{"id":"https://openalex.org/W4402260922","doi":"https://doi.org/10.1109/igarss53475.2024.10641150","title":"Xai-Guided Enhancement of Vegetation Indices for Crop Mapping","display_name":"Xai-Guided Enhancement of Vegetation Indices for Crop Mapping","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402260922","doi":"https://doi.org/10.1109/igarss53475.2024.10641150"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10641150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10641150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 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/A5087589867","display_name":"Hiba Najjar","orcid":"https://orcid.org/0000-0002-7498-794X"},"institutions":[{"id":"https://openalex.org/I2802076133","display_name":"University of Koblenz and Landau","ror":"https://ror.org/01j9f6752","country_code":"DE","type":"education","lineage":["https://openalex.org/I2802076133"]},{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Hiba Najjar","raw_affiliation_strings":["University of Kaiserslautern-Landau,Kaiserslautern,Germany"],"affiliations":[{"raw_affiliation_string":"University of Kaiserslautern-Landau,Kaiserslautern,Germany","institution_ids":["https://openalex.org/I2802076133","https://openalex.org/I153267046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022033505","display_name":"Francisco Mena","orcid":"https://orcid.org/0000-0002-5004-6571"},"institutions":[{"id":"https://openalex.org/I153267046","display_name":"University of Kaiserslautern","ror":"https://ror.org/04zrf7b53","country_code":"DE","type":"education","lineage":["https://openalex.org/I153267046"]},{"id":"https://openalex.org/I2802076133","display_name":"University of Koblenz and Landau","ror":"https://ror.org/01j9f6752","country_code":"DE","type":"education","lineage":["https://openalex.org/I2802076133"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Francisco Mena","raw_affiliation_strings":["University of Kaiserslautern-Landau,Kaiserslautern,Germany"],"affiliations":[{"raw_affiliation_string":"University of Kaiserslautern-Landau,Kaiserslautern,Germany","institution_ids":["https://openalex.org/I2802076133","https://openalex.org/I153267046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013923731","display_name":"Marlon Nuske","orcid":"https://orcid.org/0000-0002-0651-0664"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Marlon Nuske","raw_affiliation_strings":["German Research Center for Artificial Intelligence,Kaiserslautern,Germany"],"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence,Kaiserslautern,Germany","institution_ids":["https://openalex.org/I33256026"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101904182","display_name":"Andreas Dengel","orcid":"https://orcid.org/0000-0002-6100-8255"},"institutions":[{"id":"https://openalex.org/I33256026","display_name":"German Research Centre for Artificial Intelligence","ror":"https://ror.org/01ayc5b57","country_code":"DE","type":"funder","lineage":["https://openalex.org/I33256026"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Dengel","raw_affiliation_strings":["German Research Center for Artificial Intelligence,Kaiserslautern,Germany"],"affiliations":[{"raw_affiliation_string":"German Research Center for Artificial Intelligence,Kaiserslautern,Germany","institution_ids":["https://openalex.org/I33256026"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087589867"],"corresponding_institution_ids":["https://openalex.org/I153267046","https://openalex.org/I2802076133"],"apc_list":null,"apc_paid":null,"fwci":1.9039,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.85587922,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4140","last_page":"4144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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":0.9871000051498413,"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"}},{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9819999933242798,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.6505700349807739},{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.5161219835281372},{"id":"https://openalex.org/keywords/vegetation-index","display_name":"Vegetation Index","score":0.4354192018508911},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3914395570755005},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3426600694656372},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2548089325428009},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.24114665389060974},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.20947015285491943},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.16948091983795166},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.059854656457901},{"id":"https://openalex.org/keywords/climate-change","display_name":"Climate change","score":0.04847836494445801}],"concepts":[{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.6505700349807739},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.5161219835281372},{"id":"https://openalex.org/C2780376076","wikidata":"https://www.wikidata.org/wiki/Q1499458","display_name":"Vegetation Index","level":4,"score":0.4354192018508911},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3914395570755005},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3426600694656372},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2548089325428009},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.24114665389060974},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.20947015285491943},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.16948091983795166},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.059854656457901},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.04847836494445801},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss53475.2024.10641150","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss53475.2024.10641150","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1924770834","https://openalex.org/W1994508789","https://openalex.org/W2039604550","https://openalex.org/W2742706476","https://openalex.org/W2742982421","https://openalex.org/W2792827505","https://openalex.org/W2890443177","https://openalex.org/W2962858109","https://openalex.org/W2988111912","https://openalex.org/W2989983865","https://openalex.org/W3007590609","https://openalex.org/W3020975691","https://openalex.org/W3081429447","https://openalex.org/W3087468769","https://openalex.org/W3102127038","https://openalex.org/W3112273466","https://openalex.org/W3185292364","https://openalex.org/W4240485910","https://openalex.org/W4286299948","https://openalex.org/W4387829365","https://openalex.org/W6636950212","https://openalex.org/W6640212811","https://openalex.org/W6682385587","https://openalex.org/W6765001775"],"related_works":["https://openalex.org/W3018080369","https://openalex.org/W4298152215","https://openalex.org/W4292161287","https://openalex.org/W2383038510","https://openalex.org/W2171400093","https://openalex.org/W2371343493","https://openalex.org/W2388889817","https://openalex.org/W3017461794","https://openalex.org/W2980711745","https://openalex.org/W2372683889"],"abstract_inverted_index":{"Vegetation":[0],"indices":[1,28,95,125,142],"allow":[2],"to":[3,31,61,83,99,129],"efficiently":[4,51],"monitor":[5],"vegetation":[6,27,66,94],"growth":[7],"and":[8,23,39,63,104],"agricultural":[9],"activities.":[10],"Previous":[11],"generations":[12,36],"of":[13,20,37,140],"satellites":[14,41],"were":[15,29],"capturing":[16],"a":[17,24,71,113],"limited":[18],"number":[19],"spectral":[21],"bands,":[22,46,136],"few":[25],"expert-designed":[26],"sufficient":[30],"harness":[32],"their":[33],"potential.":[34],"New":[35],"multi-":[38],"hyperspectral":[40],"can":[42],"however":[43],"capture":[44],"additional":[45],"but":[47],"are":[48],"not":[49],"yet":[50],"exploited.":[52],"In":[53],"this":[54],"work,":[55],"we":[56],"propose":[57],"an":[58],"explainable-AI-based":[59],"method":[60],"select":[62,91],"design":[64],"suitable":[65,92],"indices.":[67],"We":[68,89,108],"first":[69],"train":[70],"deep":[72],"neural":[73],"network":[74],"using":[75],"multispectral":[76],"satellite":[77],"data,":[78],"then":[79],"extract":[80],"feature":[81],"importance":[82],"identify":[84],"the":[85,101,130,138,144],"most":[86],"influential":[87],"bands.":[88],"subsequently":[90],"existing":[93],"or":[96],"modify":[97],"them":[98],"incorporate":[100],"identified":[102],"bands":[103],"retrain":[105],"our":[106,110],"model.":[107],"validate":[109],"approach":[111],"on":[112,123,134],"crop":[114],"classification":[115],"task.":[116],"Our":[117],"results":[118,128],"indicate":[119],"that":[120],"models":[121],"trained":[122,133],"individual":[124],"achieve":[126],"comparable":[127],"baseline":[131,145],"model":[132],"all":[135],"while":[137],"combination":[139],"two":[141],"surpasses":[143],"in":[146],"certain":[147],"cases.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
