Multisensor remote sensing data for land use/cover mapping
Identifieur interne : 000895 ( Istex/Corpus ); précédent : 000894; suivant : 000896Multisensor remote sensing data for land use/cover mapping
Auteurs : B. Haack ; M. BechdolSource :
- Computers, Environment and Urban Systems [ 0198-9715 ] ; 1999.
Abstract
Spaceborne radar data have only recently been consistently available. This project evaluated, independently and in combination, the relative utility of traditional spaceborne optical data from the visible and infrared wavelengths and the more longer wavelength radar. East African landscapes including settlements, natural vegetation, and agriculture were examined as case studies. For three study sites, multisensor data sets were digitally integrated with training and truth information derived from field visits assisted by global positioning systems. For each study site, a variety of information extraction techniques were conducted. The primary methodology was standard image processing spectral signature extraction and application of a statistical decision rule to classify the surface features. The relative accuracy of the classifications were established by comparison to ground truth information. Several primary results were obtained, all of which establish the value of spaceborne radar. For one site, the combination of sensors obtained good mapping accuracies when neither sensor could independently. In other sites, the radar was independently as useful as the optical data. For radar, additional processing manipulations, such as pre- and post-filtering significantly improved classification accuracies. ©
Url:
DOI: 10.1016/S0198-9715(99)00003-4
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Bechdol</name><affiliation><mods:affiliation>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:D765ABBE74BAB9645C1F99C3B13BECE182126755</idno><date when="1999" year="1999">1999</date><idno type="doi">10.1016/S0198-9715(99)00003-4</idno><idno type="url">https://api.istex.fr/document/D765ABBE74BAB9645C1F99C3B13BECE182126755/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">000895</idno><idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">000895</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a">Multisensor remote sensing data for land use/cover mapping</title><author><name sortKey="Haack, B" sort="Haack, B" uniqKey="Haack B" first="B" last="Haack">B. Haack</name><affiliation><mods:affiliation>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</mods:affiliation></affiliation></author><author><name sortKey="Bechdol, M" sort="Bechdol, M" uniqKey="Bechdol M" first="M" last="Bechdol">M. Bechdol</name><affiliation><mods:affiliation>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j">Computers, Environment and Urban Systems</title><title level="j" type="abbrev">CEUS</title><idno type="ISSN">0198-9715</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1999">1999</date><biblScope unit="volume">23</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="53">53</biblScope><biblScope unit="page" to="69">69</biblScope></imprint><idno type="ISSN">0198-9715</idno></series><idno type="istex">D765ABBE74BAB9645C1F99C3B13BECE182126755</idno><idno type="DOI">10.1016/S0198-9715(99)00003-4</idno><idno type="PII">S0198-9715(99)00003-4</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0198-9715</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Spaceborne radar data have only recently been consistently available. This project evaluated, independently and in combination, the relative utility of traditional spaceborne optical data from the visible and infrared wavelengths and the more longer wavelength radar. East African landscapes including settlements, natural vegetation, and agriculture were examined as case studies. For three study sites, multisensor data sets were digitally integrated with training and truth information derived from field visits assisted by global positioning systems. For each study site, a variety of information extraction techniques were conducted. The primary methodology was standard image processing spectral signature extraction and application of a statistical decision rule to classify the surface features. The relative accuracy of the classifications were established by comparison to ground truth information. Several primary results were obtained, all of which establish the value of spaceborne radar. For one site, the combination of sensors obtained good mapping accuracies when neither sensor could independently. In other sites, the radar was independently as useful as the optical data. For radar, additional processing manipulations, such as pre- and post-filtering significantly improved classification accuracies. ©</div></front></TEI><istex><corpusName>elsevier</corpusName><author><json:item><name>B Haack</name><affiliations><json:string>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</json:string></affiliations></json:item><json:item><name>M Bechdol</name><affiliations><json:string>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>Multisensor</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Land use/cover mapping</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Radar</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Sensor