{"id":"https://openalex.org/W4412049118","doi":"https://doi.org/10.1016/j.ecoinf.2025.103308","title":"FOLU-Net: A novel framework using long short-term memory networks to predict future forestry and other land use","display_name":"FOLU-Net: A novel framework using long short-term memory networks to predict future forestry and other land use","publication_year":2025,"publication_date":"2025-07-05","ids":{"openalex":"https://openalex.org/W4412049118","doi":"https://doi.org/10.1016/j.ecoinf.2025.103308"},"language":"en","primary_location":{"id":"doi:10.1016/j.ecoinf.2025.103308","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ecoinf.2025.103308","pdf_url":null,"source":{"id":"https://openalex.org/S195809937","display_name":"Ecological Informatics","issn_l":"1574-9541","issn":["1574-9541","1878-0512"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"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":"Ecological Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.ecoinf.2025.103308","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Sanchali Banerjee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sanchali Banerjee","raw_affiliation_strings":["Thomas Jefferson High School for Science and Technology, Alexandria, VA, USA"],"affiliations":[{"raw_affiliation_string":"Thomas Jefferson High School for Science and Technology, Alexandria, VA, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039793667","display_name":"Paige T. Williams","orcid":null},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Paige T. Williams","raw_affiliation_strings":["Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087114682","display_name":"Randolph H. Wynne","orcid":"https://orcid.org/0000-0003-3649-835X"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Randolph H. Wynne","raw_affiliation_strings":["Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5039793667"],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":{"value":2510,"currency":"USD","value_usd":2510},"apc_paid":{"value":2510,"currency":"USD","value_usd":2510},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.14143889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"90","issue":null,"first_page":"103308","last_page":"103308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9966999888420105,"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"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9966999888420105,"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"}},{"id":"https://openalex.org/T12713","display_name":"Forest Ecology and Biodiversity Studies","score":0.9757000207901001,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect 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/T11753","display_name":"Forest Management and Policy","score":0.9660000205039978,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/term","display_name":"Term (time)","score":0.6444711685180664},{"id":"https://openalex.org/keywords/forestry","display_name":"Forestry","score":0.6072433590888977},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.48930951952934265},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4760044515132904},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.4207160472869873},{"id":"https://openalex.org/keywords/agroforestry","display_name":"Agroforestry","score":0.3322526216506958},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.2771373391151428},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15920773148536682},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12844142317771912},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12816515564918518},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06720665097236633},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.06110846996307373}],"concepts":[{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.6444711685180664},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.6072433590888977},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.48930951952934265},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4760044515132904},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.4207160472869873},{"id":"https://openalex.org/C54286561","wikidata":"https://www.wikidata.org/wiki/Q397350","display_name":"Agroforestry","level":1,"score":0.3322526216506958},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.2771373391151428},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15920773148536682},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12844142317771912},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12816515564918518},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06720665097236633},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.06110846996307373},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.ecoinf.2025.103308","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ecoinf.2025.103308","pdf_url":null,"source":{"id":"https://openalex.org/S195809937","display_name":"Ecological Informatics","issn_l":"1574-9541","issn":["1574-9541","1878-0512"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"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":"Ecological Informatics","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:fef224badd2f4c17821552d3fac725c8","is_oa":true,"landing_page_url":"https://doaj.org/article/fef224badd2f4c17821552d3fac725c8","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Ecological Informatics, Vol 90, Iss , Pp 103308- (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.ecoinf.2025.103308","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.ecoinf.2025.103308","pdf_url":null,"source":{"id":"https://openalex.org/S195809937","display_name":"Ecological Informatics","issn_l":"1574-9541","issn":["1574-9541","1878-0512"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"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":"Ecological