The use of remotely-sensed satellite imagery for landscape classification in Wales (U.K.)
Identifieur interne : 001108 ( Istex/Corpus ); précédent : 001107; suivant : 001109The use of remotely-sensed satellite imagery for landscape classification in Wales (U.K.)
Auteurs : Roy H. Haines-YoungSource :
- Landscape Ecology [ 0921-2973 ] ; 1992-12-01.
Abstract
Abstract: Remotely-sensed satellite data from Landsat TM and MSS were processed digitally to make landscape classifications of three study areas of south east Wales. The classifications were constructed by classifying major variations in land cover mosaics within the areas, and using these data to group the 1 km × 1 km cells of the National Grid into landscape classes according to the combination of cover types found within them. The TWINSPAN algorithm, which is a polythetic, divisive classification method, was used as the basis of the study. The results showed that while satellite imagery could only be used to extract information about land cover, the close association betwen landscape, land cover and terrain meant that the major physical divisions in the study area could also be detected in the landscape classification. The landscape types recognised in the study were found to be consistent with those indicated in other independent data which relate to the areas. These data included the ITE Land Classes for Great Britain, and the Agricultural (June) Census statistics for England and Wales. The approach to landscape classification described allows landscape classifications to be made rapidly. These classifications can provide a sampling frameworks for landscape survey in areas where basic map data are lacking or resources for field survey are limited. The landscape classifications can also assist in making landscape evaluations since they allow different landscape types to be compared in respect of such properties such as their typicalness, rarity, naturalness and position on a geographical or ecological gradient.
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DOI: 10.1007/BF00131256
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Haines-Young</name><affiliation><mods:affiliation>Department of Geography, University of Nottingham, NG7 2RD, Nottingham, UK</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Landscape Ecology</title><title level="j" type="abbrev">Landscape Ecol</title><idno type="ISSN">0921-2973</idno><idno type="eISSN">1572-9761</idno><imprint><publisher>Kluwer Academic Publishers</publisher><pubPlace>Dordrecht</pubPlace><date type="published" when="1992-12-01">1992-12-01</date><biblScope unit="volume">7</biblScope><biblScope unit="issue">4</biblScope><biblScope unit="page" from="253">253</biblScope><biblScope unit="page" to="274">274</biblScope></imprint><idno type="ISSN">0921-2973</idno></series><idno type="istex">D48B6B871B0B8CFD7791F309CC1B5AD6EEC6261D</idno><idno type="DOI">10.1007/BF00131256</idno><idno type="ArticleID">BF00131256</idno><idno type="ArticleID">Art3</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0921-2973</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: Remotely-sensed satellite data from Landsat TM and MSS were processed digitally to make landscape classifications of three study areas of south east Wales. The classifications were constructed by classifying major variations in land cover mosaics within the areas, and using these data to group the 1 km × 1 km cells of the National Grid into landscape classes according to the combination of cover types found within them. The TWINSPAN algorithm, which is a polythetic, divisive classification method, was used as the basis of the study. The results showed that while satellite imagery could only be used to extract information about land cover, the close association betwen landscape, land cover and terrain meant that the major physical divisions in the study area could also be detected in the landscape classification. The landscape types recognised in the study were found to be consistent with those indicated in other independent data which relate to the areas. These data included the ITE Land Classes for Great Britain, and the Agricultural (June) Census statistics for England and Wales. The approach to landscape classification described allows landscape classifications to be made rapidly. These classifications can provide a sampling frameworks for landscape survey in areas where basic map data are lacking or resources for field survey are limited. The landscape classifications can also assist in making landscape evaluations since they allow different landscape types to be compared in respect of such properties such as their typicalness, rarity, naturalness and position on a geographical or ecological gradient.