{"id":"https://openalex.org/W2169119136","doi":"https://doi.org/10.1109/lgrs.2011.2141651","title":"Combining Hyperspectral Data Processing Chains for Robust Mapping Using Hierarchical Trees and Class Memberships","display_name":"Combining Hyperspectral Data Processing Chains for Robust Mapping Using Hierarchical Trees and Class Memberships","publication_year":2011,"publication_date":"2011-06-07","ids":{"openalex":"https://openalex.org/W2169119136","doi":"https://doi.org/10.1109/lgrs.2011.2141651","mag":"2169119136"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2011.2141651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2011.2141651","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5065880285","display_name":"K\u00e1roly Livius Bakos","orcid":null},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Karoly Livius Bakos","raw_affiliation_strings":["Dipartimento di Elettronica, Universit\u00e0 di Pavia, Pavia, Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Elettronica, Universit\u00e0 di Pavia, Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006623289","display_name":"Paolo Gamba","orcid":"https://orcid.org/0000-0002-9576-6337"},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Gamba","raw_affiliation_strings":["Dipartimento di Elettronica, Universit\u00e0 di Pavia, Pavia, Italy"],"affiliations":[{"raw_affiliation_string":"Dipartimento di Elettronica, Universit\u00e0 di Pavia, Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5065880285"],"corresponding_institution_ids":["https://openalex.org/I25217355"],"apc_list":null,"apc_paid":null,"fwci":1.0085,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81903414,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"8","issue":"5","first_page":"968","last_page":"972"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9800000190734863,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9793000221252441,"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/computer-science","display_name":"Computer science","score":0.7332630753517151},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7302258014678955},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6913642883300781},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6695119142532349},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6220064759254456},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5235830545425415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4825703203678131},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.47859832644462585},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.4186442196369171},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38721731305122375},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1989922821521759},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07920017838478088}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7332630753517151},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7302258014678955},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6913642883300781},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6695119142532349},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6220064759254456},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5235830545425415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4825703203678131},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.47859832644462585},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.4186442196369171},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38721731305122375},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1989922821521759},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07920017838478088},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2011.2141651","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2011.2141651","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1606445564","https://openalex.org/W2046245205","https://openalex.org/W2067562626","https://openalex.org/W2083825310","https://openalex.org/W2084413241","https://openalex.org/W2086762254","https://openalex.org/W2113898416","https://openalex.org/W2124073857","https://openalex.org/W2127038040","https://openalex.org/W2127881472","https://openalex.org/W2127962925","https://openalex.org/W2131864940","https://openalex.org/W2132941001","https://openalex.org/W2136625467","https://openalex.org/W2137894640","https://openalex.org/W2140095548","https://openalex.org/W2154231986","https://openalex.org/W2156116978","https://openalex.org/W2162480849","https://openalex.org/W2168842575","https://openalex.org/W2171896159","https://openalex.org/W2294798173","https://openalex.org/W4214564766"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4312814274","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"we":[3,33],"introduce":[4],"a":[5,23,35,51,56],"methodology":[6,58],"to":[7,43,96,108],"combine":[8],"decisions":[9],"of":[10,92],"multiple":[11],"hyperspectral":[12],"data":[13,28],"processing":[14,48],"chains":[15,49],"using":[16],"an":[17],"already":[18],"tested":[19],"preselection":[20],"step":[21],"and":[22,99],"novel":[24,83],"algorithm":[25,42],"for":[26,50,59,81,89],"the":[27,45,67,82],"labeling":[29],"procedure.":[30],"More":[31],"specifically,":[32],"exploit":[34],"hierarchical":[36],"binary":[37],"decision":[38,60],"tree":[39],"(HBDT)":[40],"optimization":[41],"select":[44],"most":[46],"suitable":[47],"given":[52],"mapping":[53,91],"problem.":[54],"Then,":[55],"new":[57],"fusion":[61],"is":[62],"introduced,":[63],"based":[64],"on":[65],"weighting":[66],"class":[68],"probability":[69],"membership":[70],"values.":[71],"Experimental":[72],"results":[73],"in":[74],"two":[75],"test":[76],"areas":[77],"show":[78],"great":[79],"potentials":[80],"procedure,":[84],"identified":[85],"as":[86],"particularly":[87],"useful":[88],"generic":[90],"complex":[93],"environments":[94],"due":[95],"its":[97],"flexibility":[98],"robustness.":[100],"Moreover,":[101],"accuracy":[102],"values":[103],"are":[104],"improved":[105],"with":[106],"respect":[107],"those":[109],"obtained":[110],"by":[111],"HBDT":[112],"alone.":[113]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}