{"id":"https://openalex.org/W4367333180","doi":"https://doi.org/10.1109/access.2023.3271410","title":"A Multimodal Data Fusion and Deep Neural Networks Based Technique for Tea Yield Estimation in Pakistan Using Satellite Imagery","display_name":"A Multimodal Data Fusion and Deep Neural Networks Based Technique for Tea Yield Estimation in Pakistan Using Satellite Imagery","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4367333180","doi":"https://doi.org/10.1109/access.2023.3271410"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3271410","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3271410","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10110955.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10110955.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5038844495","display_name":"Zeeshan Ramzan","orcid":"https://orcid.org/0000-0003-2643-4627"},"institutions":[{"id":"https://openalex.org/I142732210","display_name":"University of Engineering and Technology Lahore","ror":"https://ror.org/0051w2v06","country_code":"PK","type":"education","lineage":["https://openalex.org/I142732210"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Zeeshan Ramzan","raw_affiliation_strings":["Department of Computer Science, New Campus, University of Engineering & Technology Lahore, Lahore, Pakistan"],"raw_orcid":"https://orcid.org/0000-0003-2643-4627","affiliations":[{"raw_affiliation_string":"Department of Computer Science, New Campus, University of Engineering & Technology Lahore, Lahore, Pakistan","institution_ids":["https://openalex.org/I142732210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101899733","display_name":"Hafiz Muhammad Shahzad Asif","orcid":"https://orcid.org/0000-0002-2529-7707"},"institutions":[{"id":"https://openalex.org/I142732210","display_name":"University of Engineering and Technology Lahore","ror":"https://ror.org/0051w2v06","country_code":"PK","type":"education","lineage":["https://openalex.org/I142732210"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"H. M. Shahzad Asif","raw_affiliation_strings":["Department of Computer Science, New Campus, University of Engineering & Technology Lahore, Lahore, Pakistan"],"raw_orcid":"https://orcid.org/0000-0002-2529-7707","affiliations":[{"raw_affiliation_string":"Department of Computer Science, New Campus, University of Engineering & Technology Lahore, Lahore, Pakistan","institution_ids":["https://openalex.org/I142732210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036659376","display_name":"Muhammad Irfan Yousuf","orcid":"https://orcid.org/0000-0003-2950-4109"},"institutions":[{"id":"https://openalex.org/I142732210","display_name":"University of Engineering and Technology Lahore","ror":"https://ror.org/0051w2v06","country_code":"PK","type":"education","lineage":["https://openalex.org/I142732210"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Irfan Yousuf","raw_affiliation_strings":["Department of Computer Science, New Campus, University of Engineering & Technology Lahore, Lahore, Pakistan"],"raw_orcid":"https://orcid.org/0000-0003-2950-4109","affiliations":[{"raw_affiliation_string":"Department of Computer Science, New Campus, University of Engineering & Technology Lahore, Lahore, Pakistan","institution_ids":["https://openalex.org/I142732210"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103219669","display_name":"Muhammad Shahbaz","orcid":"https://orcid.org/0000-0001-6493-226X"},"institutions":[{"id":"https://openalex.org/I142732210","display_name":"University of Engineering and Technology Lahore","ror":"https://ror.org/0051w2v06","country_code":"PK","type":"education","lineage":["https://openalex.org/I142732210"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Shahbaz","raw_affiliation_strings":["Department of Computer Engineering, University of Engineering & Technology Lahore, Lahore, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering, University of Engineering & Technology Lahore, Lahore, Pakistan","institution_ids":["https://openalex.org/I142732210"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I142732210"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.7903,"has_fulltext":true,"cited_by_count":39,"citation_normalized_percentile":{"value":0.98277316,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"11","issue":null,"first_page":"42578","last_page":"42594"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9990000128746033,"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":0.9990000128746033,"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":0.9980000257492065,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6318634152412415},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6194159984588623},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5994920134544373},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5900576114654541},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5583427548408508},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5457006692886353},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4969542324542999},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.47685420513153076},{"id":"https://openalex.org/keywords/data-pre-processing","display_name":"Data