fusion</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>Texture</value></json:item></subject><language><json:string>eng</json:string></language><originalGenre><json:string>Full-length article</json:string></originalGenre><abstract>Spaceborne radar data have only recently been consistently available. This project evaluated, independently and in combination, the relative utility of traditional spaceborne optical data from the visible and infrared wavelengths and the more longer wavelength radar. East African landscapes including settlements, natural vegetation, and agriculture were examined as case studies. For three study sites, multisensor data sets were digitally integrated with training and truth information derived from field visits assisted by global positioning systems. For each study site, a variety of information extraction techniques were conducted. The primary methodology was standard image processing spectral signature extraction and application of a statistical decision rule to classify the surface features. The relative accuracy of the classifications were established by comparison to ground truth information. Several primary results were obtained, all of which establish the value of spaceborne radar. For one site, the combination of sensors obtained good mapping accuracies when neither sensor could independently. In other sites, the radar was independently as useful as the optical data. For radar, additional processing manipulations, such as pre- and post-filtering significantly improved classification accuracies. ©</abstract><qualityIndicators><score>7.16</score><pdfVersion>1.2</pdfVersion><pdfPageSize>468 x 680 pts</pdfPageSize><refBibsNative>true</refBibsNative><keywordCount>5</keywordCount><abstractCharCount>1323</abstractCharCount><pdfWordCount>6101</pdfWordCount><pdfCharCount>37937</pdfCharCount><pdfPageCount>17</pdfPageCount><abstractWordCount>180</abstractWordCount></qualityIndicators><title>Multisensor remote sensing data for land use/cover mapping</title><pii><json:string>S0198-9715(99)00003-4</json:string></pii><genre><json:string>research-article</json:string></genre><host><volume>23</volume><pii><json:string>S0198-9715(00)X0020-8</json:string></pii><pages><last>69</last><first>53</first></pages><issn><json:string>0198-9715</json:string></issn><issue>1</issue><genre><json:string>journal</json:string></genre><language><json:string>unknown</json:string></language><title>Computers, Environment and Urban Systems</title><publicationDate>1999</publicationDate></host><categories><wos><json:string>social science</json:string><json:string>geography</json:string><json:string>environmental studies</json:string></wos><scienceMetrix><json:string>applied sciences</json:string><json:string>engineering</json:string><json:string>geological & geomatics engineering</json:string></scienceMetrix></categories><publicationDate>1999</publicationDate><copyrightDate>1999</copyrightDate><doi><json:string>10.1016/S0198-9715(99)00003-4</json:string></doi><id>D765ABBE74BAB9645C1F99C3B13BECE182126755</id><score>0.038670763</score><fulltext><json:item><extension>pdf</extension><original>true</original><mimetype>application/pdf</mimetype><uri>https://api.istex.fr/document/D765ABBE74BAB9645C1F99C3B13BECE182126755/fulltext/pdf</uri></json:item><json:item><extension>zip</extension><original>false</original><mimetype>application/zip</mimetype><uri>https://api.istex.fr/document/D765ABBE74BAB9645C1F99C3B13BECE182126755/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/D765ABBE74BAB9645C1F99C3B13BECE182126755/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a">Multisensor remote sensing data for land use/cover mapping</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>ELSEVIER</publisher><availability><p>©1999 Elsevier Science Ltd</p></availability><date>1999</date></publicationStmt><notesStmt><note type="content">Section title: Article</note><note type="content">Fig. 1: Ground photograph of village near Wad Medani, Sudan.</note><note type="content">Fig. 2: Shuttle image radar (SIR)-B image along the Blue Nile in Sudan (approximate scale 1:70,000).</note><note type="content">Fig. 3: Typical agricultural landscape near Singida, Tanzania.</note><note type="content">Fig. 4: Shuttle imaging radar-C, C-band image near Singida, Tanzania (approximate scale 1:100,000).</note><note type="content">Table 1: Spectral signatures for Wad Medani</note><note type="content">Table 2: Contingency table for Wad Medani</note><note type="content">Table 3: Spectral signatures for Singida</note><note type="content">Table 4: Classification accuracies for Singida comparing sensors and sensor combinations</note><note type="content">Table 5: Post-classification filtering results for Singida</note><note type="content">Table 6: Classification results from Tinderet</note></notesStmt><sourceDesc><biblStruct type="inbook"><analytic><title level="a">Multisensor remote sensing data for land use/cover mapping</title><author xml:id="author-1"><persName><forename type="first">B</forename><surname>Haack</surname></persName><note type="correspondence"><p>Corresponding author. Tel.: +1-703-993-1215; fax: +1-703-993-1216; e-mail: bhaack@gmu.edu</p></note><affiliation>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</affiliation></author><author xml:id="author-2"><persName><forename type="first">M</forename><surname>Bechdol</surname></persName><affiliation>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</affiliation></author></analytic><monogr><title level="j">Computers, Environment and Urban Systems</title><title level="j" type="abbrev">CEUS</title><idno type="pISSN">0198-9715</idno><idno type="PII">S0198-9715(00)X0020-8</idno><imprint><publisher>ELSEVIER</publisher><date type="published" when="1999"></date><biblScope unit="volume">23</biblScope><biblScope unit="issue">1</biblScope><biblScope unit="page" from="53">53</biblScope><biblScope unit="page" to="69">69</biblScope></imprint></monogr><idno type="istex">D765ABBE74BAB9645C1F99C3B13BECE182126755</idno><idno type="DOI">10.1016/S0198-9715(99)00003-4</idno><idno type="PII">S0198-9715(99)00003-4</idno></biblStruct></sourceDesc></fileDesc><profileDesc><creation><date>1999</date></creation><langUsage><language ident="en">en</language></langUsage><abstract xml:lang="en"><p>Spaceborne radar data have only recently been consistently available. This project evaluated, independently and in combination, the relative utility of traditional spaceborne optical data from the visible and infrared wavelengths and the more longer wavelength radar. East African landscapes including settlements, natural vegetation, and agriculture were examined as case studies. For three study sites, multisensor data sets were digitally integrated with training and truth information derived from field visits assisted by global positioning systems. For each study site, a variety of information extraction techniques were conducted. The primary methodology was standard image processing spectral signature extraction and application of a statistical decision rule to classify the surface features. The relative accuracy of the classifications were established by comparison to ground truth information. Several primary results were obtained, all of which establish the value of spaceborne radar. For one site, the combination of sensors obtained good mapping accuracies when neither sensor could independently. In other sites, the radar was independently as useful as the optical data. For radar, additional processing manipulations, such as pre- and post-filtering significantly improved classification accuracies. ©</p></abstract><textClass><keywords scheme="keyword"><list><head>Keywords</head><item><term>Multisensor</term></item><item><term>Land use/cover mapping</term></item><item><term>Radar</term></item><item><term>Sensor fusion</term></item><item><term>Texture</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="1999">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/D765ABBE74BAB9645C1F99C3B13BECE182126755/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:docType><istex:document><converted-article version="4.5.2" docsubtype="fla"><item-info><jid>CEUS</jid><aid>181</aid><ce:pii>S0198-9715(99)00003-4</ce:pii><ce:doi>10.1016/S0198-9715(99)00003-4</ce:doi><ce:copyright year="1999" type="full-transfer">Elsevier Science Ltd</ce:copyright></item-info><head><ce:dochead><ce:textfn>Article</ce:textfn></ce:dochead><ce:title>Multisensor remote sensing data for land use/cover mapping</ce:title><ce:author-group><ce:author><ce:given-name>B</ce:given-name><ce:surname>Haack</ce:surname><ce:cross-ref refid="CORR1">*</ce:cross-ref></ce:author><ce:author><ce:given-name>M</ce:given-name><ce:surname>Bechdol</ce:surname></ce:author><ce:affiliation><ce:textfn>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</ce:textfn></ce:affiliation><ce:correspondence id="CORR1"><ce:label>*</ce:label><ce:text>Corresponding author. Tel.: +1-703-993-1215; fax: +1-703-993-1216; e-mail: bhaack@gmu.edu</ce:text></ce:correspondence></ce:author-group><ce:abstract><ce:section-title>Abstract</ce:section-title><ce:abstract-sec><ce:simple-para>Spaceborne radar data have only recently been consistently available. This project evaluated, independently and in combination, the relative utility of traditional spaceborne optical data from the visible and infrared wavelengths and the more longer wavelength radar. East African landscapes including settlements, natural vegetation, and agriculture were examined as case studies. For three study sites, multisensor data sets were digitally integrated with training and truth information derived from field visits assisted by global positioning systems. For each study site, a variety of information extraction techniques were conducted. The primary methodology was standard image processing spectral signature extraction and application of a statistical decision rule to classify the surface features. The relative accuracy of the classifications were established by comparison to ground truth information. Several primary results were obtained, all of which establish the value of spaceborne radar. For one site, the combination of sensors obtained good mapping accuracies when neither sensor could independently. In other sites, the radar was independently as useful as the optical data. For radar, additional