{"id":"https://openalex.org/W4403534450","doi":"https://doi.org/10.1109/codit62066.2024.10708219","title":"Improving Yield Prediction at Field Scale by Exploring Temporal and Spectral Dependencies in High-Resolution Remotely Sensed Data using At-LSTM and R-PCA","display_name":"Improving Yield Prediction at Field Scale by Exploring Temporal and Spectral Dependencies in High-Resolution Remotely Sensed Data using At-LSTM and R-PCA","publication_year":2024,"publication_date":"2024-07-01","ids":{"openalex":"https://openalex.org/W4403534450","doi":"https://doi.org/10.1109/codit62066.2024.10708219"},"language":"en","primary_location":{"id":"doi:10.1109/codit62066.2024.10708219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit62066.2024.10708219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 10th International Conference on Control, Decision and Information Technologies (CoDIT)","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/A5026357022","display_name":"Khadija Meghraou\u0131","orcid":"https://orcid.org/0000-0003-3925-0691"},"institutions":[{"id":"https://openalex.org/I4210135377","display_name":"Hassan II Academy of Science and Technology","ror":"https://ror.org/03ymhqy66","country_code":"MA","type":"government","lineage":["https://openalex.org/I4210135377"]},{"id":"https://openalex.org/I4210157616","display_name":"Institut Agronomique et V\u00e9t\u00e9rinaire Hassan II","ror":"https://ror.org/05f8qcz72","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210157616"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Khadija Meghraoui","raw_affiliation_strings":["IAV Hassan II,Unit of Geospatial Technologies for a Smart Decision,Rabat,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IAV Hassan II,Unit of Geospatial Technologies for a Smart Decision,Rabat,Morocco","institution_ids":["https://openalex.org/I4210135377","https://openalex.org/I4210157616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069739917","display_name":"Imane Sebari","orcid":"https://orcid.org/0000-0002-6754-8404"},"institutions":[{"id":"https://openalex.org/I4210135377","display_name":"Hassan II Academy of Science and Technology","ror":"https://ror.org/03ymhqy66","country_code":"MA","type":"government","lineage":["https://openalex.org/I4210135377"]},{"id":"https://openalex.org/I4210157616","display_name":"Institut Agronomique et V\u00e9t\u00e9rinaire Hassan II","ror":"https://ror.org/05f8qcz72","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210157616"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Imane Sebari","raw_affiliation_strings":["IAV Hassan II,Unit of Geospatial Technologies for a Smart Decision,Rabat,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IAV Hassan II,Unit of Geospatial Technologies for a Smart Decision,Rabat,Morocco","institution_ids":["https://openalex.org/I4210135377","https://openalex.org/I4210157616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008412149","display_name":"Saloua Bensiali","orcid":"https://orcid.org/0000-0003-1753-2209"},"institutions":[{"id":"https://openalex.org/I4210157616","display_name":"Institut Agronomique et V\u00e9t\u00e9rinaire Hassan II","ror":"https://ror.org/05f8qcz72","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210157616"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Saloua Bensiali","raw_affiliation_strings":["IAV Hassan II,Department of Applied Statistics and Computer Science,Rabat,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IAV Hassan II,Department of Applied Statistics and Computer Science,Rabat,Morocco","institution_ids":["https://openalex.org/I4210157616"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111782279","display_name":"Kenza Ait El Kadi","orcid":"https://orcid.org/0000-0002-4233-1292"},"institutions":[{"id":"https://openalex.org/I4210135377","display_name":"Hassan II Academy of Science and Technology","ror":"https://ror.org/03ymhqy66","country_code":"MA","type":"government","lineage":["https://openalex.org/I4210135377"]},{"id":"https://openalex.org/I4210157616","display_name":"Institut Agronomique et V\u00e9t\u00e9rinaire Hassan II","ror":"https://ror.org/05f8qcz72","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210157616"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Kenza Ait El Kadi","raw_affiliation_strings":["IAV Hassan II,Unit of Geospatial Technologies for a Smart Decision,Rabat,Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IAV Hassan II,Unit of Geospatial Technologies for a Smart