pre-processing","score":0.42604243755340576},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.4214053153991699},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.4177875518798828},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.41415727138519287},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3854611814022064},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22702506184577942},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20243364572525024}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6318634152412415},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6194159984588623},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5994920134544373},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5900576114654541},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5583427548408508},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5457006692886353},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4969542324542999},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.47685420513153076},{"id":"https://openalex.org/C10551718","wikidata":"https://www.wikidata.org/wiki/Q5227332","display_name":"Data pre-processing","level":2,"score":0.42604243755340576},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.4214053153991699},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.4177875518798828},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.41415727138519287},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3854611814022064},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22702506184577942},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20243364572525024},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3271410","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3271410","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10110955.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0766b021dcc048bd8f6af45fe8f7c697","is_oa":true,"landing_page_url":"https://doaj.org/article/0766b021dcc048bd8f6af45fe8f7c697","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 42578-42594 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3271410","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3271410","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/10005208/10110955.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"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":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.6700000166893005}],"awards":[{"id":"https://openalex.org/G5559068778","display_name":null,"funder_award_id":"NRPU 9201","funder_id":"https://openalex.org/F4320322799","funder_display_name":"Higher Education Commission, Pakistan"}],"funders":[{"id":"https://openalex.org/F4320322799","display_name":"Higher Education Commission, Pakistan","ror":"https://ror.org/038y3sz68"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4367333180.pdf","grobid_xml":"https://content.openalex.org/works/W4367333180.grobid-xml"},"referenced_works_count":77,"referenced_works":["https://openalex.org/W60686164","https://openalex.org/W248389711","https://openalex.org/W1457115475","https://openalex.org/W1500895378","https://openalex.org/W1559923427","https://openalex.org/W1571001096","https://openalex.org/W1607241334","https://openalex.org/W1663985127","https://openalex.org/W1964217023","https://openalex.org/W1968496754","https://openalex.org/W1971977120","https://openalex.org/W1979636379","https://openalex.org/W1988489115","https://openalex.org/W1998451497","https://openalex.org/W2014847057","https://openalex.org/W2025217506","https://openalex.org/W2029258345","https://openalex.org/W2030370010","https://openalex.org/W2044574395","https://openalex.org/W2052160891","https://openalex.org/W2058709694","https://openalex.org/W2086342036","https://openalex.org/W2086710305","https://openalex.org/W2102539288","https://openalex.org/W2106343913","https://openalex.org/W2106411961","https://openalex.org/W2111839312","https://openalex.org/W2113956708","https://openalex.org/W2125549677","https://openalex.org/W2131241448","https://openalex.org/W2171033594","https://openalex.org/W2193847129","https://openalex.org/W2202019762","https://openalex.org/W2312997001","https://openalex.org/W2411226130","https://openalex.org/W2553303224","https://openalex.org/W2564103795","https://openalex.org/W2607177037","https://openalex.org/W2740577199","https://openalex.org/W2885311373","https://openalex.org/W2914293428","https://openalex.org/W2931650435","https://openalex.org/W2943530662","https://openalex.org/W2953686964","https://openalex.org/W2964081807","https://openalex.org/W2965658867","https://openalex.org/W2979666105","https://openalex.org/W2991004173","https://openalex.org/W3000098473","https://openalex.org/W3010885041","https://openalex.org/W3033815121","https://openalex.org/W3035196568","https://openalex.org/W3098019734","https://openalex.org/W3118412853","https://openalex.org/W3126835551","https://openalex.org/W3128092465","https://openalex.org/W3182380878","https://openalex.org/W3197801984","https://openalex.org/W4211007200","https://openalex.org/W4211116959","https://openalex.org/W4211208325","https://openalex.org/W4287879957","https://openalex.org/W4294864637","https://openalex.org/W4297434941","https://openalex.org/W4300961965","https://openalex.org/W4301014524","https://openalex.org/W6628353318","https://openalex.org/W6633702045","https://openalex.org/W6676179485","https://openalex.org/W6678911119","https://openalex.org/W6729956949","https://openalex.org/W6741132002","https://openalex.org/W6753278433","https://openalex.org/W6762376514","https://openalex.org/W6787985496","https://openalex.org/W6790082478","https://openalex.org/W6842834842"],"related_works":["https://openalex.org/W4366990902","https://openalex.org/W4388550696","https://openalex.org/W4321636153","https://openalex.org/W4313289487","https://openalex.org/W2994772185","https://openalex.org/W1528227026","https://openalex.org/W2756012949","https://openalex.org/W4386970085","https://openalex.org/W4214940564","https://openalex.org/W4206908315"],"abstract_inverted_index":{"Achieving":[0],"food":[1,20],"security":[2],"has":[3],"become":[4],"a":[5,46,63,245,302,310],"major":[6],"challenge":[7],"for":[8,15,148,248],"society.":[9],"Crop":[10,123],"yield":[11,24,52,101,250],"estimation":[12,25,251],"is":[13,26,112,137,154,175,259,281],"essential":[14],"crop":[16,23],"monitoring":[17],"to":[18,57,62,72,85,97,139,156,177],"ensure":[19],"security.":[21],"Manual":[22],"cumbersome":[27],"and":[28,30,93,121,166,204,210,214,239,268,286,333],"inaccurate":[29],"becomes":[31],"infeasible":[32],"when":[33],"scaled":[34],"up.":[35],"Machine":[36],"learning":[37,65,184,229],"algorithms":[38],"trained":[39],"using":[40,252,261],"remotely":[41],"sensed":[42],"data":[43,60,87,132,174],"have":[44,231,269],"played":[45],"vital":[47],"role":[48],"in":[49,109],"estimating":[50],"the":[51,59,74,99,103,118,134,151,162,167,179,222,227,287,295],"of":[53,77,117,133,164,169,182,226,304,307,315,323,330,339],"different":[54],"crops.":[55],"Furthermore,":[56],"enrich":[58],"provided":[61,294,301],"machine":[64,183],"algorithm,":[66],"multiple":[67,89],"modalities":[68],"can":[69,274],"be":[70],"combined":[71],"improve":[73],"predictive":[75,297],"performance":[76],"these":[78],"algorithms.":[79,186],"In":[80],"this":[81,110,242],"research,":[82],"we":[83],"propose":[84],"combine":[86],"from":[88,114],"modalities,":[90],"i.e.,":[91],"agrometeorological":[92],"remote":[94,130],"sensing":[95,131],"data,":[96],"predict":[98],"tea":[100,115,249],"at":[102],"farm":[104],"level.":[105],"The":[106,129,299],"dataset":[107,153],"employed":[108],"study":[111,243],"acquired":[113],"fields":[116],"National":[119],"Tea":[120],"High-Value":[122],"Research":[124],"Institute":[125],"(NTHRI),":[126],"Mansehra,":[127],"Pakistan.":[128],"Landsat-8":[135],"satellite":[136],"converted":[138],"farm-level":[140],"NDVI":[141],"statistics":[142],"through":[143,283],"geocoding.":[144],"Before":[145],"being":[146],"used":[147,176],"regression":[149,185,188,292],"modeling,":[150],"final":[152],"subjected":[155],"some":[157],"further":[158],"preprocessing":[159],"steps,":[160],"including":[161,190],"selection":[163],"features":[165],"optimization":[168,267],"feature":[170,216],"sets.":[171],"This":[172,255],"preprocessed":[173],"train":[178],"three":[180,224,270],"classes":[181],"Conventional":[187],"algorithms,":[189],"Decision":[191],"Trees,":[192],"Multilayer":[193],"Perceptron":[194],"(MLP),":[195],"Support":[196],"Vector":[197],"Regression":[198,202,207],"(SVR),":[199],"Gaussian":[200],"Process":[201],"(GPR),":[203],"Multiple":[205],"Linear":[206],"applied":[208],"with":[209,218,309],"without":[211],"interaction":[212],"terms":[213],"stepwise":[215],"inclusion":[217],"various":[219],"kernels.":[220],"Moreover,":[221],"following":[223],"variants":[225],"ensemble":[228],"methods":[230],"also":[232],"been":[233],"applied:":[234],"random":[235],"forest,":[236],"gradient":[237],"boosting,":[238],"XgBoost.":[240],"Finally,":[241],"proposed":[244,288],"neural":[246,257,262,290],"architecture":[247,263],"Landsat":[253],"imagery.":[254],"deep":[256],"network":[258,291],"built":[260],"search":[264],"via":[265],"Bayesian":[266],"hidden":[271],"layers,":[272],"which":[273],"perform":[275],"complex":[276],"non-linear":[277],"modeling.":[278],"Experimental":[279],"evaluation":[280],"performed":[282],"10-fold":[284],"cross-validation,":[285],"Deep":[289],"model":[293,300],"best":[296],"performance.":[298],"coefficient":[303],"determination":[305],"(R-squared)":[306],"0.99":[308],"Mean":[311,319,326,334],"Square":[312,320],"Error":[313,321,328,337],"(MSE)":[314],"108.17":[316],"kg/ha,":[317,325],"Root":[318],"(RMSE)":[322],"10.87":[324],"Absolute":[327,335],"(MAE)":[329],"2.26":[331],"kg/ha":[332],"Percentage":[336],"(MAPE)":[338],"2.92.":[340]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":5}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}