{"id":"https://openalex.org/W7216888292","doi":null,"title":"Satellite Imaging for Crop Yield Forecasting Using AI","display_name":"Satellite Imaging for Crop Yield Forecasting Using AI","publication_year":2026,"publication_date":"2026-08-11","ids":{"openalex":"https://openalex.org/W7216888292"},"language":"en","primary_location":{"id":"pmh:oai:ojs2.ijerst.org:article/4375","doi":null,"is_oa":true,"landing_page_url":"https://ijerst.org/index.php/ijerst/article/view/4375","pdf_url":"https://ijerst.org/index.php/ijerst/article/download/4375/4032","source":{"id":"https://openalex.org/S5406990484","display_name":"International Journal of Engineering Research and Science & Technology","issn_l":"2319-5991","issn":["2319-5991"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2319-5991","raw_type":"info:eu-repo/semantics/article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ijerst.org/index.php/ijerst/article/download/4375/4032","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5155368783","display_name":"2 Dr.K.Shahu Chatrapati 1 Thagirancha Harshitha","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"1 Thagirancha Harshitha, 2 Dr.K.Shahu Chatrapati","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5155368783"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.69312211,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.7562999725341797,"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":0.7562999725341797,"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":0.24279999732971191,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.0003000000142492354,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/crop-yield-prediction","display_name":"crop yield prediction","score":1.0},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"satellite imagery","score":0.9639999866485596},{"id":"https://openalex.org/keywords/multispectral-imagery","display_name":"multispectral imagery","score":0.8949999809265137},{"id":"https://openalex.org/keywords/hyperspectral-imagery","display_name":"hyperspectral imagery","score":0.9919999837875366},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.9710000157356262},{"id":"https://openalex.org/keywords/transformer","display_name":"transformer models","score":0.9480000138282776},{"id":"https://openalex.org/keywords/deep-learning","display_name":"deep learning","score":0.6399999856948853},{"id":"https://openalex.org/keywords/food-security","display_name":"food security","score":0.7260000109672546},{"id":"https://openalex.org/keywords/agricultural-planning","display_name":"agricultural planning","score":0.6800000071525574},{"id":"https://openalex.org/keywords/soil-moisture","display_name":"soil moisture","score":0.718999981880188},{"id":"https://openalex.org/keywords/vegetation-analysis","display_name":"vegetation analysis","score":0.6269999742507935},{"id":"https://openalex.org/keywords/climate-resilience","display_name":"climate resilience","score":0.6269999742507935},{"id":"https://openalex.org/keywords/irrigation-planning","display_name":"irrigation planning","score":0.49300000071525574}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5751000046730042},{"id":"https://openalex.org/C126343540","wikidata":"https://www.wikidata.org/wiki/Q889514","display_name":"Crop yield","level":2,"score":0.5715000033378601},{"id":"https://openalex.org/C88463610","wikidata":"https://www.wikidata.org/wiki/Q194118","display_name":"Agricultural engineering","level":1,"score":0.5583000183105469},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.5156999826431274},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.45890000462532043},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.447299987077713},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.44679999351501465},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.40389999747276306},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4020000100135803},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.38760000467300415},{"id":"https://openalex.org/C128383755","wikidata":"https://www.wikidata.org/wiki/Q3816336","display_name":"Agricultural productivity","level":3,"score":0.3695000112056732},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.32659998536109924},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.3255999982357025},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.31839999556541443},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.3018999993801117},{"id":"https://openalex.org/C88862950","wikidata":"https://www.wikidata.org/wiki/Q11453","display_name":"Irrigation","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C552854447","wikidata":"https://www.wikidata.org/wiki/Q131201","display_name":"Sustainable development","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C39399123","wikidata":"https://www.wikidata.org/wiki/Q1348989","display_name":"Earth