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Roy H. 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The results showed that while satellite imagery could only be used to extract information about land cover, the close association betwen landscape, land cover and terrain meant that the major physical divisions in the study area could also be detected in the landscape classification. The landscape types recognised in the study were found to be consistent with those indicated in other independent data which relate to the areas. These data included the ITE Land Classes for Great Britain, and the Agricultural (June) Census statistics for England and Wales. The approach to landscape classification described allows landscape classifications to be made rapidly. These classifications can provide a sampling frameworks for landscape survey in areas where basic map data are lacking or resources for field survey are limited. 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The classifications were constructed by classifying major variations in land cover mosaics within the areas, and using these data to group the 1 km × 1 km cells of the National Grid into landscape classes according to the combination of cover types found within them. The TWINSPAN algorithm, which is a polythetic, divisive classification method, was used as the basis of the study. The results showed that while satellite imagery could only be used to extract information about land cover, the close association betwen landscape, land cover and terrain meant that the major physical divisions in the study area could also be detected in the landscape classification. The landscape types recognised in the study were found to be consistent with those indicated in other independent data which relate to the areas. These data included the ITE Land Classes for Great Britain, and the Agricultural (June) Census statistics for England and Wales. The approach to landscape classification described allows landscape classifications to be made rapidly. These classifications can provide a sampling frameworks for landscape survey in areas where basic map data are lacking or resources for field survey are limited. The landscape classifications can also assist in making landscape evaluations since they allow different landscape types to be compared in respect of such properties such as their typicalness, rarity, naturalness and position on a geographical or ecological gradient.</p></abstract><textClass><keywords scheme="Journal Subject"><list><head>Life Sciences</head><item><term>Ecology</term></item><item><term>Landscape Ecology</term></item><item><term>Plant Ecology</term></item><item><term>Forestry</term></item><item><term>Forestry Management</term></item><item><term>Plant Sciences</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="1992-12-01">Published</change><change xml:id="refBibs-istex" who="#ISTEX-API" when="2016-11-22">References added</change><change xml:id="refBibs-istex" who="#ISTEX-API" when="2017-01-21">References added</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/D48B6B871B0B8CFD7791F309CC1B5AD6EEC6261D/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Springer, Publisher found" wicri:toSee="no header"><istex:xmlDeclaration>version="1.0" encoding="UTF-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//Springer-Verlag//DTD A++ V2.4//EN" URI="http://devel.springer.de/A++/V2.4/DTD/A++V2.4.dtd" name="istex:docType"></istex:docType><istex:document><Publisher><PublisherInfo><PublisherName>Kluwer Academic Publishers</PublisherName><PublisherLocation>Dordrecht</PublisherLocation></PublisherInfo><Journal><JournalInfo JournalProductType="ArchiveJournal" NumberingStyle="Unnumbered"><JournalID>10980</JournalID><JournalPrintISSN>0921-2973</JournalPrintISSN><JournalElectronicISSN>1572-9761</JournalElectronicISSN><JournalTitle>Landscape Ecology</JournalTitle><JournalAbbreviatedTitle>Landscape Ecol</JournalAbbreviatedTitle><JournalSubjectGroup><JournalSubject Type="Primary">Life Sciences</JournalSubject><JournalSubject