{"id":"https://openalex.org/W2161234346","doi":"https://doi.org/10.1109/igarss.2008.4779348","title":"An Evaluation of Ecotope Classification using Superresolution Images Derived from Chris/Proba Data","display_name":"An Evaluation of Ecotope Classification using Superresolution Images Derived from Chris/Proba Data","publication_year":2008,"publication_date":"2008-07-01","ids":{"openalex":"https://openalex.org/W2161234346","doi":"https://doi.org/10.1109/igarss.2008.4779348","mag":"2161234346"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2008.4779348","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2008.4779348","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047379149","display_name":"Jonathan Cheung-Wai Chan","orcid":"https://orcid.org/0000-0002-3741-1124"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Jonathan Cheung-Wai Chan","raw_affiliation_strings":["Department of Geography, Vrije Universiteit Brussel, Belgium, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, Vrije Universiteit Brussel, Belgium, Belgium","institution_ids":["https://openalex.org/I13469542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101198662","display_name":"Jianglin Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Jianglin Ma","raw_affiliation_strings":["Department of Geography, Vrije Universiteit Brussel, Belgium, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, Vrije Universiteit Brussel, Belgium, Belgium","institution_ids":["https://openalex.org/I13469542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000964900","display_name":"Pieter Kempeneers","orcid":"https://orcid.org/0000-0002-4317-4807"},"institutions":[{"id":"https://openalex.org/I68522396","display_name":"Flemish Institute for Technological Research","ror":"https://ror.org/04gq0w522","country_code":"BE","type":"facility","lineage":["https://openalex.org/I68522396"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Pieter Kempeneers","raw_affiliation_strings":["Centre of Expertise in Remote Sensing and Atmospheric Processes (TAP), Flemish Institute for Technological Research (VITO), Belgium, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Centre of Expertise in Remote Sensing and Atmospheric Processes (TAP), Flemish Institute for Technological Research (VITO), Belgium, Belgium","institution_ids":["https://openalex.org/I68522396"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091439710","display_name":"Frank Canters","orcid":"https://orcid.org/0000-0002-5850-9577"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Frank Canters","raw_affiliation_strings":["Department of Geography, Vrije Universiteit Brussel, Belgium, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, Vrije Universiteit Brussel, Belgium, Belgium","institution_ids":["https://openalex.org/I13469542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053461734","display_name":"Jeroen Vanden Borre","orcid":"https://orcid.org/0000-0002-0153-7243"},"institutions":[{"id":"https://openalex.org/I202500258","display_name":"Research Institute for Nature and Forest","ror":"https://ror.org/00j54wy13","country_code":"BE","type":"facility","lineage":["https://openalex.org/I202500258"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Jeroen Vanden Borre","raw_affiliation_strings":["Research Institute for Nature and Forest (INBO), Belgium, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute for Nature and Forest (INBO), Belgium, Belgium","institution_ids":["https://openalex.org/I202500258"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063495031","display_name":"Desir\u00e9 Paelinckx","orcid":"https://orcid.org/0000-0002-2835-4455"},"institutions":[{"id":"https://openalex.org/I202500258","display_name":"Research Institute for Nature and Forest","ror":"https://ror.org/00j54wy13","country_code":"BE","type":"facility","lineage":["https://openalex.org/I202500258"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Desire Paelinckx","raw_affiliation_strings":["Research Institute for Nature and Forest (INBO), Belgium, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research Institute for Nature and Forest (INBO), Belgium, Belgium","institution_ids":["https://openalex.org/I202500258"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.485,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.90504063,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"III ","last_page":" 