{"id":"https://openalex.org/W4403724828","doi":"https://doi.org/10.1109/temsconlatam61834.2024.10717792","title":"Prediction of yield and diseases in crops using vegetation indices through satellite image processing","display_name":"Prediction of yield and diseases in crops using vegetation indices through satellite image processing","publication_year":2024,"publication_date":"2024-07-18","ids":{"openalex":"https://openalex.org/W4403724828","doi":"https://doi.org/10.1109/temsconlatam61834.2024.10717792"},"language":"en","primary_location":{"id":"doi:10.1109/temsconlatam61834.2024.10717792","doi":"https://doi.org/10.1109/temsconlatam61834.2024.10717792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/temsconlatam61834.2024.10717792","pdf_url":null,"source":{"id":"https://openalex.org/S7407097138","display_name":"IEEE Technology and Engineering Management Conference - Latin America (TEMSCON LATAM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Technology and Engineering Management Society (TEMSCON LATAM)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"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/A5074809226","display_name":"Rigoberto Castro Castro","orcid":"https://orcid.org/0000-0002-7671-2149","observed_orcids":["https://orcid.org/0000-0002-7671-2149"]},"institutions":[{"id":"https://openalex.org/I3131337692","display_name":"Central American Technological University","ror":"https://ror.org/03gxj8t57","country_code":"HN","type":"education","lineage":["https://openalex.org/I3131337692"]}],"countries":["HN"],"is_corresponding":true,"raw_author_name":"R. Castro Castro","raw_affiliation_strings":["Universidad Tecnol\u00f3gica Centroamericana (UNITEC),Faculty of Engineering,Tegucigalpa,Honduras"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidad Tecnol\u00f3gica Centroamericana (UNITEC),Faculty of Engineering,Tegucigalpa,Honduras","institution_ids":["https://openalex.org/I3131337692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5074809226"],"corresponding_institution_ids":["https://openalex.org/I3131337692"],"apc_list":null,"apc_paid":null,"fwci":5.2317,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.93890586,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9984999895095825,"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":0.9984999895095825,"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/T10616","display_name":"Smart Agriculture and AI","score":0.001500000013038516,"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/T10439","display_name":"Climate change impacts on agriculture","score":0.0,"subfield":{"id":"https://openalex.org/subfields/1102","display_name":"Agronomy and Crop 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/crop-yield-prediction","display_name":"crop yield prediction","score":1.0},{"id":"https://openalex.org/keywords/crop-disease-detection","display_name":"crop disease detection","score":0.9649999737739563},{"id":"https://openalex.org/keywords/vegetation-index","display_name":"vegetation indices","score":0.7979999780654907},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"NDVI","score":0.9980000257492065},{"id":"https://openalex.org/keywords/landsat-8","display_name":"Landsat 8","score":0.9769999980926514},{"id":"https://openalex.org/keywords/sentinel-2","display_name":"Sentinel-2","score":1.0},{"id":"https://openalex.org/keywords/multiple-linear-regression","display_name":"multiple linear regression","score":0.8119999766349792},{"id":"https://openalex.org/keywords/cucumber","display_name":"cucumber","score":0.9110000133514404},{"id":"https://openalex.org/keywords/beans","display_name":"beans","score":0.8740000128746033},{"id":"https://openalex.org/keywords/maize","display_name":"maize","score":0.9229999780654907},{"id":"https://openalex.org/keywords/crop-phenology","display_name":"crop phenology","score":0.8519999980926514},{"id":"https://openalex.org/keywords/agricultural-decision-support-systems","display_name":"agricultural decision support","score":0.8259999752044678}],"concepts":[{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.7388452291488647},{"id":"https://openalex.org/C2780376076","wikidata":"https://www.wikidata.org/wiki/Q1499458","display_name":"Vegetation Index","level":4,"score":0.6237075328826904},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6140715479850769},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.601745069026947},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.5969797968864441},{"id":"https://openalex.org/C2985301230","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite image","level":3,"score":0.5224144458770752},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.507972776889801},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.35377174615859985},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.348696231842041},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.2905442714691162},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21259325742721558},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.15672296285629272},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08281734585762024},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.054280877113342285},{"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/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","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/temsconlatam61834.2024.10717792","doi":"https://doi.org/10.1109/temsconlatam61834.2024.10717792","is_oa":false,"landing_page_url":"https://doi.org/10.1109/temsconlatam61834.2024.10717792","pdf_url":null,"source":{"id":"https://openalex.org/S7407097138","display_name":"IEEE