Type="Secondary">Ecology</JournalSubject><JournalSubject Type="Secondary">Landscape Ecology</JournalSubject><JournalSubject Type="Secondary">Plant Ecology</JournalSubject><JournalSubject Type="Secondary">Forestry</JournalSubject><JournalSubject Type="Secondary">Forestry Management</JournalSubject><JournalSubject Type="Secondary">Plant Sciences</JournalSubject></JournalSubjectGroup></JournalInfo><Volume><VolumeInfo VolumeType="Regular" TocLevels="0"><VolumeIDStart>7</VolumeIDStart><VolumeIDEnd>7</VolumeIDEnd><VolumeIssueCount>4</VolumeIssueCount></VolumeInfo><Issue IssueType="Regular"><IssueInfo TocLevels="0"><IssueIDStart>4</IssueIDStart><IssueIDEnd>4</IssueIDEnd><IssueArticleCount>5</IssueArticleCount><IssueHistory><CoverDate><Year>1992</Year><Month>12</Month></CoverDate></IssueHistory><IssueCopyright><CopyrightHolderName>SPB Academic Publishing bv</CopyrightHolderName><CopyrightYear>1992</CopyrightYear></IssueCopyright></IssueInfo><Article ID="Art3"><ArticleInfo Language="En" ArticleType="OriginalPaper" NumberingStyle="Unnumbered" TocLevels="0" ContainsESM="No"><ArticleID>BF00131256</ArticleID><ArticleDOI>10.1007/BF00131256</ArticleDOI><ArticleSequenceNumber>3</ArticleSequenceNumber><ArticleTitle Language="En">The use of remotely-sensed satellite imagery for landscape classification in Wales (U.K.)</ArticleTitle><ArticleFirstPage>253</ArticleFirstPage><ArticleLastPage>274</ArticleLastPage><ArticleHistory><RegistrationDate><Year>2004</Year><Month>5</Month><Day>25</Day></RegistrationDate></ArticleHistory><ArticleCopyright><CopyrightHolderName>SPB Academic Publishing bv</CopyrightHolderName><CopyrightYear>1992</CopyrightYear></ArticleCopyright><ArticleGrants Type="Regular"><MetadataGrant Grant="OpenAccess"></MetadataGrant><AbstractGrant Grant="OpenAccess"></AbstractGrant><BodyPDFGrant Grant="Restricted"></BodyPDFGrant><BodyHTMLGrant Grant="Restricted"></BodyHTMLGrant><BibliographyGrant Grant="Restricted"></BibliographyGrant><ESMGrant Grant="Restricted"></ESMGrant></ArticleGrants><ArticleContext><JournalID>10980</JournalID><VolumeIDStart>7</VolumeIDStart><VolumeIDEnd>7</VolumeIDEnd><IssueIDStart>4</IssueIDStart><IssueIDEnd>4</IssueIDEnd></ArticleContext></ArticleInfo><ArticleHeader><AuthorGroup><Author AffiliationIDS="Aff1"><AuthorName DisplayOrder="Western"><GivenName>Roy</GivenName><GivenName>H.</GivenName><FamilyName>Haines-Young</FamilyName></AuthorName></Author><Affiliation ID="Aff1"><OrgDivision>Department of Geography</OrgDivision><OrgName>University of Nottingham</OrgName><OrgAddress><Postcode>NG7 2RD</Postcode><City>Nottingham</City><Country>UK</Country></OrgAddress></Affiliation></AuthorGroup><Abstract ID="Abs1" Language="En"><Heading>Abstract</Heading><Para>Remotely-sensed satellite data from Landsat TM and MSS were processed digitally to make landscape classifications of three study areas of south east Wales. The classifications were constructed by classifying major variations in land cover mosaics within the areas, and using these data to group the 1 km × 1 km cells of the National Grid into landscape classes according to the combination of cover types found within them. The TWINSPAN algorithm, which is a polythetic, divisive classification method, was used as the basis of the study.</Para><Para>The results showed that while satellite imagery could only be used to extract information about land cover, the close association betwen landscape, land cover and terrain meant that the major physical divisions in the study area could also be detected in the landscape classification. The landscape types recognised in the study were found to be consistent with those indicated in other independent data which relate to the areas. These data included the ITE Land Classes for Great Britain, and the Agricultural (June) Census statistics for England and Wales.</Para><Para>The approach to landscape classification described allows landscape classifications to be made rapidly. These classifications can provide a sampling frameworks for landscape survey in areas where basic map data are lacking or resources for field survey are limited. The landscape classifications can also assist in making landscape evaluations since they allow different landscape types to be compared in respect of such properties such as their typicalness, rarity, naturalness and position on a geographical or ecological gradient.