The potential of remote sensing for monitoring rural land use changes and their effects on soil conditions
Identifieur interne : 001754 ( Istex/Corpus ); précédent : 001753; suivant : 001755The potential of remote sensing for monitoring rural land use changes and their effects on soil conditions
Auteurs : S. Sommer ; J. Hill ; J. MégierSource :
- Agriculture, Ecosystems and Environment [ 0167-8809 ] ; 1998.
Abstract
The paper reviews the principles of existing remote sensing techniques and new methods considered particularly suitable for monitoring rural land use changes and their effects on soil conditions. Conventional classification methods in combination with local field surveys are operationally used in national as well as in supra-national environmental and agricultural inventories established by the EU such as the European Commission's CORINE programme (Coordination of Information on the Environment) and the MARS project (Monitoring Agriculture with Remote Sensing). The `Environmental Mapping and Modelling Unit' (EMAP) of the EC Joint Research Centre, in cooperation with other partners, is investigating the use of operational earth observation satellites and airborne hyperspectral data (imaging spectrometry) for mapping and monitoring of vegetation and soil characteristics. In the context of previous experiments, approaches such as spectral mixture analysis have been developed which can already be routinely applied to large regions. Problems related to the standardised retrieval of remotely sensed primary parameters (such as reflectance), concepts for the thematic interpretation of reflectance data, and the definition of satellite-derived land degradation indices are discussed. On this basis, the requirements for the design of an operational satellite observatory for environmental monitoring are presented.
Url:
DOI: 10.1016/S0167-8809(97)00119-9
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ISTEX:26172E3E2983FE384635614B76E8E65E4397CDE1Le document en format XML
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Sommer</name><affiliation><mods:affiliation>SAI/EMAP, European Commission, Joint Research Centre, Space Applications Institute, Ispra I-21020, Italy</mods:affiliation></affiliation></author><author><name sortKey="Hill, J" sort="Hill, J" uniqKey="Hill J" first="J." last="Hill">J. Hill</name><affiliation><mods:affiliation>University of Trier, FB VI Geography, Remote Sensing Dept., Trier D-54286, Germany</mods:affiliation></affiliation></author><author><name sortKey="Megier, J" sort="Megier, J" uniqKey="Megier J" first="J." last="Mégier">J. 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Conventional classification methods in combination with local field surveys are operationally used in national as well as in supra-national environmental and agricultural inventories established by the EU such as the European Commission's CORINE programme (Coordination of Information on the Environment) and the MARS project (Monitoring Agriculture with Remote Sensing). The `Environmental Mapping and Modelling Unit' (EMAP) of the EC Joint Research Centre, in cooperation with other partners, is investigating the use of operational earth observation satellites and airborne hyperspectral data (imaging spectrometry) for mapping and monitoring of vegetation and soil characteristics. In the context of previous experiments, approaches such as spectral mixture analysis have been developed which can already be routinely applied to large regions. Problems related to the standardised retrieval of remotely sensed primary parameters (such as reflectance), concepts for the thematic interpretation of reflectance data, and the definition of satellite-derived land degradation indices are discussed. On this basis, the requirements for the design of an operational satellite observatory for environmental monitoring are presented.