A remote sensing based vegetation classification logic for global land cover analysis
This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field...
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| Veröffentlicht in: | Remote Sensing of Environment 1995, Vol.51 (1), p.39-48 |
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| container_end_page | 48 |
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| container_title | Remote Sensing of Environment |
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| creator | Running, Steven W. Loveland, Thomas R. Pierce, Lars L. Nemani, R.R. Hunt, E.R. |
| description | This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation, 2) the structural characteristics are remotely sensible so that repeatable and efficient global reclassifications of existing vegetation will be possible, and 3) the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km AVHRR normalized difference vegetation index database. Procedures for solving critical remote sensing problems needed to implement the classification are discussed. Also, some inferences from this classification to advanced vegetation biophysical variables such as specific leaf area and photosynthetic capacity useful to global biogeochemical modeling are suggested. |
| doi_str_mv | 10.1016/0034-4257(94)00063-S |
| format | Article |
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Techniques ; GLOBAL ASPECTS ; GROUND COVER ; MATHEMATICAL MODELS ; PHOTOSYNTHESIS ; PLANTAS DE COBERTURA ; PLANTE DE COUVERTURE ; PLANTS ; REMOTE SENSING ; TELEDETECCION ; TELEDETECTION ; Teledetection and vegetation maps ; TERRESTRIAL ECOSYSTEMS ; USA ; VEGETACION ; VEGETATION ; VEGETATION TYPES</subject><ispartof>Remote Sensing of Environment, 1995, Vol.51 (1), p.39-48</ispartof><rights>1995</rights><rights>1995 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c490t-eec8393fb4943d18ccfbe9362696836b0bcfedefbe38bf5c5fbabb981e4ae5823</citedby><cites>FETCH-LOGICAL-c490t-eec8393fb4943d18ccfbe9362696836b0bcfedefbe38bf5c5fbabb981e4ae5823</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/0034-4257(94)00063-S$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>309,310,314,777,781,786,787,882,3537,4010,4036,4037,23911,23912,25121,27904,27905,27906,45976</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=3460854$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.osti.gov/biblio/31834$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Running, Steven W.</creatorcontrib><creatorcontrib>Loveland, Thomas R.</creatorcontrib><creatorcontrib>Pierce, Lars L.</creatorcontrib><creatorcontrib>Nemani, R.R.</creatorcontrib><creatorcontrib>Hunt, E.R.</creatorcontrib><title>A remote sensing based vegetation classification logic for global land cover analysis</title><title>Remote Sensing of Environment</title><description>This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation, 2) the structural characteristics are remotely sensible so that repeatable and efficient global reclassifications of existing vegetation will be possible, and 3) the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km AVHRR normalized difference vegetation index database. Procedures for solving critical remote sensing problems needed to implement the classification are discussed. Also, some inferences from this classification to advanced vegetation biophysical variables such as specific leaf area and photosynthetic capacity useful to global biogeochemical modeling are suggested.</description><subject>Animal, plant and microbial ecology</subject><subject>Biological and medical sciences</subject><subject>CLASIFICACION</subject><subject>CLASSIFICATION</subject><subject>CLIMATIC CHANGE</subject><subject>COVER PLANTS</subject><subject>ENVIRONMENTAL SCIENCES</subject><subject>ETATS UNIS</subject><subject>EUA</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General aspects. Techniques</subject><subject>GLOBAL ASPECTS</subject><subject>GROUND COVER</subject><subject>MATHEMATICAL MODELS</subject><subject>PHOTOSYNTHESIS</subject><subject>PLANTAS DE COBERTURA</subject><subject>PLANTE DE COUVERTURE</subject><subject>PLANTS</subject><subject>REMOTE SENSING</subject><subject>TELEDETECCION</subject><subject>TELEDETECTION</subject><subject>Teledetection and vegetation maps</subject><subject>TERRESTRIAL ECOSYSTEMS</subject><subject>USA</subject><subject>VEGETACION</subject><subject>VEGETATION</subject><subject>VEGETATION TYPES</subject><issn>0034-4257</issn><issn>1879-0704</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1995</creationdate><recordtype>article</recordtype><recordid>eNqFkU2P1DAMhisEEsPCH0AcckAIDoVk8tHkgrRa8SWtxGGYc5S4TgnqNEvcHWn_PS1d7RFOlu3H1uvXTfNK8PeCC_OBc6latdfdW6fecc6NbA-Pmp2wnWt5x9XjZveAPG2eEf3iXGjbiV1zvGQVT2VGRjhRngYWA2HPzjjgHOZcJgZjIMopw5aOZcjAUqlsGEsMIxvD1DMoZ6wsTGG8o0zPmycpjIQv7uNFc_z86cfV1_b6-5dvV5fXLSjH5xYRrHQyReWU7IUFSBGdNHvjjJUm8ggJe1yK0sakQacYYnRWoAqo7V5eNGzbW2jOniDPCD-hTBPC7KWwUi3Imw25qeX3LdLsT5kAx0U1llvye-1M13H9X1CYTihp-AKqDYRaiComf1PzKdQ7L7hf_-FXs_1qtnfK__2HPyxjr-_3B4IwphomyPQwK5XhVq96X25YCsWHoS7I8eC01J3qlubHrYmLqeeMdb0ZJ8A-1_XkvuR_i_gDV5eoDA</recordid><startdate>1995</startdate><enddate>1995</enddate><creator>Running, Steven W.