{"id":"https://openalex.org/W4312370298","doi":"https://doi.org/10.1109/igarss46834.2022.9883524","title":"Olive Tree Health Monitoring Approach Using Satellite Images and Based on Artificial Intelligence: Toward Automatic Olive Stress Detection Solution","display_name":"Olive Tree Health Monitoring Approach Using Satellite Images and Based on Artificial Intelligence: Toward Automatic Olive Stress Detection Solution","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4312370298","doi":"https://doi.org/10.1109/igarss46834.2022.9883524"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9883524","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883524","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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/A5060701763","display_name":"Achraf Makhloufi","orcid":"https://orcid.org/0000-0002-3483-3612"},"institutions":[{"id":"https://openalex.org/I142899784","display_name":"University of Sfax","ror":"https://ror.org/04d4sd432","country_code":"TN","type":"education","lineage":["https://openalex.org/I142899784"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Achraf Makhloufi","raw_affiliation_strings":["SFAX UNIVERSITY,LAB. ATMS","LAB. ATMS, SFAX UNIVERSITY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SFAX UNIVERSITY,LAB. ATMS","institution_ids":["https://openalex.org/I142899784"]},{"raw_affiliation_string":"LAB. ATMS, SFAX UNIVERSITY","institution_ids":["https://openalex.org/I142899784"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081185686","display_name":"Hana Abdelmoula","orcid":"https://orcid.org/0000-0003-3097-6357"},"institutions":[{"id":"https://openalex.org/I4210119561","display_name":"Digital Research Centre of Sfax","ror":"https://ror.org/02s48dm85","country_code":"TN","type":"facility","lineage":["https://openalex.org/I4210119561"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Hana Abdelmoula","raw_affiliation_strings":["CENTRE DE RECHERCHE EN NUMÉRIQUE DE SFAX,LAB. SM@RTS,TUNISIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CENTRE DE RECHERCHE EN NUMÉRIQUE DE SFAX,LAB. SM@RTS,TUNISIA","institution_ids":["https://openalex.org/I4210119561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061299258","display_name":"Asma Ben Abdallah","orcid":"https://orcid.org/0000-0001-7821-7734"},"institutions":[{"id":"https://openalex.org/I4210119561","display_name":"Digital Research Centre of Sfax","ror":"https://ror.org/02s48dm85","country_code":"TN","type":"facility","lineage":["https://openalex.org/I4210119561"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Asma Ben Abdallah","raw_affiliation_strings":["CENTRE DE RECHERCHE EN NUMÉRIQUE DE SFAX,LAB. SM@RTS,TUNISIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CENTRE DE RECHERCHE EN NUMÉRIQUE DE SFAX,LAB. SM@RTS,TUNISIA","institution_ids":["https://openalex.org/I4210119561"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065284035","display_name":"Abdelaziz Kallel","orcid":"https://orcid.org/0000-0003-2490-0241"},"institutions":[{"id":"https://openalex.org/I4210119561","display_name":"Digital Research Centre of Sfax","ror":"https://ror.org/02s48dm85","country_code":"TN","type":"facility","lineage":["https://openalex.org/I4210119561"]}],"countries":["TN"],"is_corresponding":false,"raw_author_name":"Abdelaziz Kallel","raw_affiliation_strings":["CENTRE DE RECHERCHE EN NUMÉRIQUE DE SFAX,LAB. SM@RTS,TUNISIA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CENTRE DE RECHERCHE EN NUMÉRIQUE DE SFAX,LAB. SM@RTS,TUNISIA","institution_ids":["https://openalex.org/I4210119561"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4635,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.83058652,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"7839","last_page":"7842"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9988999962806702,"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":0.9988999962806702,"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/T11796","display_name":"Horticultural and Viticultural Research","score":0.9850999712944031,"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"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9825000166893005,"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/context","display_name":"Context (archaeology)","score":0.6153989434242249},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.596867561340332},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5655820369720459},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.5547048449516296},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5404648780822754},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5219297409057617},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5218778252601624},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.4836062490940094},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47890153527259827},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.42377495765686035},{"id":"https://openalex.org/keywords/cork","display_name":"Cork","score":0.4220142066478729},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.41780608892440796},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.37529587745666504},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23004648089408875},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14572548866271973}],"concepts":[{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6153989434242249},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.596867561340332},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5655820369720459},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.5547048449516296},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5404648780822754},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5219297409057617},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5218778252601624},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.4836062490940094},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47890153527259827},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.42377495765686035},{"id":"https://openalex.org/C2777899904","wikidata":"https://www.wikidata.org/wiki/Q49444","display_name":"Cork","level":2,"score":0.4220142066478729},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.41780608892440796},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.37529587745666504},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23004648089408875},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14572548866271973},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9883524","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883524","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2166312616","https://openalex.org/W2605582374","https://openalex.org/W3095491581","https://openalex.org/W3160342396","https://openalex.org/W3200728974"],"related_works":["https://openalex.org/W2026245968","https://openalex.org/W2101779743","https://openalex.org/W2606193507","https://openalex.org/W1176101057","https://openalex.org/W2731455616","https://openalex.org/W4205547607","https://openalex.org/W2088987569","https://openalex.org/W4235238427","https://openalex.org/W4255177638","https://openalex.org/W4388923766"],"abstract_inverted_index":{"In":[0,20,70],"Tunisian":[1],"agriculture,":[2],"olive":[3],"tree":[4,49,194],"cultivation":[5],"plays":[6],"an":[7,143],"important":[8],"role.":[9],"It":[10,82],"is":[11,25,76,83,118,124,161,188],"affected":[12],"by":[13,85,170],"different":[14,139],"stresses":[15],"that":[16,148,175],"jeopardize":[17],"its":[18],"sustainability.":[19],"this":[21,31,35],"context,":[22],"our":[23,37,212],"objective":[24],"to":[26,50,78,90,92,133,150],"enhance":[27],"the":[28,48,51,60,72,80,116,122,135,138,152,156,177,181,209],"resilience":[29],"of":[30,40,59,62,112,137,166,211],"crop.":[32],"To":[33],"achieve":[34],"goal,":[36],"work":[38],"consists":[39],"detecting":[41],"anomalies":[42],"at":[43],"early":[44],"stage":[45],"starting":[46],"from":[47],"field":[52],"scale.":[53],"The":[54,159,185],"proposed":[55],"solution":[56],"takes":[57],"advantage":[58],"emergence":[61],"satellites":[63],"with":[64,199,202],"high":[65],"spatial":[66],"and":[67,105,196,204],"temporal":[68],"resolution.":[69],"particular,":[71],"Sentinel-2":[73],"sensor":[74],"which":[75],"well-adapted":[77],"monitor":[79],"vegetation.":[81],"characterized":[84],"ten":[86],"spectral":[87],"bands":[88],"allowing":[89],"access":[91],"key":[93],"vegetation":[94,153,182],"properties":[95,154],"such":[96],"as":[97,121],"leaf":[98],"area":[99],"index":[100],"(LAI),":[101],"chlorophyll":[102],"content":[103,107],"(Cab)":[104],"water":[106],"(Cw),":[108],"etc.":[109],"Direct":[110],"estimation":[111],"these":[113],"parameters":[114],"for":[115],"image":[117,179],"not":[119],"practical":[120],"signal":[123],"convolved.":[125],"For":[126],"that,":[127],"we":[128],"use":[129],"artificial":[130],"intelligence":[131],"techniques":[132],"separate":[134],"effects":[136],"properties.":[140,184],"We":[141],"develop":[142],"Artificial":[144],"Neural":[145],"Network":[146],"(ANN)":[147],"learn":[149],"estimate":[151],"given":[155,180],"pixel":[157],"signature.":[158],"learning":[160],"done":[162],"using":[163],"a":[164,171,191],"database":[165],"simulated":[167],"data":[168],"produced":[169],"radiative":[172],"transfer":[173],"model":[174],"simulates":[176],"satellite":[178],"cover":[183],"stress":[186],"detection":[187],"based":[189],"on":[190,193],"threshold":[192],"LAI":[195],"Cab.":[197],"Comparison":[198],"ground":[200],"truth":[201],"healthy":[203],"stressed":[205],"plots":[206],"has":[207],"shown":[208],"validity":[210],"approach.":[213]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}