Technology and Engineering Management Conference - Latin America (TEMSCON LATAM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Technology and Engineering Management Society (TEMSCON LATAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":1.0,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1969256532","https://openalex.org/W2032175810","https://openalex.org/W2061172255","https://openalex.org/W2068371905","https://openalex.org/W2112674101","https://openalex.org/W2167443344","https://openalex.org/W2754935226","https://openalex.org/W2789673541","https://openalex.org/W2811245497","https://openalex.org/W2915536774","https://openalex.org/W2973246319","https://openalex.org/W2978040761","https://openalex.org/W2979666105","https://openalex.org/W2998024395","https://openalex.org/W3015456289","https://openalex.org/W3045734753","https://openalex.org/W3132602407","https://openalex.org/W3134816142","https://openalex.org/W3174385379"],"related_works":["https://openalex.org/W4320489028","https://openalex.org/W4411400253","https://openalex.org/W4376618781","https://openalex.org/W4220679429","https://openalex.org/W3039542254","https://openalex.org/W4223600081","https://openalex.org/W2343193908","https://openalex.org/W3158174812","https://openalex.org/W2259833329","https://openalex.org/W7201873486"],"abstract_inverted_index":{"Crop":[0],"yield":[1,80,179,191,215],"prediction":[2,83,192,259],"represents":[3,337],"a":[4,338,347],"crucial":[5],"tool":[6,340],"used":[7,113,130,225,245,285,312,317],"by":[8,231,313],"farmers":[9,314],"to":[10,30,59,62,77,114,131,176,222,226,242,246,286,318,325,358,360],"optimize":[11,363],"the":[12,45,64,67,71,106,120,133,149,195,219,239,248,253,270,281,356],"management":[13],"of":[14,50,66,73,88,141,151,168,201,250,255,272,330],"their":[15,20],"crop":[16,42,79,160,178,197,256,293,353],"areas":[17,140],"and":[18,26,41,56,81,95,109,125,144,163,180,209,276,289,321,349,362],"maximize":[19],"income.":[21],"It":[22,345],"allows":[23,54],"farmers,":[24],"governments,":[25],"other":[27,46],"relevant":[28],"actors":[29],"make":[31],"informed":[32],"decisions":[33],"about":[34],"planting":[35],"planning,":[36],"production":[37,117],"management,":[38],"resource":[39],"allocation":[40],"marketing.":[43],"On":[44],"hand,":[47],"early":[48],"detection":[49,254],"diseases":[51,181,291],"in":[52,139,148,292],"crops":[53,146],"quick":[55],"precise":[57],"measures":[58],"be":[60,262,284,316],"taken":[61],"control":[63],"spread":[65],"disease.In":[68],"this":[69,74,101],"context,":[70],"objective":[72],"work":[75],"was":[76,207],"develop":[78],"disease":[82],"models":[84,173,193,310],"through":[85,182],"computational":[86],"processing":[87],"satellite":[89,103,303,331],"images":[90,104,128,304,332],"implementing":[91],"vegetation":[92,335],"indexes":[93],"(VI)":[94],"multiple":[96,183,296],"linear":[97],"regression":[98,184,297],"mathematical":[99,172,232],"models.In":[100],"study,":[102],"from":[105,218,238],"Landsat":[107],"8":[108],"Sentinel-2":[110],"constellation":[111],"were":[112,129,174,224,244],"analyze":[115],"agricultural":[116,326,343,364],"farms":[118],"during":[119],"productive":[121],"periods":[122],"between":[123],"2019":[124,221,241],"2024.":[126],"These":[127,309],"calculate":[132],"Normalized":[134],"Differentiated":[135],"Vegetation":[136],"Index":[137],"(NDVI)":[138],"cucumber,":[142],"bean":[143,205],"corn":[145,211],"located":[147],"region":[150],"Comayagua,":[152],"Honduras.":[153],"NDVI":[154,282],"had":[155],"particularly":[156],"close":[157],"relationships":[158],"with":[159,228,300,334],"growth":[161],"stages":[162],"served":[164],"as":[165],"an":[166,199],"indicator":[167],"phenological":[169],"stages.":[170],"Finally,":[171],"developed":[175],"predict":[177,287],"analysis":[185],"using":[186,264],"field":[187,236],"reference":[188,214],"data.":[189],"The":[190,328],"for":[194,204,210,252,341],"cucumber":[196],"reached":[198],"accuracy":[200],"98.92%,":[202],"while":[203],"it":[206],"96.74%":[208],"98.87%.":[212],"Soil":[213],"data":[216],"sets":[217],"years":[220],"2024":[223,243],"compare":[227],"yields":[229,288],"predicted":[230],"models.":[233,308],"In":[234],"addition,":[235],"reports":[237],"period":[240],"validate":[247],"effectiveness":[249],"VI":[251],"diseases.":[257],"This":[258],"methodology":[260],"can":[261,283,305],"automated":[263],"artificial":[265],"intelligence":[266],"(AI)":[267],"software,":[268],"allowing":[269],"execution":[271],"these":[273],"tasks":[274],"efficiently":[275],"automatically.The":[277],"findings":[278],"suggest":[279],"that":[280],"identify":[290],"areas.":[294],"Mathematical":[295],"methods":[298],"applied":[299],"time":[301],"series":[302],"achieve":[306],"reliable":[307],"being":[311],"could":[315],"improve":[319],"logistics":[320],"decision":[322],"making":[323],"related":[324],"production.":[327,365],"utilization":[329],"combined":[333],"indices":[336],"powerful":[339],"contemporary":[342],"management.":[344],"offers":[346],"comprehensive":[348],"dynamic":[350],"perspective":[351],"on":[352],"conditions,":[354],"enhancing":[355],"capability":[357],"adapt":[359],"fluctuations":[361]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3}],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2024-10-25T00:00:00"}