{"id":"https://openalex.org/W2901440531","doi":"https://doi.org/10.1109/igarss.2018.8517523","title":"Remote Estimation of Canopy Water Content in Different Crop Types with New Hyperspectral Indices","display_name":"Remote Estimation of Canopy Water Content in Different Crop Types with New Hyperspectral Indices","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2901440531","doi":"https://doi.org/10.1109/igarss.2018.8517523","mag":"2901440531"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8517523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517523","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 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/A5005200115","display_name":"Nieves Pasqualotto","orcid":"https://orcid.org/0000-0002-0782-8455"},"institutions":[{"id":"https://openalex.org/I2801097182","display_name":"Parc Cient\u00edfic de la Universitat de Val\u00e8ncia","ror":"https://ror.org/04rb60x98","country_code":"ES","type":"education","lineage":["https://openalex.org/I2801097182"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Nieves Pasqualotto","raw_affiliation_strings":["Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain"],"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain","institution_ids":["https://openalex.org/I2801097182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008075763","display_name":"Jes\u00fas Delegido","orcid":"https://orcid.org/0000-0002-2819-6979"},"institutions":[{"id":"https://openalex.org/I2801097182","display_name":"Parc Cient\u00edfic de la Universitat de Val\u00e8ncia","ror":"https://ror.org/04rb60x98","country_code":"ES","type":"education","lineage":["https://openalex.org/I2801097182"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jesus Delegido","raw_affiliation_strings":["Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain"],"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain","institution_ids":["https://openalex.org/I2801097182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055783828","display_name":"Shari Van Wittenberghe","orcid":"https://orcid.org/0000-0002-5699-0352"},"institutions":[{"id":"https://openalex.org/I2801097182","display_name":"Parc Cient\u00edfic de la Universitat de Val\u00e8ncia","ror":"https://ror.org/04rb60x98","country_code":"ES","type":"education","lineage":["https://openalex.org/I2801097182"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Shari Van Wittenberghe","raw_affiliation_strings":["Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain"],"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain","institution_ids":["https://openalex.org/I2801097182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079448372","display_name":"Jochem Verrelst","orcid":"https://orcid.org/0000-0002-6313-2081"},"institutions":[{"id":"https://openalex.org/I2801097182","display_name":"Parc Cient\u00edfic de la Universitat de Val\u00e8ncia","ror":"https://ror.org/04rb60x98","country_code":"ES","type":"education","lineage":["https://openalex.org/I2801097182"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jochem Verrelst","raw_affiliation_strings":["Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain"],"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain","institution_ids":["https://openalex.org/I2801097182"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101999251","display_name":"Juan Pablo Rivera","orcid":"https://orcid.org/0000-0003-3188-1448"},"institutions":[{"id":"https://openalex.org/I4210163111","display_name":"Consejo Nacional de Humanidades, Ciencias y Tecnolog\u00edas","ror":"https://ror.org/059ex5q34","country_code":"MX","type":"funder","lineage":["https://openalex.org/I4210163111"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Juan Pablo Rivera","raw_affiliation_strings":["CONACYT-UAN, Secretariat of Research and Postgraduate, Tepic, M\u00e9xico"],"affiliations":[{"raw_affiliation_string":"CONACYT-UAN, Secretariat of Research and Postgraduate, Tepic, M\u00e9xico","institution_ids":["https://openalex.org/I4210163111"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003044369","display_name":"J. Moreno","orcid":"https://orcid.org/0000-0002-5283-3333"},"institutions":[{"id":"https://openalex.org/I2801097182","display_name":"Parc Cient\u00edfic de la Universitat de Val\u00e8ncia","ror":"https://ror.org/04rb60x98","country_code":"ES","type":"education","lineage":["https://openalex.org/I2801097182"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jose Moreno","raw_affiliation_strings":["Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain"],"affiliations":[{"raw_affiliation_string":"Image Processing Laboratory (IPL), University of Valencia, Paterna, Val\u00e8ncia, Spain","institution_ids":["https://openalex.org/I2801097182"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5005200115"],"corresponding_institution_ids":["https://openalex.org/I2801097182"],"apc_list":null,"apc_paid":null,"fwci":0.1906,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61191479,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"4","issue":null,"first_page":"3812","last_page":"3815"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9998999834060669,"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":0.9998999834060669,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/T10766","display_name":"Urban Heat Island Mitigation","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8893904685974121},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.7142737507820129},{"id":"https://openalex.org/keywords/canopy","display_name":"Canopy","score":0.6702321171760559},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5982168316841125},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.5141775608062744},{"id":"https://openalex.org/keywords/water-content","display_name":"Water content","score":0.48718875646591187},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.45974522829055786},{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.44464436173439026},{"id":"https://openalex.org/keywords/enhanced-vegetation-index","display_name":"Enhanced