Informatics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5176850623","display_name":null,"funder_award_id":"NNH21ZDA001N-SARI","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"}],"funders":[{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"},{"id":"https://openalex.org/F4320306114","display_name":"U.S. Department of Agriculture","ror":"https://ror.org/01na82s61"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1581241074","https://openalex.org/W2008832756","https://openalex.org/W2029543583","https://openalex.org/W2120153268","https://openalex.org/W2218047931","https://openalex.org/W2541502989","https://openalex.org/W2601710563","https://openalex.org/W2732020563","https://openalex.org/W2803498638","https://openalex.org/W2884260323","https://openalex.org/W2926658951","https://openalex.org/W2936503027","https://openalex.org/W2942962169","https://openalex.org/W2980322467","https://openalex.org/W2991941657","https://openalex.org/W3006735782","https://openalex.org/W3013082057","https://openalex.org/W3036013298","https://openalex.org/W3038903430","https://openalex.org/W3089149000","https://openalex.org/W3114429882","https://openalex.org/W3126694320","https://openalex.org/W3133618741","https://openalex.org/W3139241726","https://openalex.org/W3161071332","https://openalex.org/W3180781590","https://openalex.org/W3208172463","https://openalex.org/W3216773468","https://openalex.org/W4200223653","https://openalex.org/W4281933899","https://openalex.org/W4293105393","https://openalex.org/W4302763946","https://openalex.org/W4310038319","https://openalex.org/W4362466062","https://openalex.org/W4381940541","https://openalex.org/W4385159963","https://openalex.org/W4399294104","https://openalex.org/W4399881413","https://openalex.org/W4401411998","https://openalex.org/W4405211954","https://openalex.org/W6634411170","https://openalex.org/W6634731002","https://openalex.org/W6735893812","https://openalex.org/W6740837484","https://openalex.org/W6834687282","https://openalex.org/W6851395287","https://openalex.org/W6853750947","https://openalex.org/W6861128717"],"related_works":["https://openalex.org/W2912321008","https://openalex.org/W1998607122","https://openalex.org/W2980611886","https://openalex.org/W2324368075","https://openalex.org/W2972124131","https://openalex.org/W42295635","https://openalex.org/W338149487","https://openalex.org/W1973996291","https://openalex.org/W4403012196","https://openalex.org/W4401807425"],"abstract_inverted_index":{"The":[0,200,228],"objective":[1],"of":[2,35,63,157,171,196,245,281],"this":[3],"study":[4],"is":[5,29],"to":[6,100,152,209,219,296],"predict":[7,153,220,297,307],"future":[8,154,222,308,319],"tropical":[9],"forest":[10,42,123],"cover":[11,23,121,133,231,283,299],"presence":[12],"and":[13,38,129,236],"types":[14],"using":[15,136,179,284],"multitemporal":[16,103,285],"imaging":[17,286,290],"spectroscopy":[18,291],"data.":[19,310],"Accurately":[20],"predicting":[21],"land":[22,39,98,120,132,223,230,246,255,282,298,320],"changes":[24],"with":[25,145,190],"image":[26,104,189],"time":[27,261],"series":[28],"vital":[30],"for":[31,161,252,277,317],"assessing":[32],"the":[33,48,59,70,94,102,112,137,158,184,210,215,221,250,279],"effects":[34],"climate":[36],"change":[37,248],"management":[40],"on":[41,69,183],"resources.":[43],"Data":[44],"were":[45,91,115],"obtained":[46],"from":[47,187,203,214,293],"DLR":[49],"Earth":[50,75],"Sensing":[51],"Imaging":[52],"Spectrometer":[53],"(DESIS)":[54],"covering":[55],"a":[56,82,274],"region":[57],"in":[58,78],"West":[60],"Godavari":[61],"district":[62],"Andhra":[64],"Pradesh,":[65],"India.":[66],"DESIS,":[67],"mounted":[68],"International":[71],"Space":[72],"Station,":[73],"records":[74],"observation":[76],"data":[77,212,292],"235":[79,159],"channels":[80],"over":[81],"400\u20131000":[83],"nm":[84],"spectral":[85],"range.":[86],"Five":[87],"overlapping":[88],"cloud-free":[89],"images":[90],"selected,":[92],"capturing":[93],"seasonal":[95],"variability":[96],"among":[97],"covers":[99],"form":[101],"stack.":[105],"1070":[106],"randomly":[107],"generated":[108,213],"training":[109],"points":[110,186],"spanning":[111],"five":[113],"dates":[114],"visually":[116],"classified":[117,185],"into":[118],"four":[119],"classes:":[122],"plantation,":[124,126],"palm":[125],"natural":[127],"forest,":[128],"non-forest.":[130],"Future":[131],"was":[134,150,181,206],"predicted":[135],"following":[138],"steps:":[139],"(1)":[140],"A":[141,175],"recurrent":[142],"neural":[143,177],"network":[144,178],"long":[146],"short-term":[147,303],"memory":[148,304],"(LSTM)":[149],"used":[151,295],"reflectance":[155,211],"values":[156],"bands":[160],"each":[162,188,226,259],"point.":[163,227],"This":[164],"model":[165,202],"had":[166],"an":[167,194],"R":[168],"2":[169,205],"coefficient":[170],"83.0":[172],"%.":[173,198],"(2)":[174],"multi-layer":[176],"Keras":[180],"trained":[182],"5-fold":[191],"cross-validation,":[192],"achieving":[193],"accuracy":[195],"73.0":[197],"(3)":[199],"classification":[201],"step":[204,262],"then":[207],"applied":[208],"LSTM":[216],"(step":[217],"1)":[218],"type":[224],"at":[225,258],"combined":[229],"prediction":[232],"framework,":[233],"titled":[234],"Forestry":[235],"Other":[237],"Land":[238],"Use":[239],"Neural":[240],"Network":[241],"(FOLU-Net),":[242],"enables":[243],"predictions":[244],"use":[247,256],"without":[249],"need":[251],"potentially":[253],"error-prone":[254,325],"classifications":[257,326],"prior":[260],"necessitated":[263],"by":[264],"approaches":[265],"such":[266],"as":[267],"Markov":[268,330],"chain":[269],"analysis.":[270,331],"Our":[271],"findings":[272],"demonstrate":[273],"robust":[275,315],"framework":[276,316],"characterizing":[278,318],"evolution":[280],"spectroscopy.":[287],"\u2022":[288,301,311,322],"Multitemporal":[289],"DESIS":[294],"change.":[300],"Long":[302],"networks":[305],"successfully":[306],"hyperspectral":[309],"Deep":[312],"learning":[313],"provides":[314],"use.":[321],"FOLU-Net":[323],"eliminates":[324],"per":[327],"timestep":[328],"unlike":[329]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
