. M.</surname></name><year>1996</year>: <article-title>Methods for assessing public health vulnerability to global climate change</article-title>. <source>Climate Research</source><volume>6</volume>, <fpage>113</fpage>-<lpage>125</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Pew, K. L.</surname></name> and <name name-style="western"><surname>Larsen, C. P. S.</surname></name><year>2001</year>: <article-title>GIS analysis of spatial and temporal patterns of human-caused wildfires in the temperate rain forest of Vancouver Island, Canada</article-title>. <source>Forest Ecology and Management</source><volume>140</volume>, <fpage>1</fpage>-<lpage>18</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Pfister, A.</surname></name> and <name name-style="western"><surname>Fischer, H.</surname></name><year>1995</year>: <article-title>Influence of the topography of the surface of the earth on vertical sounding of the temperature profile</article-title>. <source>Annales Geophysicae - Atmospheres Hydrospheres and Space Sciences</source><volume>13</volume>, <fpage>318</fpage>-<lpage>329</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Phillips, V. D.</surname></name>, <name name-style="western"><surname>Singh, D.</surname></name>, <name name-style="western"><surname>Khan, M. A.</surname></name> and <name name-style="western"><surname>Takahashi, P. K.</surname></name><year>1992</year>: <article-title>Preliminary assessment of biomass energy resources in Hawaii</article-title>. <source>Energy Sources</source><volume>14</volume>, <fpage>381</fpage>-<lpage>389</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Pleshikov, F. I.</surname></name>, <name name-style="western"><surname>Ryzkova, V. A.</surname></name>, <name name-style="western"><surname>Kaplunov, V. Y.</surname></name> and <name name-style="western"><surname>Usoltseva, J. V.</surname></name><year>1998</year>: <article-title>A computer system for evaluating and predicting hurricane impact on forest</article-title>. <source>Safety Science</source><volume>30</volume>, <fpage>3</fpage>-<lpage>8</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Prabha, T. V.</surname></name> and <name name-style="western"><surname>Mursch-Radlgruber, E</surname></name><year>1999</year>: <article-title>Investigation of air pollution distribution in Linz: case studies to evaluate a K-type diffusion model coupled with a mass-consistent wind model</article-title>. <source>Atmospheric Environment</source><volume>33</volume>, <fpage>4067</fpage>-<lpage>4080</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Priya, S.</surname></name> and <name name-style="western"><surname>Shibasaki, R.</surname></name><year>2001</year>: <article-title>National spatial crop yield simulation using GIS-based crop production model</article-title>. <source>Ecological Modelling</source><volume>136</volume>, <fpage>113</fpage>-<lpage>129</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Prudhomme, C.</surname></name><year>1999</year>: <article-title>Mapping a statistic of extreme rainfall in a mountainous region</article-title>. <source>Physics and Chemistry of the Earth Part B. Hydrology Oceans and Atmosphere</source><volume>24</volume>, <fpage>79</fpage>-<lpage>84</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Reinke, K.</surname></name>, <name name-style="western"><surname>Butcher, E. C.</surname></name>, <name name-style="western"><surname>Russell, C. J.</surname></name>, <name name-style="western"><surname>Nicholls, D. G.</surname></name> and <name name-style="western"><surname>Murray, M. D.</surname></name><year>1998</year>: <article-title>Understanding the flight movements of a non-breeding wandering albatross, Diomedea exulans gibsoni, using a geographic information system</article-title>. <source>Australian Journal of Zoology</source><volume>46</volume>, <fpage>171</fpage>-<lpage>181</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Rigol, J. P.</surname></name>, <name name-style="western"><surname>Jarvis, C. H.</surname></name> and <name name-style="western"><surname>Stuart, N.</surname></name><year>2001</year>: <article-title>Artificial neural networks as a tool for spatial interpolation</article-title>. <source>International Journal of Geographical Information Science</source><volume>15</volume>, <fpage>323</fpage>-<lpage>343</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Romero, H.</surname></name>, <name name-style="western"><surname>Ihl, M.</surname></name>, <name name-style="western"><surname>Rivera, A.</surname></name>, <name name-style="western"><surname>Zalazar, P.</surname></name> and <name name-style="western"><surname>Azocar, P.</surname></name><year>1999</year>: <article-title>Rapid urban growth, land-use changes and air pollution in Santiago, Chile</article-title>. <source>Atmospheric Environment</source><volume>33</volume>, <fpage>4039</fpage>-<lpage>4047</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Schadlich, S.</surname></name>, <name name-style="western"><surname>Gottsche, F. M.