</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>S. Sommer</name><affiliations><json:string>SAI/EMAP, European Commission, Joint Research Centre, Space Applications Institute, Ispra I-21020, Italy</json:string></affiliations></json:item><json:item><name>J. Hill</name><affiliations><json:string>University of Trier, FB VI Geography, Remote Sensing Dept., Trier D-54286, Germany</json:string></affiliations></json:item><json:item><name>J. Mégier</name><affiliations><json:string>SAI/EMAP, European Commission, Joint Research Centre, Space Applications Institute, Ispra I-21020, Italy</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>Soil degradation</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Environmental monitoring</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Earth observation satellites</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Airborne hyperspectral data</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Spectral mixture analysis</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Environmental satellite observatory</value></json:item></subject><language><json:string>eng</json:string></language><originalGenre><json:string>Full-length article</json:string></originalGenre><abstract>The paper reviews the principles of existing remote sensing techniques and new methods considered particularly suitable for monitoring rural land use changes and their effects on soil conditions. Conventional classification methods in combination with local field surveys are operationally used in national as well as in supra-national environmental and agricultural inventories established by the EU such as the European Commission's CORINE programme (Coordination of Information on the Environment) and the MARS project (Monitoring Agriculture with Remote Sensing). The `Environmental Mapping and Modelling Unit' (EMAP) of the EC Joint Research Centre, in cooperation with other partners, is investigating the use of operational earth observation satellites and airborne hyperspectral data (imaging spectrometry) for mapping and monitoring of vegetation and soil characteristics. In the context of previous experiments, approaches such as spectral mixture analysis have been developed which can already be routinely applied to large regions. Problems related to the standardised retrieval of remotely sensed primary parameters (such as reflectance), concepts for the thematic interpretation of reflectance data, and the definition of satellite-derived land degradation indices are discussed. On this basis, the requirements for the design of an operational satellite observatory for environmental monitoring are presented.</abstract><qualityIndicators><score>7.316</score><pdfVersion>1.2</pdfVersion><pdfPageSize>540 x 712 pts</pdfPageSize><refBibsNative>true</refBibsNative><keywordCount>6</keywordCount><abstractCharCount>1424</abstractCharCount><pdfWordCount>5583</pdfWordCount><pdfCharCount>37061</pdfCharCount><pdfPageCount>13</pdfPageCount><abstractWordCount>193</abstractWordCount></qualityIndicators><title>The potential of remote sensing for monitoring rural land use changes and their effects on soil conditions</title><pii><json:string>S0167-8809(97)00119-9</json:string></pii><refBibs><json:item><host><author></author></host></json:item><json:item><host><author></author></host></json:item><json:item><host><author></author></host></json:item><json:item><author><json:item><name>J.P.G.W. 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Gillespie, A</name></json:item></author><host><volume>31</volume><pages><last>26</last><first>1</first></pages><author></author><title>Remote Sensing Environ.</title></host><title>Vegetation in deserts: I. a regional measure of abundance from multispectral images</title></json:item><json:item><host><author></author></host></json:item><json:item><author><json:item><name>E.R. Stoner</name></json:item><json:item><name>M.F. Baumgardner</name></json:item></author><host><volume>45</volume><pages><last>1165</last><first>1161</first></pages><author></author><title>J. Am. Soc. Soil Sci.</title></host><title>Characteristic variations in the reflectance of surface soils</title></json:item><json:item><host><author></author></host></json:item><json:item><host><author></author></host></json:item></refBibs><genre><json:string>research-article</json:string></genre><host><volume>67</volume><pii><json:string>S0167-8809(00)X0044-8</json:string></pii><pages><last>209</last><first>197</first></pages><issn><json:string>0167-8809</json:string></issn><issue>2–3</issue><genre><json:string>journal</json:string></genre><language><json:string>unknown</json:string></language><title>Agriculture, Ecosystems and Environment</title><publicationDate>1998</publicationDate></host><publicationDate>1998</publicationDate><copyrightDate>1998</copyrightDate><doi><json:string>10.1016/S0167-8809(97)00119-9</json:string></doi><id>26172E3E2983FE384635614B76E8E65E4397CDE1</id><score>0.8569974</score><fulltext><json:item><extension>pdf</extension><original>true</original><mimetype>application/pdf</mimetype><uri>https://api.istex.fr/document/26172E3E2983FE384635614B76E8E65E4397CDE1/fulltext/pdf</uri></json:item><json:item><extension>zip</extension><original>false</original><mimetype>application/zip</mimetype><uri>https://api.istex.fr/document/26172E3E2983FE384635614B76E8E65E4397CDE1/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/26172E3E2983FE384635614B76E8E65E4397CDE1/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a">The potential of remote sensing for monitoring rural land use changes and their effects on soil conditions</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>ELSEVIER</publisher><availability><p>©1998 Elsevier Science B.V.