observation","level":3,"score":0.2685000002384186},{"id":"https://openalex.org/C54924851","wikidata":"https://www.wikidata.org/wiki/Q2751054","display_name":"Sustainable agriculture","level":3,"score":0.26420000195503235},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:ojs2.ijerst.org:article/4375","doi":null,"is_oa":true,"landing_page_url":"https://ijerst.org/index.php/ijerst/article/view/4375","pdf_url":"https://ijerst.org/index.php/ijerst/article/download/4375/4032","source":{"id":"https://openalex.org/S5406990484","display_name":"International Journal of Engineering Research and Science & Technology","issn_l":"2319-5991","issn":["2319-5991"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2319-5991","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:ojs2.ijerst.org:article/4375","doi":null,"is_oa":true,"landing_page_url":"https://ijerst.org/index.php/ijerst/article/view/4375","pdf_url":"https://ijerst.org/index.php/ijerst/article/download/4375/4032","source":{"id":"https://openalex.org/S5406990484","display_name":"International Journal of Engineering Research and Science & Technology","issn_l":"2319-5991","issn":["2319-5991"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2319-5991","raw_type":"info:eu-repo/semantics/article"},"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.991100013256073}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7216888292.pdf","grobid_xml":"https://content.openalex.org/works/W7216888292.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7117410372","https://openalex.org/W4410229144","https://openalex.org/W4405379350","https://openalex.org/W4400975657","https://openalex.org/W4415367800","https://openalex.org/W7216913799","https://openalex.org/W7218012125","https://openalex.org/W7217323504","https://openalex.org/W4413978458","https://openalex.org/W4412405642"],"abstract_inverted_index":{"Accurate":[0],"crop":[1,84,121,148,168,191,206],"yield":[2,22,85,169],"forecasting":[3,86],"plays":[4],"a":[5,224],"crucial":[6],"role":[7],"in":[8,185],"ensuring":[9],"food":[10],"security,":[11],"supporting":[12],"effective":[13],"agricultural":[14,49,111,173,181,215],"planning,":[15,196],"and":[16,32,44,64,74,92,101,112,123,128,142,150,166,183,197,207,220,227],"strengthening":[17],"the":[18,39,57,132,210,221],"rural":[19],"economy.":[20],"Traditional":[21],"estimation":[23,170],"methods,":[24],"which":[25],"often":[26,54],"depend":[27],"on":[28],"manual":[29],"field":[30,208],"surveys":[31],"conventional":[33],"statistical":[34],"techniques,":[35,95],"may":[36],"not":[37],"provide":[38],"level":[40],"of":[41,59,110,155,223],"accuracy,":[42],"scalability,":[43],"timeliness":[45],"required":[46],"for":[47],"modern":[48],"systems.":[50],"These":[51],"approaches":[52],"are":[53],"constrained":[55],"by":[56],"difficulty":[58],"collecting":[60],"large-scale":[61],"ground-level":[62],"data":[63,114],"their":[65],"limited":[66],"ability":[67],"to":[68,70,115,190,213],"adapt":[69],"changing":[71],"weather":[72],"conditions":[73],"climate":[75,218],"variability.This":[76],"work":[77],"proposes":[78],"an":[79],"Artificial":[80],"Intelligence":[81],"(AI)-":[82],"based":[83],"framework":[87,106,211],"that":[88,146],"utilizes":[89],"satellite":[90,130,157],"imagery":[91],"advanced":[93],"deep-learning":[94],"including":[96],"Convolutional":[97],"Neural":[98],"Networks":[99],"(CNNs)":[100],"transformer-based":[102],"models.":[103],"The":[104,153,175],"proposed":[105,176],"processes":[107],"large":[108,172],"volumes":[109],"remote-sensing":[113],"identify":[116],"important":[117],"patterns":[118],"associated":[119],"with":[120,160],"growth":[122],"productivity.":[124],"By":[125,200],"utilizing":[126],"multispectral":[127],"hyperspectral":[129],"imagery,":[131],"system":[133],"can":[134,178],"analyze":[135],"vegetation":[136],"characteristics,":[137],"soil":[138],"conditions,":[139,209],"moisture":[140],"levels,":[141],"other":[143],"environmental":[144],"factors":[145],"influence":[147],"development":[149,222],"final":[151],"yield.":[152],"integration":[154],"AI-driven":[156],"image":[158],"analysis":[159],"predictive":[161],"analytics":[162],"enables":[163],"more":[164,225],"accurate":[165],"timely":[167],"across":[171],"regions.":[174],"approach":[177],"assist":[179],"farmers,":[180],"experts,":[182],"policymakers":[184],"making":[186],"data-driven":[187],"decisions":[188],"related":[189],"management,":[192],"resource":[193],"allocation,":[194],"irrigation":[195],"food-production":[198,229],"strategies.":[199],"providing":[201],"near":[202],"real-time":[203],"insights":[204],"into":[205],"contributes":[212],"improved":[214],"productivity,":[216],"enhanced":[217],"resilience,":[219],"efficient":[226],"sustainable":[228],"ecosystem.":[230]},"counts_by_year":[],"updated_date":"2026-10-07T09:51:55.459714","created_date":"2026-10-03T00:00:00"}