</surname></name> and <name name-style="western"><surname>Olesen, F. S.</surname></name><year>2001</year>: <article-title>Influence of land surface parameters and atmosphere on METEOSAT brightness temperatures and generation of land surface temperature maps by temporally and spatially interpolating atmospheric correction</article-title>. <source>Remote Sensing of Environment</source><volume>75</volume>, <fpage>39</fpage>-<lpage>46</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Scherer, D.</surname></name>, <name name-style="western"><surname>Fehrenbach, U.</surname></name>, <name name-style="western"><surname>Beha, H. D.</surname></name> and <name name-style="western"><surname>Parlow, E.</surname></name><year>1999</year>: <article-title>Improved concepts and methods in analysis and evaluation of the urban climate for optimising urban planning processes</article-title>. <source>Atmospheric Environment</source><volume>33</volume>, <fpage>4185</fpage>-<lpage>4193</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Schmidt, M.</surname></name> and <name name-style="western"><surname>Schafer, R. P.</surname></name><year>1998</year>: <article-title>An integrated simulation system for traffic induced air pollution</article-title>. <source>Environmental Modelling and Software</source><volume>13</volume>, <fpage>295</fpage>-<lpage>303</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Schneider, L. C.</surname></name>, <name name-style="western"><surname>Kinzig, A. P.</surname></name>, <name name-style="western"><surname>Larson, E. D.</surname></name> and <name name-style="western"><surname>Solorzano, L. A.</surname></name><year>2001</year>: <article-title>Method for spatially explicit calculations of potential biomass yields and assessment of laud availability for biomass energy production in northeastern Brazil</article-title>. <source>Agriculture Ecosystems and Environment</source><volume>84</volume>, <fpage>207</fpage>-<lpage>226</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Shevenell, L.</surname></name><year>1999</year>: <article-title>Regional potential evapotranspiration in arid climates based on temperature, topography and calculated solar radiation</article-title>. <source>Hydrological Processes</source><volume>13</volume>, <fpage>577</fpage>-<lpage>596</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Soderstrom, M.</surname></name> and <name name-style="western"><surname>Magnusson, B.</surname></name><year>1995</year>: <article-title>Assessment of local agroclimatic conditions: a methodology</article-title>. <source>Agricultural and Forest Meteorology</source><volume>72</volume>, <fpage>243</fpage>-<lpage>260</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Sorensen, B.</surname></name><year>2001</year>: <article-title>GIS management of solar resource data</article-title>. <source>Solar Energy Materials and Solar Cells</source><volume>67</volume>, <fpage>503</fpage>-<lpage>509</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Sorensen, B.</surname></name> and <name name-style="western"><surname>Meibom, P.</surname></name><year>1999</year>: <article-title>GIS tools for renewable energy modelling</article-title>. <source>Renewable Energy</source><volume>16</volume>, <fpage>1262</fpage>-<lpage>1267</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Sousa, V.</surname></name> and <name name-style="western"><surname>Pereira, L. S.</surname></name><year>1999</year>: <article-title>Regional analysis of irrigation water requirements using kriging - Application to potato crop (Solanum tuberosum L.) at Tras-os-Montes</article-title>. <source>Agricultural Water Management</source><volume>40</volume>, <fpage>221</fpage>-<lpage>233</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Srivastava, A.</surname></name>, <name name-style="western"><surname>Nagpal, B. N.</surname></name>, <name name-style="western"><surname>Saxena, R.</surname></name> and <name name-style="western"><surname>Subbarao, S. K.</surname></name><year>2001</year>: <article-title>Predictive habitat modelling for forest malaria vector species An. dirus in India - a GIS-based approach</article-title>. <source>Current Science</source><volume>80</volume>, <fpage>1129</fpage>-<lpage>1134</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Strzepek, K. M.</surname></name> and <name name-style="western"><surname>Yates, D. N.</surname></name><year>1997</year>: <article-title>Climate change impacts on the hydrologic resources of Europe: a simplified continental scale analysis</article-title>. <source>Climatic Change</source><volume>36</volume>, <fpage>79</fpage>-<lpage>92</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Suga, Y.</surname></name>, <name name-style="western"><surname>Takeuchi, S.</surname></name>, <name name-style="western"><surname>Kimura, H.</surname></name> and <name name-style="western"><surname>Inanga, A.