</creator><creator>Loveland, Thomas R.</creator><creator>Pierce, Lars L.</creator><creator>Nemani, R.R.</creator><creator>Hunt, E.R.</creator><general>Elsevier Inc</general><general>Elsevier Science</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>C1K</scope><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope><scope>OTOTI</scope></search><sort><creationdate>1995</creationdate><title>A remote sensing based vegetation classification logic for global land cover analysis</title><author>Running, Steven W. ; Loveland, Thomas R. ; Pierce, Lars L. ; Nemani, R.R. ; Hunt, E.R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c490t-eec8393fb4943d18ccfbe9362696836b0bcfedefbe38bf5c5fbabb981e4ae5823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1995</creationdate><topic>Animal, plant and microbial ecology</topic><topic>Biological and medical sciences</topic><topic>CLASIFICACION</topic><topic>CLASSIFICATION</topic><topic>CLIMATIC CHANGE</topic><topic>COVER PLANTS</topic><topic>ENVIRONMENTAL SCIENCES</topic><topic>ETATS UNIS</topic><topic>EUA</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>General aspects. Techniques</topic><topic>GLOBAL ASPECTS</topic><topic>GROUND COVER</topic><topic>MATHEMATICAL MODELS</topic><topic>PHOTOSYNTHESIS</topic><topic>PLANTAS DE COBERTURA</topic><topic>PLANTE DE COUVERTURE</topic><topic>PLANTS</topic><topic>REMOTE SENSING</topic><topic>TELEDETECCION</topic><topic>TELEDETECTION</topic><topic>Teledetection and vegetation maps</topic><topic>TERRESTRIAL ECOSYSTEMS</topic><topic>USA</topic><topic>VEGETACION</topic><topic>VEGETATION</topic><topic>VEGETATION TYPES</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Running, Steven W.</creatorcontrib><creatorcontrib>Loveland, Thomas R.</creatorcontrib><creatorcontrib>Pierce, Lars L.</creatorcontrib><creatorcontrib>Nemani, R.R.</creatorcontrib><creatorcontrib>Hunt, E.R.</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>OSTI.GOV</collection><jtitle>Remote Sensing of Environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Running, Steven W.</au><au>Loveland, Thomas R.</au><au>Pierce, Lars L.</au><au>Nemani, R.R.</au><au>Hunt, E.R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A remote sensing based vegetation classification logic for global land cover analysis</atitle><jtitle>Remote Sensing of Environment</jtitle><date>1995</date><risdate>1995</risdate><volume>51</volume><issue>1</issue><spage>39</spage><epage>48</epage><pages>39-48</pages><issn>0034-4257</issn><eissn>1879-0704</eissn><coden>RSEEA7</coden><abstract>This article proposes a simple new logic for classifying global vegetation. The critical features of this classification are that 1) it is based on simple, observable, unambiguous characteristics of vegetation structure that are important to ecosystem biogeochemistry and can be measured in the field for validation, 2) the structural characteristics are remotely sensible so that repeatable and efficient global reclassifications of existing vegetation will be possible, and 3) the defined vegetation classes directly translate into the biophysical parameters of interest by global climate and biogeochemical models. A first test of this logic for the continental United States is presented based on an existing 1 km AVHRR normalized difference vegetation index database. Procedures for solving critical remote sensing problems needed to implement the classification are discussed. Also, some inferences from this classification to advanced vegetation biophysical variables such as specific leaf area and photosynthetic capacity useful to global biogeochemical modeling are suggested.</abstract><cop>New York, NY</cop><pub>Elsevier Inc</pub><doi>10.1016/0034-4257(94)00063-S</doi><tpages>10</tpages></addata></record> |
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| ispartof | Remote Sensing of Environment, 1995, Vol.51 (1), p.39-48 |
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| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Animal, plant and microbial ecology Biological and medical sciences CLASIFICACION CLASSIFICATION CLIMATIC CHANGE COVER PLANTS ENVIRONMENTAL SCIENCES ETATS UNIS EUA Fundamental and applied biological sciences. Psychology General aspects. Techniques GLOBAL ASPECTS GROUND COVER MATHEMATICAL MODELS PHOTOSYNTHESIS PLANTAS DE COBERTURA PLANTE DE COUVERTURE PLANTS REMOTE SENSING TELEDETECCION TELEDETECTION Teledetection and vegetation maps TERRESTRIAL ECOSYSTEMS USA VEGETACION VEGETATION VEGETATION TYPES |
| title | A remote sensing based vegetation classification logic for global land cover analysis |
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