</p></availability><date>1998</date></publicationStmt><notesStmt><note type="content">Fig. 1: Characteristic soil bidirectional reflectance spectra after Baumgardner et al. (1985). Curve (A) developed fine textured soils with high (>2%) organic matter content; (B) undeveloped soils with low (<2%) organic matter and low (<1%) iron oxide content; (C) developed soil with low (<2%) organic matter and medium (1–4%) iron oxide content; (D) moderately course textured soils with high (>2%) organic matter content and low (<1%) iron-oxide content; (E) fine textured soils with high (>4%) iron oxide content.</note><note type="content">Fig. 2: Process flow-chart for the production of accurate land cover maps and statistical inventories with multi-temporal earth observation satellite images (Hill, 1993a).</note><note type="content">Fig. 3: The conversion of satellite raw data into standardised thematic information layers (Hill et al., 1995b).</note><note type="content">Fig. 4: Ternary plot of about 100 field- and lab-measured soil spectra at Landsat-TM spectral resolution, where the mixing volume is defined by one soil (vertic cambisol) and two bedrock spectra (marls and limestone). Soil conditions range from undisturbed soils (I) to substrates that are increasingly affected by erosion (II–IVa/b) (Hill et al., 1995b).</note><note type="content">Fig. 5: Spectral endmembers of the expanded linear mixing model in the spectral resolution of an imaging spectrometer (AVIRIS, NASA/JPL) and the Landsat-5 TM system (Hill et al., 1995a).</note><note type="content">Fig. 6: Degradation of satellite detectable soil conditions in a Mediterranean test site (Xilokastron, NE-Peloponnesos, Greece) between 1985 and 1990, mapped with SMA from Landsat TM images. The black parts are masked areas with more than 50% vegetation cover. Soil conditions are mapped as grey values ranging from I (undisturbed soils), II (moderately degraded), III (severely degraded) and IV (denuded parent material/rock) (Hill, 1993b).</note><note type="content">Fig. 7: Classification of spectral anomalies of rape and rye grown on a filled waste deposit. The classification was performed according to the spectral match of GER 63 band imaging spectrometer pixels with heavy metal affected reference spectra. The highest spectral anomalies, marked with the white pointers, are related to Zinc anomalies. The factor of the grey scale is related to the standard deviation of pixel and reference spectra (Rothfuss, 1994).</note><note type="content">Fig. 8: Processing scheme for deriving standardised land degradation indices from earth observation satellite data (Hill et al., 1995b).</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a">The potential of remote sensing for monitoring rural land use changes and their effects on soil conditions</title><author xml:id="author-1"><persName><forename type="first">S.</forename><surname>Sommer</surname></persName><note type="correspondence"><p>Corresponding author. Tel.: +39-332-789631; fax: +39-332-789469; e-mail: stefan.sommer@jrc.it</p></note><affiliation>SAI/EMAP, European Commission, Joint Research Centre, Space Applications Institute, Ispra I-21020, Italy</affiliation></author><author xml:id="author-2"><persName><forename type="first">J.</forename><surname>Hill</surname></persName><affiliation>University of Trier, FB VI Geography, Remote Sensing Dept., Trier D-54286, Germany</affiliation></author><author xml:id="author-3"><persName><forename type="first">J.