</surname></name><year>1995</year>: <article-title>Environmental monitoring of land and sea surface using multisensors</article-title>. <source>Calibration and Application of Satellite Sensors for Environmental Monitoring</source><volume>17</volume>, <fpage>97</fpage>-<lpage>106</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Sunar, F.</surname></name> and <name name-style="western"><surname>Ozkan, C.</surname></name><year>2001</year>: <article-title>Forest fire analysis with remote sensing data</article-title>. <source>International Journal of Remote Sensing</source><volume>22</volume>, <fpage>2265</fpage>-<lpage>2277</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Tappeiner, U.</surname></name>, <name name-style="western"><surname>Tappeiner, G.</surname></name>, <name name-style="western"><surname>Aschenwald, J.</surname></name>, <name name-style="western"><surname>Tasser, E.</surname></name> and <name name-style="western"><surname>Ostendorf, B.</surname></name><year>2001</year>: <article-title>GIS-based modelling of spatial pattern of snow cover duration in an alpine area</article-title>. <source>Ecological Modelling</source><volume>138</volume>, <fpage>265</fpage>-<lpage>275</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Taschner, S.</surname></name>, <name name-style="western"><surname>Ludwig, R.</surname></name> and <name name-style="western"><surname>Mauser, W.</surname></name><year>2001</year>: <article-title>Multi-scenario flood modelling in a mountain watershed using data from a NWP model, rain radar and rain gauges</article-title>. <source>Physics and Chemistry of the Earth Part B. Hydrology Oceans and Atmosphere</source><volume>26</volume>, <fpage>509</fpage>-<lpage>515</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Taylor, M. A. P.</surname></name>, <name name-style="western"><surname>Woolley, J. E.</surname></name> and <name name-style="western"><surname>Zito, R.</surname></name><year>2000</year>: <article-title>Integration of the global positioning system and geographical information systems for traffic congestion studies</article-title>. <source>Transportation Research Part C - Emerging Technologies</source><volume>8</volume>, <fpage>257</fpage>-<lpage>285</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Thumerer, T.</surname></name>, <name name-style="western"><surname>Jones, A. P.</surname></name> and <name name-style="western"><surname>Brown, D.</surname></name><year>2000</year>: <article-title>A GIS based coastal management system for climate change associated flood risk assessment on the east coast of England</article-title>. <source>International Journal of Geographical Information Science</source><volume>14</volume>, <fpage>265</fpage>-<lpage>281</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Tsanis, I. K.</surname></name> and <name name-style="western"><surname>Gad, M. A.</surname></name><year>2001</year>: <article-title>A GIS precipitation method for analysis of storm kinematics</article-title>. <source>Environmental Modelling and Software</source><volume>16</volume>, <fpage>273</fpage>-<lpage>281</lpage>.</citation></ref><ref><citation citation-type="book" xlink:type="simple"><name name-style="western"><surname>Tveito, O. E.</surname></name>, <name name-style="western"><surname>Førland, E. J.</surname></name>, <name name-style="western"><surname>Alexandersson, H.</surname></name>, <name name-style="western"><surname>Drebs, A.</surname></name>, <name name-style="western"><surname>Jónsson, T.</surname></name>, <name name-style="western"><surname>Tuomenvirta, H.</surname></name> and <name name-style="western"><surname>Vaarby Laursen, E.</surname></name><year>2001</year>: <source>Nordic climate maps</source>. DNMI Report Number 06/01. <uri xlink:type="simple">http://www.smhi.se/hfa_coord/nordklim/report06_2001.pdf</uri> (last accessed 15 April 2003).</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Udouj, T. H.</surname></name> and <name name-style="western"><surname>Scott, H. D.</surname></name><year>1999</year>: <article-title>Simulated phosphorus and sediment loadings in two representative subbasins of the Illinois River</article-title>. <source>Journal of Soil Contamination</source><volume>8</volume>, <fpage>509</fpage>-<lpage>526</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Valdes, M. C.</surname></name>, <name name-style="western"><surname>Stiff, C.</surname></name> and <name name-style="western"><surname>Dechert, T. V.</surname></name><year>1994</year>: <article-title>Site quality evaluation and yield of Pinus occurpa in Honduras Central Zone</article-title>. <source>Interciencia</source><volume>19</volume>, <fpage>336</fpage>-<lpage>346</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Vandenbergh, M.</surname></name>, <name name-style="western"><surname>Neirac, F. P.</surname></name> and <name name-style="western"><surname>Turki, H.</surname></name><year>1999</year>: <article-title>A GIS approach for the siting of solar thermal power plants application to Tunisia</article-title>. <source>Journal de Physique IV</source><volume>9</volume>, <fpage>223</fpage>-<lpage>228</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>van Wesenbeeck, I. J.