322"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9818000197410583,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9815999865531921,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6538231372833252},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6077090501785278},{"id":"https://openalex.org/keywords/ecotope","display_name":"Ecotope","score":0.5974668264389038},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5690901875495911},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5536881685256958},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5053680539131165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4663257896900177},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.42841485142707825},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3564523458480835},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23408228158950806},{"id":"https://openalex.org/keywords/landscape-ecology","display_name":"Landscape ecology","score":0.0840480625629425}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6538231372833252},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6077090501785278},{"id":"https://openalex.org/C37884843","wikidata":"https://www.wikidata.org/wiki/Q296185","display_name":"Ecotope","level":4,"score":0.5974668264389038},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5690901875495911},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5536881685256958},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5053680539131165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4663257896900177},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.42841485142707825},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3564523458480835},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23408228158950806},{"id":"https://openalex.org/C87690585","wikidata":"https://www.wikidata.org/wiki/Q738011","display_name":"Landscape ecology","level":3,"score":0.0840480625629425},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C185933670","wikidata":"https://www.wikidata.org/wiki/Q52105","display_name":"Habitat","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2008.4779348","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2008.4779348","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"mag:3128171348","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1621228199","https://openalex.org/W1829506271","https://openalex.org/W1971552725","https://openalex.org/W1991259147","https://openalex.org/W1999821839","https://openalex.org/W2067042811","https://openalex.org/W2096455981","https://openalex.org/W2133506218","https://openalex.org/W2145862305","https://openalex.org/W2165939075","https://openalex.org/W2167510883","https://openalex.org/W2911964244"],"related_works":["https://openalex.org/W4251728012","https://openalex.org/W2736200820","https://openalex.org/W2138534875","https://openalex.org/W4365804719","https://openalex.org/W2055072819","https://openalex.org/W2784452928","https://openalex.org/W1496347422","https://openalex.org/W3004000015","https://openalex.org/W2559771220","https://openalex.org/W4387300017"],"abstract_inverted_index":{"This":[0,88],"paper":[1],"discusses":[2],"the":[3,19,32,55,58,64,69,109,118,151,163,174],"application":[4],"of":[5,22,117,153,187],"superresolution":[6],"(SR)":[7],"image":[8,62,120],"reconstruction":[9],"on":[10,173],"multi-angle":[11,188],"Chris/Proba":[12,23,166],"images.":[13],"The":[14,40,114],"goal":[15],"is":[16,47,91,121,148],"to":[17,34,107,126],"increase":[18,161],"spatial":[20,115,185],"resolution":[21,61,66,112,116],"images,":[24,67,167,189],"with":[25,68,162,169],"18":[26,154],"bands":[27],"from":[28,123],"0.4-1.0":[29],"mum":[30],"in":[31,93,97,140],"hope":[33],"obtain":[35],"a":[36,72,75,85,159,170],"better":[37],"ecotope":[38],"classification.":[39],"SR":[41,164,181],"approach":[42,90],"chosen":[43],"for":[44,150],"this":[45],"study":[46],"Total":[48,130],"Variation,":[49],"an":[50,79],"iterative":[51],"method":[52],"which":[53],"models":[54],"relationship":[56],"between":[57],"desired":[59,110],"high":[60,111],"and":[63,82,84,95,190],"low":[65],"following":[70],"components:":[71],"subsampling":[73],"factor,":[74],"point":[76],"spread":[77],"function,":[78],"estimated":[80],"rotation":[81],"shift,":[83],"regularization":[86,89],"term.":[87],"fast":[92],"implementation":[94],"flexible":[96],"handling":[98],"noise.":[99],"Efficient":[100],"gradient":[101],"descent":[102],"methods":[103,182],"can":[104,183],"be":[105],"used":[106,149],"find":[108],"image.":[113],"original":[119,175],"improved":[122],"25":[124],"m":[125,128],"12":[127],"using":[129],"Variation.":[131],"Subjective":[132],"assessment":[133],"through":[134],"visual":[135],"interpretation":[136],"shows":[137,158],"substantial":[138],"improvement":[139],"detail.":[141],"A":[142],"tree-based":[143],"ensemble":[144],"classifier":[145],"Random":[146],"Forest":[147],"classification":[152,171,192],"ecotopes.":[155],"Overall":[156],"accuracy":[157],"10%":[160],"derived":[165],"compared":[168],"based":[172],"imagery.":[176],"Our":[177],"results":[178],"demonstrate":[179],"that":[180],"improve":[184],"detail":[186],"subsequently":[191],"accuracy.":[193]},"counts_by_year":[{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}