</forename><surname>Mégier</surname></persName><affiliation>SAI/EMAP, European Commission, Joint Research Centre, Space Applications Institute, Ispra I-21020, Italy</affiliation></author></analytic><monogr><title level="j">Agriculture, Ecosystems and Environment</title><title level="j" type="abbrev">AGEE</title><idno type="pISSN">0167-8809</idno><idno type="PII">S0167-8809(00)X0044-8</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1998"></date><biblScope unit="volume">67</biblScope><biblScope unit="issue">2–3</biblScope><biblScope unit="page" from="197">197</biblScope><biblScope unit="page" to="209">209</biblScope></imprint></monogr><idno type="istex">26172E3E2983FE384635614B76E8E65E4397CDE1</idno><idno type="DOI">10.1016/S0167-8809(97)00119-9</idno><idno type="PII">S0167-8809(97)00119-9</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>1998</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>The paper reviews the principles of existing remote sensing techniques and new methods considered particularly suitable for monitoring rural land use changes and their effects on soil conditions. Conventional classification methods in combination with local field surveys are operationally used in national as well as in supra-national environmental and agricultural inventories established by the EU such as the European Commission's CORINE programme (Coordination of Information on the Environment) and the MARS project (Monitoring Agriculture with Remote Sensing). The `Environmental Mapping and Modelling Unit' (EMAP) of the EC Joint Research Centre, in cooperation with other partners, is investigating the use of operational earth observation satellites and airborne hyperspectral data (imaging spectrometry) for mapping and monitoring of vegetation and soil characteristics. In the context of previous experiments, approaches such as spectral mixture analysis have been developed which can already be routinely applied to large regions. Problems related to the standardised retrieval of remotely sensed primary parameters (such as reflectance), concepts for the thematic interpretation of reflectance data, and the definition of satellite-derived land degradation indices are discussed. On this basis, the requirements for the design of an operational satellite observatory for environmental monitoring are presented.</p></abstract><textClass><keywords scheme="keyword"><list><head>Keywords</head><item><term>Soil degradation</term></item><item><term>Environmental monitoring</term></item><item><term>Earth observation satellites</term></item><item><term>Airborne hyperspectral data</term></item><item><term>Spectral mixture analysis</term></item><item><term>Environmental satellite observatory</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="1998">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/26172E3E2983FE384635614B76E8E65E4397CDE1/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Elsevier, elements deleted: ce:floats; body; tail"><istex:xmlDeclaration>version="1.0" encoding="utf-8"</istex:xmlDeclaration><istex:docType PUBLIC="-//ES//DTD journal article DTD version 4.5.2//EN//XML" URI="art452.dtd" name="istex:docType"><istex:entity SYSTEM="gr1" NDATA="IMAGE" name="gr1"></istex:entity><istex:entity SYSTEM="gr2" NDATA="IMAGE" name="gr2"></istex:entity><istex:entity SYSTEM="gr3" NDATA="IMAGE" name="gr3"></istex:entity><istex:entity SYSTEM="gr4" NDATA="IMAGE" name="gr4"></istex:entity><istex:entity SYSTEM="gr5" NDATA="IMAGE" name="gr5"></istex:entity><istex:entity SYSTEM="gr6" NDATA="IMAGE" name="gr6"></istex:entity><istex:entity SYSTEM="gr7" NDATA="IMAGE" name="gr7"></istex:entity><istex:entity SYSTEM="gr8" NDATA="IMAGE" name="gr8"></istex:entity></istex:docType><istex:document><converted-article version="4.5.2" docsubtype="fla"><item-info><jid>AGEE</jid><aid>1263</aid><ce:pii>S0167-8809(97)00119-9</ce:pii><ce:doi>10.1016/S0167-8809(97)00119-9</ce:doi><ce:copyright year="1998" type="full-transfer">Elsevier Science B.V.</ce:copyright></item-info><head><ce:title>The potential of remote sensing for monitoring rural land use changes and their effects on soil conditions</ce:title><ce:author-group><ce:author><ce:given-name>S.</ce:given-name><ce:surname>Sommer</ce:surname><ce:cross-ref refid="AFF1">a</ce:cross-ref><ce:cross-ref refid="CORR1">*</ce:cross-ref></ce:author><ce:author><ce:given-name>J.</ce:given-name><ce:surname>Hill</ce:surname><ce:cross-ref refid="AFF2">b</ce:cross-ref></ce:author><ce:author><ce:given-name>J.