</surname></name> and <name name-style="western"><surname>Havens, P. L.</surname></name><year>1999</year>: <article-title>A groundwater exposure assessment for cloransulam-methyl in the US soybean market</article-title>. <source>Journal of Environmental Quality</source><volume>28</volume>, <fpage>513</fpage>-<lpage>522</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Vazquez, A.</surname></name> and <name name-style="western"><surname>Moreno, J. M.</surname></name><year>2001</year>: <article-title>Spatial distribution of forest fires in Sierra de Gredos (Central Spain)</article-title>. <source>Forest Ecology and Management</source><volume>147</volume>, <fpage>55</fpage>-<lpage>65</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Verdebout, J.</surname></name><year>2000</year>: <article-title>A method to generate surface UV radiation maps over Europe using GOME, Meteosat, and ancillary geophysical data</article-title>. <source>Journal of Geophysical Research - Atmospheres</source><volume>105</volume>, <fpage>5049</fpage>-<lpage>5058</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Waluda, C. M.</surname></name>, <name name-style="western"><surname>Rodhouse, P. G.</surname></name>, <name name-style="western"><surname>Trathan, P. N.</surname></name> and <name name-style="western"><surname>Pierce, G. J.</surname></name><year>2001</year>: <article-title>Remotely sensed mesoscale oceanography and the distribution of Illex argentinus in the South Atlantic</article-title>. <source>Fisheries Oceanography</source><volume>10</volume>, <fpage>207</fpage>-<lpage>216</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Weiss, S. B.</surname></name> and <name name-style="western"><surname>Weiss, A. D.</surname></name><year>1998</year>: <article-title>Landscape-level phenology of a threatened butterfly: a GIS-based modeling approach</article-title>. <source>Ecosystems</source><volume>1</volume>, <fpage>299</fpage>-<lpage>309</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Weng, Q.</surname></name><year>2001</year>: <article-title>A remote sensing-GIS evaluation of urban expansion and its impact on surface temperature in the Zhujiang Delta, China</article-title>. <source>International Journal of Remote Sensing</source><volume>22</volume>, <fpage>1999</fpage>-<lpage>2014</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Wilk, J.</surname></name> and <name name-style="western"><surname>Andersson, L.</surname></name><year>2001</year>: <article-title>GIS-supported modelling of areal rainfall in a mountainous river basin with monsoon climate in southern India</article-title>. <source>Hydrological Sciences Journal</source><volume>45</volume>, <fpage>185</fpage>-<lpage>202</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Wooldridge, S. A.</surname></name>, <name name-style="western"><surname>Franks, S. W.</surname></name> and <name name-style="western"><surname>Kalma, J. D.</surname></name><year>2001</year>: <article-title>Hydrological implications of the Southern Oscillation: variability of the rainfall-runoff relationship</article-title>. <source>Hydrological Sciences Journal</source><volume>46</volume>, <fpage>73</fpage>-<lpage>88</lpage>.</citation></ref><ref><citation citation-type="book" xlink:type="simple"><name name-style="western"><surname>Worboys, M. F.</surname></name><year>1995</year>: <source>GIS: a computing perspective</source>. <publisher-loc>London</publisher-loc>: <publisher-name>Taylor and Francis</publisher-name>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Wu, J. J.</surname></name> and <name name-style="western"><surname>Babcock, B. A.</surname></name><year>1999</year>: <article-title>Metamodeling potential nitrate water pollution in the central United States</article-title>. <source>Journal of Environmental Quality</source><volume>28</volume>, <fpage>1916</fpage>-<lpage>1928</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Yajima, M.</surname></name><year>1996</year>: <article-title>Monitoring regional rice development and cool-summer damage</article-title>. <source>Japan Agricultural Research Quarterly</source><volume>30</volume>, <fpage>139</fpage>-<lpage>143</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Yarnal, B.</surname></name><name name-style="western"><surname>Lakhtakia, M. N.</surname></name>, <name name-style="western"><surname>Yu, Z.</surname></name>, <name name-style="western"><surname>White, R. A.</surname></name>, <name name-style="western"><surname>Pollard, D.</surname></name>, <name name-style="western"><surname>Miller, D. A.</surname></name> and <name name-style="western"><surname>Lapenta, W. M.</surname></name><year>2000</year>: <article-title>A linked meteorological and hydrological model system: the Susquehanna River Basin Experiment (SRBEX)</article-title>. <source>Global and Planetary Change</source><volume>25</volume>, <fpage>149</fpage>-<lpage>161</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Zakarin, E. A.