{"id":"https://openalex.org/W2122278591","doi":"https://doi.org/10.1109/whispers.2009.5289090","title":"Simplifying Support Vector Machines for Regression analysis of hyperspectral imagery","display_name":"Simplifying Support Vector Machines for Regression analysis of hyperspectral imagery","publication_year":2009,"publication_date":"2009-08-01","ids":{"openalex":"https://openalex.org/W2122278591","doi":"https://doi.org/10.1109/whispers.2009.5289090","mag":"2122278591"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2009.5289090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2009.5289090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5082912564","display_name":"A. Rabe","orcid":"https://orcid.org/0009-0003-9026-1166"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"A. Rabe","raw_affiliation_strings":["Geomatics Laboratory, Humboldt-Universitaet zu Berlin, Berlin, Germany","Humboldt-Universit\u00e4t zu Berlin, Geomatics Lab, Unter den Linden 6, 10099, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Geomatics Laboratory, Humboldt-Universitaet zu Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I39343248"]},{"raw_affiliation_string":"Humboldt-Universit\u00e4t zu Berlin, Geomatics Lab, Unter den Linden 6, 10099, Germany","institution_ids":["https://openalex.org/I39343248"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015469539","display_name":"Sebastian van der Linden","orcid":"https://orcid.org/0000-0001-6576-8377"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"S. van der Linden","raw_affiliation_strings":["Geomatics Laboratory, Humboldt-Universitaet zu Berlin, Berlin, Germany","Humboldt-Universit\u00e4t zu Berlin, Geomatics Lab, Unter den Linden 6, 10099, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Geomatics Laboratory, Humboldt-Universitaet zu Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I39343248"]},{"raw_affiliation_string":"Humboldt-Universit\u00e4t zu Berlin, Geomatics Lab, Unter den Linden 6, 10099, Germany","institution_ids":["https://openalex.org/I39343248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041171844","display_name":"Patrick Hostert","orcid":"https://orcid.org/0000-0002-5730-5484"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"P. Hostert","raw_affiliation_strings":["Geomatics Laboratory, Humboldt-Universitaet zu Berlin, Berlin, Germany","Humboldt-Universit\u00e4t zu Berlin, Geomatics Lab, Unter den Linden 6, 10099, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Geomatics Laboratory, Humboldt-Universitaet zu Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I39343248"]},{"raw_affiliation_string":"Humboldt-Universit\u00e4t zu Berlin, Geomatics Lab, Unter den Linden 6, 10099, Germany","institution_ids":["https://openalex.org/I39343248"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39343248"],"apc_list":null,"apc_paid":null,"fwci":5.9459,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.94734759,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9986000061035156,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9983000159263611,"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":0.9947999715805054,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9574427008628845},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8561021685600281},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5816403031349182},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5768534541130066},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5122389197349548},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.5015580654144287},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45835816860198975},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.42255163192749023},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3911835551261902},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3294488191604614},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31093505024909973},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24733972549438477},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20527395606040955},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06514421105384827}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9574427008628845},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8561021685600281},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5816403031349182},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5768534541130066},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5122389197349548},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.5015580654144287},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45835816860198975},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.42255163192749023},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3911835551261902},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3294488191604614},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31093505024909973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24733972549438477},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20527395606040955},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06514421105384827},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers.2009.5289090","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2009.5289090","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335584","display_name":"Helmholtz-Zentrum Potsdam - Deutsches GeoForschungsZentrum GFZ","ror":"https://ror.org/04z8jg394"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1676317136","https://openalex.org/W2011869541","https://openalex.org/W2046547379","https://openalex.org/W2052256290","https://openalex.org/W2115539456","https://openalex.org/W2130765257","https://openalex.org/W2139211176","https://openalex.org/W2139348552","https://openalex.org/W2153635508","https://openalex.org/W2156419436","https://openalex.org/W2156909104","https://openalex.org/W3120421331","https://openalex.org/W4230674625","https://openalex.org/W6637055845"],"related_works":["https://openalex.org/W31220157","https://openalex.org/W2312753042","https://openalex.org/W4289356671","https://openalex.org/W2389155397","https://openalex.org/W2165884543","https://openalex.org/W3186837933","https://openalex.org/W2368989808","https://openalex.org/W2034959125","https://openalex.org/W2355687852","https://openalex.org/W2621086889"],"abstract_inverted_index":{"Support":[0],"Vector":[1],"Machines":[2],"for":[3,37,56,81,110],"Regression":[4],"(SVR)":[5],"proved":[6],"to":[7,19,45,107],"perform":[8],"well.":[9],"However,":[10],"they":[11],"are":[12],"not":[13],"preferred":[14],"in":[15,100,104],"image":[16],"analysis":[17],"due":[18],"a":[20,35,46,118],"high":[21,79],"number":[22,101],"of":[23,49,102,113,121],"needed":[24],"support":[25],"vectors":[26],"(SV)":[27],"and":[28,64,88],"consequently":[29],"long":[30],"processing":[31],"times.":[32],"We":[33,53],"present":[34],"method":[36],"simplifying":[38,92],"the":[39,93,105],"original":[40,94],"SVR":[41,77],"regression":[42,58],"function":[43],"up":[44],"user-specified":[47],"degree":[48],"accepted":[50],"performance":[51],"decrease.":[52],"show":[54],"results":[55],"two":[57],"problems:":[59],"modelling":[60,82],"leaf":[61],"area":[62],"index":[63],"dry":[65],"vegetation":[66],"mixing":[67],"fraction":[68],"using":[69],"simulated":[70],"hyperspectral":[71,86],"EnMAP":[72,123],"data.":[73],"In":[74],"both":[75],"cases,":[76],"demonstrate":[78],"potential":[80],"complex":[83],"dependencies":[84],"between":[85],"reflectance":[87],"quantitative":[89],"targets.":[90],"By":[91],"SVR,":[95],"we":[96],"observed":[97],"reduction":[98],"rates":[99],"SV":[103],"86%":[106],"95%":[108],"range":[109],"acceptable":[111],"degrees":[112],"approximation":[114],"quality.":[115],"This":[116],"enables":[117],"fast":[119],"mapping":[120],"complete":[122],"scenes.":[124]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}