</ce:given-name><ce:surname>Mégier</ce:surname><ce:cross-ref refid="AFF1">a</ce:cross-ref></ce:author><ce:affiliation id="AFF1"><ce:label>a</ce:label><ce:textfn>SAI/EMAP, European Commission, Joint Research Centre, Space Applications Institute, Ispra I-21020, Italy</ce:textfn></ce:affiliation><ce:affiliation id="AFF2"><ce:label>b</ce:label><ce:textfn>University of Trier, FB VI Geography, Remote Sensing Dept., Trier D-54286, Germany</ce:textfn></ce:affiliation><ce:correspondence id="CORR1"><ce:label>*</ce:label><ce:text>Corresponding author. Tel.: +39-332-789631; fax: +39-332-789469; e-mail: stefan.sommer@jrc.it</ce:text></ce:correspondence></ce:author-group><ce:abstract><ce:section-title>Abstract</ce:section-title><ce:abstract-sec><ce:simple-para>The paper reviews the principles of existing remote sensing techniques and new methods considered particularly suitable for monitoring rural land use changes and their effects on soil conditions. Conventional classification methods in combination with local field surveys are operationally used in national as well as in supra-national environmental and agricultural inventories established by the EU such as the European Commission's CORINE programme (Coordination of Information on the Environment) and the MARS project (Monitoring Agriculture with Remote Sensing). The `Environmental Mapping and Modelling Unit' (EMAP) of the EC Joint Research Centre, in cooperation with other partners, is investigating the use of operational earth observation satellites and airborne hyperspectral data (imaging spectrometry) for mapping and monitoring of vegetation and soil characteristics. In the context of previous experiments, approaches such as spectral mixture analysis have been developed which can already be routinely applied to large regions. Problems related to the standardised retrieval of remotely sensed primary parameters (such as reflectance), concepts for the thematic interpretation of reflectance data, and the definition of satellite-derived land degradation indices are discussed. On this basis, the requirements for the design of an operational satellite observatory for environmental monitoring are presented.</ce:simple-para></ce:abstract-sec></ce:abstract><ce:keywords class="keyword"><ce:section-title>Keywords</ce:section-title><ce:keyword><ce:text>Soil degradation</ce:text></ce:keyword><ce:keyword><ce:text>Environmental monitoring</ce:text></ce:keyword><ce:keyword><ce:text>Earth observation satellites</ce:text></ce:keyword><ce:keyword><ce:text>Airborne hyperspectral data</ce:text></ce:keyword><ce:keyword><ce:text>Spectral mixture analysis</ce:text></ce:keyword><ce:keyword><ce:text>Environmental satellite observatory</ce:text></ce:keyword></ce:keywords></head></converted-article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo><title>The potential of remote sensing for monitoring rural land use changes and their effects on soil conditions</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>The potential of remote sensing for monitoring rural land use changes and their effects on soil conditions</title></titleInfo><name type="personal"><namePart type="given">S.</namePart><namePart type="family">Sommer</namePart><affiliation>SAI/EMAP, European Commission, Joint Research Centre, Space Applications Institute, Ispra I-21020, Italy</affiliation><description>Corresponding author. Tel.: +39-332-789631; fax: +39-332-789469; e-mail: stefan.sommer@jrc.it</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">J.</namePart><namePart type="family">Hill</namePart><affiliation>University of Trier, FB VI Geography, Remote Sensing Dept., Trier D-54286, Germany</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">J.</namePart><namePart type="family">Mégier</namePart><affiliation>SAI/EMAP, European Commission, Joint Research Centre, Space Applications Institute, Ispra I-21020, Italy</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="research-article" displayLabel="Full-length article"></genre><originInfo><publisher>ELSEVIER</publisher><dateIssued encoding="w3cdtf">1998</dateIssued><copyrightDate encoding="w3cdtf">1998</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 paper reviews the principles of existing remote sensing techniques and new methods considered particularly suitable for monitoring rural land use changes and their effects on soil conditions. Conventional classification methods in combination with local field surveys are operationally used in national as well as in supra-national environmental and agricultural inventories established by the EU such as the European Commission's CORINE programme (Coordination of Information on the Environment) and the MARS project (Monitoring Agriculture with Remote Sensing). The `Environmental Mapping and Modelling Unit' (EMAP) of the EC Joint Research Centre, in cooperation with other partners, is investigating the use of operational earth observation satellites and airborne hyperspectral data (imaging spectrometry) for mapping and monitoring of vegetation and soil characteristics. In the context of previous experiments, approaches such as spectral mixture analysis have been developed which can already be routinely applied to large regions. Problems related to the standardised retrieval of remotely sensed primary parameters (such as reflectance), concepts for the thematic interpretation of reflectance data, and the definition of satellite-derived land degradation indices are discussed. On this basis, the requirements for the design of an operational satellite observatory for environmental monitoring are presented.