</surname></name> and <name name-style="western"><surname>Mirkarimova, B. M.</surname></name><year>2000</year>: <article-title>GIS-based mathematical modelling of urban air pollution</article-title>. <source>Journal of Atmospheric and Oceanic Physics</source><volume>36</volume>, <fpage>334</fpage>-<lpage>342</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Zheng, X.</surname></name>, <name name-style="western"><surname>Pierce, G. J.</surname></name> and <name name-style="western"><surname>Reid, D. G.</surname></name><year>2001</year>: <article-title>Spatial patterns of whiting abundance in Scottish waters and relationships with environmental variables</article-title>. <source>Fisheries Research</source><volume>50</volume>, <fpage>259</fpage>-<lpage>270</lpage>.</citation></ref><ref><citation citation-type="journal" xlink:type="simple"><name name-style="western"><surname>Zhu, Q. J.</surname></name>, <name name-style="western"><surname>Rong, T. Z.</surname></name> and <name name-style="western"><surname>Sun, R.</surname></name><year>2000</year>: <article-title>A case study on fractal simulation of forest fire spread</article-title>. <source>Science in China Series E - Technological Sciences</source><volume>43</volume>, <fpage>104-U2</fpage>-<lpage>104-U2</lpage><issue>Suppl</issue>.</citation></ref></ref-list></back></article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>The use of geographical information systems in climatology and meteorology</title></titleInfo><titleInfo type="alternative" lang="en" contentType="CDATA"><title>The use of geographical information systems in climatology and meteorology</title></titleInfo><name type="personal"><namePart type="given">Lee</namePart><namePart type="family">Chapman</namePart><affiliation>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</affiliation><affiliation>E-mail: l.chapman@bham.ac.uk</affiliation></name><name type="personal"><namePart type="given">John E.</namePart><namePart type="family">Thornes</namePart><affiliation>Climate and Atmospheric Research Group, School of Geography, Earth and Environmental Science, University of Birmingham, Birmingham B15 2TT, UK,</affiliation><affiliation>E-mail: l.chapman@bham.ac.uk</affiliation></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="research-article"></genre><originInfo><publisher>Sage Publications</publisher><place><placeTerm type="text">Sage CA: Thousand Oaks, CA</placeTerm></place><dateIssued encoding="w3cdtf">2003-09</dateIssued><copyrightDate encoding="w3cdtf">2003</copyrightDate></originInfo><language><languageTerm type="code" authority="iso639-2b">eng</languageTerm><languageTerm type="code" authority="rfc3066">en</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">The proliferation of ‘commercial off-the-shelf’ geographical information systems into the scientific community has resulted in the widespread use of spatial climate data in a variety of applications. This paper presents a review of the role of geographical information systems in climatology and meteorology by (i) discussing methods used to derive and refine spatial climate data and (ii) reviewing the bespoke application of GIS and spatial climate datasets in agriculture, ecology, forestry, health and disease, weather forecasting, hydrology, transport, urban environments, energy and climate change.</abstract><subject><genre>keywords</genre><topic>bespoke system</topic><topic>climatology</topic><topic>digital terrain model</topic><topic>geographical information system</topic><topic>meteorology</topic><topic>weather forecasting</topic></subject><relatedItem type="host"><titleInfo><title>Progress in Physical Geography</title></titleInfo><genre type="journal">journal</genre><identifier type="ISSN">0309-1333</identifier><identifier type="eISSN">1477-0296</identifier><identifier type="PublisherID">PPG</identifier><identifier type="PublisherID-hwp">spppg</identifier><part><date>2003</date><detail type="volume"><caption>vol.</caption><number>27</number></detail><detail type="issue"><caption>no.</caption><number>3</number></detail><extent unit="pages"><start>313</start><end>330</end></extent></part></relatedItem><identifier type="istex">EEF0CFD3C80B325195625B25FF7451D0516FC525</identifier><identifier type="DOI">10.1191/0309133303pp384ra</identifier><identifier type="ArticleID">10.1191_0309133303pp384ra</identifier><recordInfo><recordContentSource>SAGE</recordContentSource></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Agronomie/explor/SisAgriV1/Data/Istex/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000412 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Istex/Corpus/biblio.hfd -nk 000412 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Agronomie
|area= SisAgriV1
|flux= Istex
|étape= Corpus
|type= RBID
|clé= ISTEX:EEF0CFD3C80B325195625B25FF7451D0516FC525
|texte= The use of geographical information systems in climatology and meteorology
}}
| This area was generated with Dilib version V0.6.28. |  |