{"id":"https://openalex.org/W1986509584","doi":"https://doi.org/10.1109/whispers.2010.5594842","title":"Quantitative detection of sediment dust analog over green canopy using airborne hyperspectral imagery","display_name":"Quantitative detection of sediment dust analog over green canopy using airborne hyperspectral imagery","publication_year":2010,"publication_date":"2010-06-01","ids":{"openalex":"https://openalex.org/W1986509584","doi":"https://doi.org/10.1109/whispers.2010.5594842","mag":"1986509584"},"language":"en","primary_location":{"id":"doi:10.1109/whispers.2010.5594842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2010.5594842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","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/A5050831226","display_name":"Anna Brook","orcid":"https://orcid.org/0000-0002-3205-6581"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Anna Brook","raw_affiliation_strings":["Remote Sensing Laboratory, Tel-Aviv University, Israel","[Remote Sensing Laboratory, Tel-Aviv University, Israel]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Remote Sensing Laboratory, Tel-Aviv University, Israel","institution_ids":["https://openalex.org/I16391192"]},{"raw_affiliation_string":"[Remote Sensing Laboratory, Tel-Aviv University, Israel]","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111392166","display_name":"Eyal Ben\u2010Dor","orcid":null},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Eyal Ben-Dor","raw_affiliation_strings":["Remote Sensing Laboratory, Tel-Aviv University, Israel","[Remote Sensing Laboratory, Tel-Aviv University, Israel]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Remote Sensing Laboratory, Tel-Aviv University, Israel","institution_ids":["https://openalex.org/I16391192"]},{"raw_affiliation_string":"[Remote Sensing Laboratory, Tel-Aviv University, Israel]","institution_ids":["https://openalex.org/I16391192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.12270804,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9993000030517578,"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":0.9933000206947327,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9141544699668884},{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.8634676933288574},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6302505731582642},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5718466639518738},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.496947318315506},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.47350484132766724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.448092520236969},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.42932960391044617},{"id":"https://openalex.org/keywords/sediment","display_name":"Sediment","score":0.42119094729423523},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38514068722724915},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3788546919822693},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.22654008865356445}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9141544699668884},{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.8634676933288574},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6302505731582642},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5718466639518738},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.496947318315506},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.47350484132766724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.448092520236969},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.42932960391044617},{"id":"https://openalex.org/C2816523","wikidata":"https://www.wikidata.org/wiki/Q180184","display_name":"Sediment","level":2,"score":0.42119094729423523},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38514068722724915},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3788546919822693},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.22654008865356445},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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/whispers.2010.5594842","is_oa":false,"landing_page_url":"https://doi.org/10.1109/whispers.2010.5594842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.5400000214576721,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1543835070","https://openalex.org/W1563088657","https://openalex.org/W1902027874","https://openalex.org/W1966798775","https://openalex.org/W2014410318","https://openalex.org/W2033140295","https://openalex.org/W2036027239","https://openalex.org/W2061039544","https://openalex.org/W2071249186","https://openalex.org/W2102069589","https://openalex.org/W2105002599","https://openalex.org/W2112076978","https://openalex.org/W2120397745","https://openalex.org/W2126436234","https://openalex.org/W2127431974","https://openalex.org/W2140691710","https://openalex.org/W2144492104","https://openalex.org/W2295820431","https://openalex.org/W4233760599","https://openalex.org/W4242321082","https://openalex.org/W4285719527","https://openalex.org/W6676769703"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W1990914742","https://openalex.org/W3106536224","https://openalex.org/W2891033441","https://openalex.org/W2890371384","https://openalex.org/W2315521504","https://openalex.org/W2006559622","https://openalex.org/W2040756827","https://openalex.org/W2051769241","https://openalex.org/W2773863718"],"abstract_inverted_index":{"A":[0,26],"smart":[1],"unmixing":[2,87,152],"approach":[3,110,132],"for":[4,99,185],"quantitative":[5],"detection":[6],"of":[7,10,30,55,95,114,168],"small":[8],"amounts":[9],"dust":[11,27,188],"that":[12,49,111,172,178],"settle":[13],"on":[14,135,190],"the":[15,56,93,96,116,123,169,173],"vegetation":[16,48],"canopy":[17],"using":[18,67],"hyperspectral":[19],"(HRS)":[20],"airborne":[21,195],"imagery":[22,121],"data":[23],"is":[24,112,133,175],"proposed.":[25],"analog":[28],"composed":[29],"Alumina":[31],"(Aluminum":[32],"Oxide":[33],"Al":[34],"<sub":[35,39],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[36,40],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sub>":[37],"O":[38],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">3</sub>":[41],")":[42],"powder":[43,118],"was":[44],"artificially":[45],"spread":[46],"over":[47],"covered":[50],"4":[51,53],"\u00d7":[52],"pixels":[54],"AISA-Dual":[57],"sensor.":[58],"The":[59,154],"alumina":[60,117],"spectral":[61,127,145],"signal":[62],"could":[63],"not":[64],"be":[65],"extracted":[66],"ordinary":[68],"methods":[69,98],"such":[70],"as":[71],"supervised":[72],"classification":[73,79],"(e.g.":[74,88],"SAM":[75],"or":[76,82,90],"MTMF),":[77],"unsupervised":[78],"(Maximum":[80],"Likelihood":[81],"Minimum":[83],"Distance),":[84],"and":[85,147,157,177],"linear":[86],"MESMA":[89],"VCA).":[91],"Considering":[92],"limitations":[94],"above":[97],"extracting":[100],"endmembers":[101],"in":[102],"a":[103,108,136,140,148,162,182,191],"nonlinear":[104,151],"domain,":[105],"we":[106],"developed":[107],"new":[109,183],"capable":[113],"detecting":[115],"from":[119],"HRS":[120],"covering":[122],"VIS-NIR-SWIR":[124],"(400-2400":[125],"nm)":[126],"regions.":[128],"This":[129],"step":[130],"wised":[131],"based":[134],"sequence":[137],"merge":[138],"between":[139],"decision":[141],"tree":[142],"algorithm,":[143],"several":[144],"indices":[146],"flexible":[149],"constrained":[150],"method.":[153],"endmember":[155],"vectors":[156],"abundances":[158],"are":[159],"obtained":[160],"through":[161],"gradient-based":[163],"optimization":[164],"approach.":[165],"Ground-truth":[166],"examination":[167],"results":[170],"showed":[171],"method":[174],"reliable":[176],"it":[179],"may":[180],"represent":[181],"frontier":[184],"assessing":[186],"sediment":[187],"contamination":[189],"dark":[192],"background":[193],"via":[194],"sensors.":[196]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}