{"id":"https://openalex.org/W2111207708","doi":"https://doi.org/10.1109/igarss.2007.4423229","title":"Influence of training sampling protocol and of feature space optimization methods on supervised classification results","display_name":"Influence of training sampling protocol and of feature space optimization methods on supervised classification results","publication_year":2007,"publication_date":"2007-01-01","ids":{"openalex":"https://openalex.org/W2111207708","doi":"https://doi.org/10.1109/igarss.2007.4423229","mag":"2111207708"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2007.4423229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4423229","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"preprint","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/A5070708598","display_name":"Sylvie Durrieu","orcid":"https://orcid.org/0000-0001-6145-9614"},"institutions":[{"id":"https://openalex.org/I131077856","display_name":"Centre de Coop\u00e9ration Internationale en Recherche Agronomique pour le D\u00e9veloppement","ror":"https://ror.org/05kpkpg04","country_code":"FR","type":"facility","lineage":["https://openalex.org/I131077856"]},{"id":"https://openalex.org/I4387153996","display_name":"Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale","ror":"https://ror.org/0458hw939","country_code":null,"type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I131077856","https://openalex.org/I22248866","https://openalex.org/I277688954","https://openalex.org/I4210088668","https://openalex.org/I4387153996"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"S. Durrieu","raw_affiliation_strings":["UMR TETIS Cemagref-Cirad-ENGREF Cemagref, Maison de la T\u00e9l\u00e9d\u00e9tection en Languedoc-Roussillon, Montpellier, France","Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UMR TETIS Cemagref-Cirad-ENGREF Cemagref, Maison de la T\u00e9l\u00e9d\u00e9tection en Languedoc-Roussillon, Montpellier, France","institution_ids":["https://openalex.org/I131077856"]},{"raw_affiliation_string":"Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale","institution_ids":["https://openalex.org/I4387153996"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051777615","display_name":"T. Tormos","orcid":"https://orcid.org/0009-0005-3477-7365"},"institutions":[{"id":"https://openalex.org/I131077856","display_name":"Centre de Coop\u00e9ration Internationale en Recherche Agronomique pour le D\u00e9veloppement","ror":"https://ror.org/05kpkpg04","country_code":"FR","type":"facility","lineage":["https://openalex.org/I131077856"]},{"id":"https://openalex.org/I4387153996","display_name":"Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale","ror":"https://ror.org/0458hw939","country_code":null,"type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I131077856","https://openalex.org/I22248866","https://openalex.org/I277688954","https://openalex.org/I4210088668","https://openalex.org/I4387153996"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"T. Tormos","raw_affiliation_strings":["UMR TETIS Cemagref-Cirad-ENGREF Cemagref, Maison de la T\u00e9l\u00e9d\u00e9tection en Languedoc-Roussillon, Montpellier, France","Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UMR TETIS Cemagref-Cirad-ENGREF Cemagref, Maison de la T\u00e9l\u00e9d\u00e9tection en Languedoc-Roussillon, Montpellier, France","institution_ids":["https://openalex.org/I131077856"]},{"raw_affiliation_string":"Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale","institution_ids":["https://openalex.org/I4387153996"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079744860","display_name":"Pascal Kosuth","orcid":null},"institutions":[{"id":"https://openalex.org/I131077856","display_name":"Centre de Coop\u00e9ration Internationale en Recherche Agronomique pour le D\u00e9veloppement","ror":"https://ror.org/05kpkpg04","country_code":"FR","type":"facility","lineage":["https://openalex.org/I131077856"]},{"id":"https://openalex.org/I4387153996","display_name":"Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale","ror":"https://ror.org/0458hw939","country_code":null,"type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I131077856","https://openalex.org/I22248866","https://openalex.org/I277688954","https://openalex.org/I4210088668","https://openalex.org/I4387153996"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"P. Kosuth","raw_affiliation_strings":["UMR TETIS Cemagref-Cirad-ENGREF Cemagref, Maison de la T\u00e9l\u00e9d\u00e9tection en Languedoc-Roussillon, Montpellier, France","Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UMR TETIS Cemagref-Cirad-ENGREF Cemagref, Maison de la T\u00e9l\u00e9d\u00e9tection en Languedoc-Roussillon, Montpellier, France","institution_ids":["https://openalex.org/I131077856"]},{"raw_affiliation_string":"Territoires, Environnement, T\u00e9l\u00e9d\u00e9tection et Information Spatiale","institution_ids":["https://openalex.org/I4387153996"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046560988","display_name":"C. Golden","orcid":null},"institutions":[{"id":"https://openalex.org/I4210112109","display_name":"Gestion de l'Eau, Acteurs, Usages","ror":"https://ror.org/020g0rw41","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I131077856","https://openalex.org/I1327553481","https://openalex.org/I154202486","https://openalex.org/I19894307","https://openalex.org/I22248866","https://openalex.org/I24906876","https://openalex.org/I277688954","https://openalex.org/I2799535048","https://openalex.org/I2802818602","https://openalex.org/I4210088668","https://openalex.org/I4210088668","https://openalex.org/I4210090127","https://openalex.org/I4210112109","https://openalex.org/I4210113730","https://openalex.org/I4210117091","https://openalex.org/I4210131494","https://openalex.org/I4210158893","https://openalex.org/I4210166444","https://openalex.org/I4399657933","https://openalex.org/I4405257220"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"C. Golden","raw_affiliation_strings":["UMR