Decision,Rabat,Morocco","institution_ids":["https://openalex.org/I4210135377","https://openalex.org/I4210157616"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1364","last_page":"1368"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8601999878883362,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8601999878883362,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6578606963157654},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6536892652511597},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5643383264541626},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46340179443359375},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.44537806510925293},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4033169150352478},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3511694073677063},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32952699065208435},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.10639718174934387},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10314467549324036},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10100576281547546},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07637199759483337}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6578606963157654},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6536892652511597},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5643383264541626},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46340179443359375},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.44537806510925293},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4033169150352478},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3511694073677063},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32952699065208435},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.10639718174934387},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10314467549324036},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10100576281547546},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07637199759483337},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/codit62066.2024.10708219","is_oa":false,"landing_page_url":"https://doi.org/10.1109/codit62066.2024.10708219","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 10th International Conference on Control, Decision and Information Technologies (CoDIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W2997068971","https://openalex.org/W3023149787","https://openalex.org/W3162501010","https://openalex.org/W3192731655","https://openalex.org/W4200218991","https://openalex.org/W4380046592","https://openalex.org/W4380632596","https://openalex.org/W4386913100","https://openalex.org/W4388233282","https://openalex.org/W4393164407","https://openalex.org/W4407829540"],"related_works":["https://openalex.org/W2121524756","https://openalex.org/W782553550","https://openalex.org/W1987967678","https://openalex.org/W2633218168","https://openalex.org/W4235897794","https://openalex.org/W2059707233","https://openalex.org/W2085738998","https://openalex.org/W2095126257","https://openalex.org/W2139939267","https://openalex.org/W1974511032"],"abstract_inverted_index":{"One":[0],"of":[1,8,15,51,124,149,163,174],"the":[2,6,25,57,125,132,152,156,161,171],"foremost":[3],"answers":[4],"to":[5,24,98],"challenge":[7],"food":[9],"security":[10],"lies":[11],"in":[12,177],"precise":[13],"prediction":[14,19,34,76,106],"crop":[16,180],"yields.":[17],"This":[18,95],"task":[20],"is":[21,35],"complex":[22],"due":[23],"numerous":[26],"variables":[27],"involved.":[28],"A":[29],"primary":[30],"source":[31],"for":[32,73,167],"yield":[33,75,105],"historical":[36,60],"remote":[37],"sensing":[38],"data,":[39],"notably":[40],"satellite":[41],"imagery.":[42],"However,":[43],"such":[44],"imagery":[45],"often":[46],"includes":[47],"redundant":[48,101],"data":[49,61,102,123],"because":[50],"its":[52],"multiple":[53],"spectral":[54,116],"bands":[55],"and":[56,89,103,111,115,128],"extensive":[58],"archived":[59],"over":[62],"extended":[63],"periods.":[64],"In":[65],"this":[66,183],"study,":[67],"we":[68],"introduce":[69],"an":[70],"advanced":[71],"framework":[72,96,142],"corn":[74],"at":[77,182],"field":[78],"level":[79],"utilizing":[80],"Long":[81],"Short-Term":[82],"Memory":[83],"(LSTM)":[84],"combined":[85],"with":[86],"attention":[87],"mechanisms":[88],"randomized":[90],"Principal":[91],"Component":[92],"Analysis":[93],"(r-PCA).":[94],"aims":[97],"filter":[99],"out":[100],"improve":[104],"using":[107,122,136],"raw":[108],"Sentinel-2":[109],"imagery,":[110],"incorporating":[112],"stacked":[113],"temporal":[114],"data.":[117],"Our":[118,140],"model":[119,176],"was":[120,129],"tested":[121],"year":[126],"2019,":[127],"compared":[130],"against":[131],"simple":[133],"LSTM":[134],"architecture":[135],"key":[137],"performance":[138],"indicators.":[139],"proposed":[141],"achieved":[143],"a":[144],"Mean":[145],"Absolute":[146],"Error":[147],"(MAE)":[148],"1.40,":[150],"surpassing":[151],"MAE":[153],"recorded":[154],"by":[155],"LSTM.":[157],"The":[158],"results":[159],"validate":[160],"effectiveness":[162],"our":[164,175],"approach,":[165],"particularly":[166],"field-scale":[168],"predictions,":[169],"demonstrating":[170],"enhanced":[172],"capability":[173],"accurately":[178],"forecasting":[179],"yields":[181],"scale.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