</Para></Abstract><KeywordGroup Language="En"><Heading>Keywords</Heading><Keyword>landscape classification</Keyword><Keyword>landscape survey</Keyword><Keyword>remote sensing</Keyword></KeywordGroup></ArticleHeader><NoBody></NoBody></Article></Issue></Volume></Journal></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>The use of remotely-sensed satellite imagery for landscape classification in Wales (U.K.)</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>The use of remotely-sensed satellite imagery for landscape classification in Wales (U.K.)</title></titleInfo><name type="personal"><namePart type="given">Roy</namePart><namePart type="given">H.</namePart><namePart type="family">Haines-Young</namePart><affiliation>Department of Geography, University of Nottingham, NG7 2RD, Nottingham, UK</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="OriginalPaper"></genre><originInfo><publisher>Kluwer Academic Publishers</publisher><place><placeTerm type="text">Dordrecht</placeTerm></place><dateIssued encoding="w3cdtf">1992-12-01</dateIssued><copyrightDate encoding="w3cdtf">1992</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: Remotely-sensed satellite data from Landsat TM and MSS were processed digitally to make landscape classifications of three study areas of south east Wales. The classifications were constructed by classifying major variations in land cover mosaics within the areas, and using these data to group the 1 km × 1 km cells of the National Grid into landscape classes according to the combination of cover types found within them. The TWINSPAN algorithm, which is a polythetic, divisive classification method, was used as the basis of the study. The results showed that while satellite imagery could only be used to extract information about land cover, the close association betwen landscape, land cover and terrain meant that the major physical divisions in the study area could also be detected in the landscape classification. The landscape types recognised in the study were found to be consistent with those indicated in other independent data which relate to the areas. These data included the ITE Land Classes for Great Britain, and the Agricultural (June) Census statistics for England and Wales. The approach to landscape classification described allows landscape classifications to be made rapidly. These classifications can provide a sampling frameworks for landscape survey in areas where basic map data are lacking or resources for field survey are limited. The landscape classifications can also assist in making landscape evaluations since they allow different landscape types to be compared in respect of such properties such as their typicalness, rarity, naturalness and position on a geographical or ecological gradient.</abstract><relatedItem type="host"><titleInfo><title>Landscape Ecology</title></titleInfo><titleInfo type="abbreviated"><title>Landscape Ecol</title></titleInfo><genre type="journal" displayLabel="Archive Journal"></genre><originInfo><dateIssued encoding="w3cdtf">1992-12-01</dateIssued><copyrightDate encoding="w3cdtf">1992</copyrightDate></originInfo><subject><genre>Life Sciences</genre><topic>Ecology</topic><topic>Landscape Ecology</topic><topic>Plant Ecology</topic><topic>Forestry</topic><topic>Forestry Management</topic><topic>Plant Sciences</topic></subject><identifier type="ISSN">0921-2973</identifier><identifier type="eISSN">1572-9761</identifier><identifier type="JournalID">10980</identifier><identifier type="IssueArticleCount">5</identifier><identifier type="VolumeIssueCount">4</identifier><part><date>1992</date><detail type="volume"><number>7</number><caption>vol.</caption></detail><detail type="issue"><number>4</number><caption>no.</caption></detail><extent unit="pages"><start>253</start><end>274</end></extent></part><recordInfo><recordOrigin>SPB Academic Publishing bv, 1992</recordOrigin></recordInfo></relatedItem><identifier type="istex">D48B6B871B0B8CFD7791F309CC1B5AD6EEC6261D</identifier><identifier type="DOI">10.1007/BF00131256</identifier><identifier type="ArticleID">BF00131256</identifier><identifier type="ArticleID">Art3</identifier><accessCondition type="use and reproduction" contentType="copyright">SPB Academic Publishing bv, 1992</accessCondition><recordInfo><recordContentSource>SPRINGER</recordContentSource><recordOrigin>SPB Academic Publishing bv, 1992</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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