</abstract><note type="content">Fig. 1: Characteristic soil bidirectional reflectance spectra after Baumgardner et al. (1985). Curve (A) developed fine textured soils with high (>2%) organic matter content; (B) undeveloped soils with low (<2%) organic matter and low (<1%) iron oxide content; (C) developed soil with low (<2%) organic matter and medium (1–4%) iron oxide content; (D) moderately course textured soils with high (>2%) organic matter content and low (<1%) iron-oxide content; (E) fine textured soils with high (>4%) iron oxide content.</note><note type="content">Fig. 2: Process flow-chart for the production of accurate land cover maps and statistical inventories with multi-temporal earth observation satellite images (Hill, 1993a).</note><note type="content">Fig. 3: The conversion of satellite raw data into standardised thematic information layers (Hill et al., 1995b).</note><note type="content">Fig. 4: Ternary plot of about 100 field- and lab-measured soil spectra at Landsat-TM spectral resolution, where the mixing volume is defined by one soil (vertic cambisol) and two bedrock spectra (marls and limestone). Soil conditions range from undisturbed soils (I) to substrates that are increasingly affected by erosion (II–IVa/b) (Hill et al., 1995b).</note><note type="content">Fig. 5: Spectral endmembers of the expanded linear mixing model in the spectral resolution of an imaging spectrometer (AVIRIS, NASA/JPL) and the Landsat-5 TM system (Hill et al., 1995a).</note><note type="content">Fig. 6: Degradation of satellite detectable soil conditions in a Mediterranean test site (Xilokastron, NE-Peloponnesos, Greece) between 1985 and 1990, mapped with SMA from Landsat TM images. The black parts are masked areas with more than 50% vegetation cover. Soil conditions are mapped as grey values ranging from I (undisturbed soils), II (moderately degraded), III (severely degraded) and IV (denuded parent material/rock) (Hill, 1993b).</note><note type="content">Fig. 7: Classification of spectral anomalies of rape and rye grown on a filled waste deposit. The classification was performed according to the spectral match of GER 63 band imaging spectrometer pixels with heavy metal affected reference spectra. The highest spectral anomalies, marked with the white pointers, are related to Zinc anomalies. The factor of the grey scale is related to the standard deviation of pixel and reference spectra (Rothfuss, 1994).</note><note type="content">Fig. 8: Processing scheme for deriving standardised land degradation indices from earth observation satellite data (Hill et al., 1995b).</note><subject><genre>Keywords</genre><topic>Soil degradation</topic><topic>Environmental monitoring</topic><topic>Earth observation satellites</topic><topic>Airborne hyperspectral data</topic><topic>Spectral mixture analysis</topic><topic>Environmental satellite observatory</topic></subject><relatedItem type="host"><titleInfo><title>Agriculture, Ecosystems and Environment</title></titleInfo><titleInfo type="abbreviated"><title>AGEE</title></titleInfo><genre type="journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">199802</dateIssued></originInfo><identifier type="ISSN">0167-8809</identifier><identifier type="PII">S0167-8809(00)X0044-8</identifier><part><date>199802</date><detail type="volume"><number>67</number><caption>vol.</caption></detail><detail type="issue"><number>2–3</number><caption>no.</caption></detail><extent unit="issue pages"><start>97</start><end>302</end></extent><extent unit="pages"><start>197</start><end>209</end></extent></part></relatedItem><identifier type="istex">26172E3E2983FE384635614B76E8E65E4397CDE1</identifier><identifier type="DOI">10.1016/S0167-8809(97)00119-9</identifier><identifier type="PII">S0167-8809(97)00119-9</identifier><accessCondition type="use and reproduction" contentType="copyright">©1998 Elsevier Science B.V.</accessCondition><recordInfo><recordContentSource>ELSEVIER</recordContentSource><recordOrigin>Elsevier Science B.V., ©1998</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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