G-EAU Cemagref, Montpellier, France","Gestion de l'Eau, Acteurs, Usages"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UMR G-EAU Cemagref, Montpellier, France","institution_ids":["https://openalex.org/I4210112109"]},{"raw_affiliation_string":"Gestion de l'Eau, Acteurs, Usages","institution_ids":["https://openalex.org/I4210112109"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070708598"],"corresponding_institution_ids":["https://openalex.org/I131077856","https://openalex.org/I4387153996"],"apc_list":null,"apc_paid":null,"fwci":0.5926,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75044563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"2030","last_page":"2033"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991000294685364,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7649619579315186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6845455765724182},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6798738241195679},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6718403100967407},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6197600960731506},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5564725399017334},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5186780691146851},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5126306414604187},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4735756814479828},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.46962621808052063},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4488506615161896},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4399663507938385},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.42037999629974365},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.24170783162117004},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22421464323997498},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07137107849121094},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.06231072545051575}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7649619579315186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6845455765724182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6798738241195679},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6718403100967407},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6197600960731506},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5564725399017334},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5186780691146851},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5126306414604187},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4735756814479828},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.46962621808052063},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4488506615161896},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4399663507938385},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.42037999629974365},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.24170783162117004},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22421464323997498},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07137107849121094},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.06231072545051575},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2007.4423229","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2007.4423229","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2007 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-02590584v1","is_oa":false,"landing_page_url":"https://hal.inrae.fr/hal-02590584","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Geoscience and Remote Sensing Symposium (IGARSS), Jul 2007, Barcelona, Spain. pp.2030-2033, ⟨10.1109/IGARSS.2007.4423229⟩","raw_type":"Conference papers"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W626287889","https://openalex.org/W1480376833","https://openalex.org/W1554944419","https://openalex.org/W2114068285","https://openalex.org/W2114828048","https://openalex.org/W2143454753","https://openalex.org/W3147109636","https://openalex.org/W6628633436"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2510961579","https://openalex.org/W156213964","https://openalex.org/W2050960118"],"abstract_inverted_index":{"Land":[0],"cover":[1],"map":[2],"are":[3],"produced":[4],"from":[5],"remote":[6],"sensing":[7],"images":[8],"using":[9],"per-pixel":[10],"or,":[11],"more":[12],"recently,":[13],"object-based":[14],"classifications.":[15],"Various":[16],"trainable":[17],"classifiers":[18,79],"and":[19,35,76],"feature":[20,90,107],"space":[21,91],"optimization":[22,92],"methods":[23,75],"can":[24],"be":[25],"used":[26],"to":[27,40,45,98,120],"that":[28,96],"aim.":[29],"The":[30,94],"choice":[31],"of":[32,57,69,86,116],"both":[33],"training":[34,112],"control":[36],"samples":[37],"is":[38,52],"liable":[39],"influence":[41],"the":[42,46,55,66,99,122],"results":[43,101],"according":[44],"classification":[47,83],"method":[48],"employed":[49],"but":[50],"little":[51],"known":[53],"about":[54],"way":[56],"choosing":[58],"an":[59],"appropriate":[60],"sampling":[61,74],"set.":[62],"This":[63],"makes":[64],"thus":[65],"focal":[67],"point":[68],"our":[70],"study.":[71],"Using":[72],"three":[73],"four":[77],"discriminative":[78],"we":[80],"compared":[81],"various":[82],"procedures,":[84],"some":[85],"them":[87],"including":[88],"a":[89],"step.":[93],"one":[95],"led":[97],"best":[100,123],"was":[102],"LDA":[103],"preceded":[104],"by":[105],"its":[106],"pre-selection":[108],"algorithm.":[109],"Generally,":[110],"for":[111],"samples,":[113],"class":[114],"numbers":[115],"40":[117],"were":[118],"necessary":[119],"get":[121],"results.":[124]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-05-07T13:39:58.223016","created_date":"2016-06-24T00:00:00"}