processing manipulations, such as pre- and post-filtering significantly improved classification accuracies. ©</ce:simple-para></ce:abstract-sec></ce:abstract><ce:keywords class="keyword"><ce:section-title>Keywords</ce:section-title><ce:keyword><ce:text>Multisensor</ce:text></ce:keyword><ce:keyword><ce:text>Land use/cover mapping</ce:text></ce:keyword><ce:keyword><ce:text>Radar</ce:text></ce:keyword><ce:keyword><ce:text>Sensor fusion</ce:text></ce:keyword><ce:keyword><ce:text>Texture</ce:text></ce:keyword></ce:keywords></head></converted-article></istex:document></istex:metadataXml><mods version="3.6"><titleInfo><title>Multisensor remote sensing data for land use/cover mapping</title></titleInfo><titleInfo type="alternative" contentType="CDATA"><title>Multisensor remote sensing data for land use/cover mapping</title></titleInfo><name type="personal"><namePart type="given">B</namePart><namePart type="family">Haack</namePart><affiliation>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</affiliation><description>Corresponding author. Tel.: +1-703-993-1215; fax: +1-703-993-1216; e-mail: bhaack@gmu.edu</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">M</namePart><namePart type="family">Bechdol</namePart><affiliation>Department of Geography and Earth Systems, George Mason University, MSN 1E2, Fairfax, VA 22030, USA</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">1999</dateIssued><copyrightDate encoding="w3cdtf">1999</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">Spaceborne radar data have only recently been consistently available. This project evaluated, independently and in combination, the relative utility of traditional spaceborne optical data from the visible and infrared wavelengths and the more longer wavelength radar. East African landscapes including settlements, natural vegetation, and agriculture were examined as case studies. For three study sites, multisensor data sets were digitally integrated with training and truth information derived from field visits assisted by global positioning systems. For each study site, a variety of information extraction techniques were conducted. The primary methodology was standard image processing spectral signature extraction and application of a statistical decision rule to classify the surface features. The relative accuracy of the classifications were established by comparison to ground truth information. Several primary results were obtained, all of which establish the value of spaceborne radar. For one site, the combination of sensors obtained good mapping accuracies when neither sensor could independently. In other sites, the radar was independently as useful as the optical data. For radar, additional processing manipulations, such as pre- and post-filtering significantly improved classification accuracies. ©</abstract><note type="content">Section title: Article</note><note type="content">Fig. 1: Ground photograph of village near Wad Medani, Sudan.</note><note type="content">Fig. 2: Shuttle image radar (SIR)-B image along the Blue Nile in Sudan (approximate scale 1:70,000).</note><note type="content">Fig. 3: Typical agricultural landscape near Singida, Tanzania.</note><note type="content">Fig. 4: Shuttle imaging radar-C, C-band image near Singida, Tanzania (approximate scale 1:100,000).</note><note type="content">Table 1: Spectral signatures for Wad Medani</note><note type="content">Table 2: Contingency table for Wad Medani</note><note type="content">Table 3: Spectral signatures for Singida</note><note type="content">Table 4: Classification accuracies for Singida comparing sensors and sensor combinations</note><note type="content">Table 5: Post-classification filtering results for Singida</note><note type="content">Table 6: Classification results from Tinderet</note><subject><genre>Keywords</genre><topic>Multisensor</topic><topic>Land use/cover mapping</topic><topic>Radar</topic><topic>Sensor fusion</topic><topic>Texture</topic></subject><relatedItem type="host"><titleInfo><title>Computers, Environment and Urban Systems</title></titleInfo><titleInfo type="abbreviated"><title>CEUS</title></titleInfo><genre type="journal">journal</genre><originInfo><dateIssued encoding="w3cdtf">19990101</dateIssued></originInfo><identifier type="ISSN">0198-9715</identifier><identifier type="PII">S0198-9715(00)X0020-8</identifier><part><date>19990101</date><detail type="volume"><number>23</number><caption>vol.</caption></detail><detail type="issue"><number>1</number><caption>no.</caption></detail><extent unit="issue pages"><start>1</start><end>70</end></extent><extent unit="pages"><start>53</start><end>69</end></extent></part></relatedItem><identifier type="istex">D765ABBE74BAB9645C1F99C3B13BECE182126755</identifier><identifier type="DOI">10.1016/S0198-9715(99)00003-4</identifier><identifier type="PII">S0198-9715(99)00003-4</identifier><accessCondition type="use and reproduction" contentType="copyright">©1999 Elsevier Science Ltd</accessCondition><recordInfo><recordContentSource>ELSEVIER</recordContentSource><recordOrigin>Elsevier Science Ltd, ©1999</recordOrigin></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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