vegetation index","score":0.4339449405670166},{"id":"https://openalex.org/keywords/soil-science","display_name":"Soil science","score":0.35037994384765625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3500596284866333},{"id":"https://openalex.org/keywords/vegetation-index","display_name":"Vegetation Index","score":0.2930084466934204},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.2313539683818817},{"id":"https://openalex.org/keywords/agronomy","display_name":"Agronomy","score":0.19487756490707397},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1677820086479187},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1269969344139099},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.11047273874282837}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8893904685974121},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.7142737507820129},{"id":"https://openalex.org/C101000010","wikidata":"https://www.wikidata.org/wiki/Q5033434","display_name":"Canopy","level":2,"score":0.6702321171760559},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5982168316841125},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.5141775608062744},{"id":"https://openalex.org/C24939127","wikidata":"https://www.wikidata.org/wiki/Q373499","display_name":"Water content","level":2,"score":0.48718875646591187},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.45974522829055786},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.44464436173439026},{"id":"https://openalex.org/C78869512","wikidata":"https://www.wikidata.org/wiki/Q5378810","display_name":"Enhanced vegetation index","level":5,"score":0.4339449405670166},{"id":"https://openalex.org/C159390177","wikidata":"https://www.wikidata.org/wiki/Q9161265","display_name":"Soil science","level":1,"score":0.35037994384765625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3500596284866333},{"id":"https://openalex.org/C2780376076","wikidata":"https://www.wikidata.org/wiki/Q1499458","display_name":"Vegetation Index","level":4,"score":0.2930084466934204},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.2313539683818817},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.19487756490707397},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1677820086479187},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1269969344139099},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.11047273874282837},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","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},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8517523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8517523","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W221493477","https://openalex.org/W1969568499","https://openalex.org/W1994378716","https://openalex.org/W2118162171","https://openalex.org/W2149813070","https://openalex.org/W2157582727","https://openalex.org/W2738843019","https://openalex.org/W6741572356"],"related_works":["https://openalex.org/W2377212262","https://openalex.org/W4327748155","https://openalex.org/W2955967599","https://openalex.org/W2549050738","https://openalex.org/W4387208895","https://openalex.org/W1594879216","https://openalex.org/W2388815296","https://openalex.org/W1747966239","https://openalex.org/W2383260421","https://openalex.org/W2616508689"],"abstract_inverted_index":{"A":[0],"diverse":[1],"range":[2],"of":[3,14,21,29,42,76,212],"vegetation":[4],"indices":[5,36,57,197],"have":[6],"earlier":[7],"been":[8,117],"developed":[9,59],"for":[10,38,87],"the":[11,106,120,123,138,144,152,158,178,184],"remote":[12],"estimation":[13,181],"canopy":[15],"water":[16,80,127,185],"content":[17,81],"(CWC),":[18],"but":[19],"most":[20],"them":[22],"are":[23],"not":[24],"universally":[25],"applicable.":[26],"The":[27],"aim":[28],"this":[30],"study":[31],"is":[32,156,164],"to":[33,47,169,203],"define":[34],"new":[35],"valid":[37],"a":[39,52,130,165,207],"wide":[40],"variety":[41],"crop":[43],"types,":[44],"that":[45],"allow":[46],"obtain":[48],"CWC":[49],"maps":[50],"at":[51,140,187],"large":[53],"spatial":[54],"scale.":[55],"These":[56,192],"were":[58],"based":[60,176],"on":[61,137,177],"PROSAIL":[62],"simulations":[63],"and":[64,82,97,99,143,148,189,214],"then":[65],"optimized":[66],"with":[67,125,172,206],"an":[68,218],"experimental":[69],"dataset":[70],"(SPARC03;":[71],"Barrax,":[72],"Spain),":[73],"which":[74,163],"consists":[75],"field":[77],"data":[78],"including":[79],"other":[83,153],"biophysical":[84],"parameters":[85],"collected":[86],"6":[88],"different":[89],"crops":[90],"(lucerne,":[91],"corn,":[92],"potato,":[93],"sugar":[94],"beet,":[95],"garlic":[96],"onion)":[98],"associated":[100],"TOC":[101],"reflectance":[102,139],"spectra":[103],"acquired":[104],"by":[105,183],"HyMap":[107],"airborne":[108],"sensor.":[109],"Specifically,":[110],"Water":[111,160],"Absorption":[112],"Area":[113],"Index":[114,161],"(WAAI)":[115],"has":[116],"defined":[118],"as":[119],"area":[121],"between":[122,146],"spectrum":[124,145],"null":[126],"content,":[128],"i.e.":[129],"straight":[131],"line":[132],"whose":[133],"slope":[134],"depends":[135],"only":[136],"800":[141],"nm,":[142],"911":[147],"1271":[149],"nm.":[150,191],"On":[151],"hand,":[154],"it":[155],"proposed":[157],"Depth":[159],"(DWI),":[162],"simple":[166],"index,":[167],"applicable":[168,202],"those":[170],"sensors":[171],"lower":[173],"spectral":[174,179],"resolution,":[175],"depths":[180],"produced":[182],"absorption":[186],"970":[188],"1200":[190],"algorithms":[193],"outperform":[194],"commonly":[195],"used":[196],"in":[198],"predicting":[199],"CWC,":[200],"being":[201],"heterogeneous":[204],"zones,":[205],"R":[208],"<sup":[209],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[210],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[211],"0.8":[213],"0.7,":[215],"respectively,":[216],"using":[217],"exponential":[219],"fit.":[220]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
