{"id":"https://openalex.org/W4412120819","doi":"https://doi.org/10.1080/10095020.2025.2514815","title":"The impact of fractional cover distribution in training samples on the accuracy of fractional cover estimation: a model-based evaluation","display_name":"The impact of fractional cover distribution in training samples on the accuracy of fractional cover estimation: a model-based evaluation","publication_year":2025,"publication_date":"2025-07-09","ids":{"openalex":"https://openalex.org/W4412120819","doi":"https://doi.org/10.1080/10095020.2025.2514815"},"language":"en","primary_location":{"id":"doi:10.1080/10095020.2025.2514815","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10095020.2025.2514815","pdf_url":null,"source":{"id":"https://openalex.org/S36798160","display_name":"Geo-spatial Information Science","issn_l":"1009-5020","issn":["1009-5020","1993-5153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geo-spatial Information Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1080/10095020.2025.2514815","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Rujia Wang","orcid":"https://orcid.org/0009-0007-8123-6873"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rujia Wang","raw_affiliation_strings":["Capital Normal University"],"raw_orcid":"https://orcid.org/0009-0007-8123-6873","affiliations":[{"raw_affiliation_string":"Capital Normal University","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chen Shi","orcid":"https://orcid.org/0009-0002-2347-2169"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Shi","raw_affiliation_strings":["Capital Normal University"],"raw_orcid":"https://orcid.org/0009-0002-2347-2169","affiliations":[{"raw_affiliation_string":"Capital Normal University","institution_ids":["https://openalex.org/I96852419"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I96852419"],"apc_list":{"value":1625,"currency":"GBP","value_usd":1993},"apc_paid":{"value":1625,"currency":"GBP","value_usd":1993},"fwci":1.0501,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.77727936,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"29","issue":"1","first_page":"374","last_page":"412"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9970999956130981,"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":0.9970999956130981,"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/T10266","display_name":"Plant Water Relations and Carbon Dynamics","score":0.9898999929428101,"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"}},{"id":"https://openalex.org/T10889","display_name":"Soil erosion and sediment transport","score":0.9837999939918518,"subfield":{"id":"https://openalex.org/subfields/1111","display_name":"Soil 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/cover","display_name":"Cover (algebra)","score":0.8164151906967163},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.48538005352020264},{"id":"https://openalex.org/keywords/distribution","display_name":"Distribution (mathematics)","score":0.46847549080848694},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4570927023887634},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42044228315353394},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.35959187150001526},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.3272501826286316},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13672348856925964},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.07798901200294495}],"concepts":[{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.8164151906967163},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.48538005352020264},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.46847549080848694},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4570927023887634},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42044228315353394},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35959187150001526},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3272501826286316},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13672348856925964},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.07798901200294495},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/10095020.2025.2514815","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10095020.2025.2514815","pdf_url":null,"source":{"id":"https://openalex.org/S36798160","display_name":"Geo-spatial Information Science","issn_l":"1009-5020","issn":["1009-5020","1993-5153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geo-spatial Information Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:07c718494cd843a99befa973340a06e3","is_oa":true,"landing_page_url":"https://doaj.org/article/07c718494cd843a99befa973340a06e3","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":"Geo-spatial Information Science, Vol 29, Iss 1, Pp 374-412 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/10095020.2025.2514815","is_oa":true,"landing_page_url":"https://doi.org/10.1080/10095020.2025.2514815","pdf_url":null,"source":{"id":"https://openalex.org/S36798160","display_name":"Geo-spatial Information Science","issn_l":"1009-5020","issn":["1009-5020","1993-5153"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Geo-spatial Information Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7697370264","display_name":null,"funder_award_id":"41601363","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":97,"referenced_works":["https://openalex.org/W221493477","https://openalex.org/W278157659","https://openalex.org/W584423923","https://openalex.org/W1057605271","https://openalex.org/W1506806321","https://openalex.org/W1516830965","https://openalex.org/W1554190159","https://openalex.org/W1970179644","https://openalex.org/W1972293418","https://openalex.org/W1978034823","https://openalex.org/W1988790447","https://openalex.org/W1993585210","https://openalex.org/W2032046865","https://openalex.org/W2040617212","https://openalex.org/W2049827513","https://openalex.org/W2056716515","https://openalex.org/W2058891717","https://openalex.org/W2069921544","https://openalex.org/W2075218710","https://openalex.org/W2079797871","https://openalex.org/W2089052758","https://openalex.org/W2113199674","https://openalex.org/W2118798900","https://openalex.org/W2121025745","https://openalex.org/W2143310516","https://openalex.org/W2152634225","https://openalex.org/W2166917517","https://openalex.org/W2170395949","https://openalex.org/W2177725520","https://openalex.org/W2218042453","https://openalex.org/W2226798190","https://openalex.org/W2489534557","https://openalex.org/W2498672755","https://openalex.org/W2520068811","https://openalex.org/W2564765202","https://openalex.org/W2626024749","https://openalex.org/W2750302842","https://openalex.org/W2756843371","https://openalex.org/W2771841295","https://openalex.org/W2792058876","https://openalex.org/W2792900864","https://openalex.org/W2798476254","https://openalex.org/W2807841289","https://openalex.org/W2884474920","https://openalex.org/W2890606140","https://openalex.org/W2894712623","https://openalex.org/W2895942690","https://openalex.org/W2909496043","https://openalex.org/W2911964244","https://openalex.org/W2913229076","https://openalex.org/W2946644377","https://openalex.org/W2964799253","https://openalex.org/W2988560153","https://openalex.org/W2990138404","https://openalex.org/W3005378446","https://openalex.org/W3038052368","https://openalex.org/W3103787556","https://openalex.org/W3116389085","https://openalex.org/W3122664765","https://openalex.org/W3125515083","https://openalex.org/W3126087996","https://openalex.org/W3150273748","https://openalex.org/W3159649695","https://openalex.org/W3161960687","https://openalex.org/W3192383278","https://openalex.org/W3207064546","https://openalex.org/W3211350324","https://openalex.org/W4213263128","https://openalex.org/W4214827030","https://openalex.org/W4233760599","https://openalex.org/W4254120667","https://openalex.org/W4280624995","https://openalex.org/W4281812774","https://openalex.org/W4282043197","https://openalex.org/W4283776488","https://openalex.org/W4285794683","https://openalex.org/W4295046169","https://openalex.org/W4296311983","https://openalex.org/W4320526431","https://openalex.org/W4322768901","https://openalex.org/W4323543094","https://openalex.org/W4376958960","https://openalex.org/W4381611900","https://openalex.org/W4385128182","https://openalex.org/W4388152217","https://openalex.org/W4390344985","https://openalex.org/W4390891332","https://openalex.org/W4391385336","https://openalex.org/W4391786300","https://openalex.org/W4392095976","https://openalex.org/W4393910323","https://openalex.org/W4396555440","https://openalex.org/W4400134761","https://openalex.org/W4403515659","https://openalex.org/W4407027175","https://openalex.org/W4409194480","https://openalex.org/W6629510986"],"related_works":["https://openalex.org/W4232403550","https://openalex.org/W623607250","https://openalex.org/W4245429118","https://openalex.org/W4205110281","https://openalex.org/W4212927854","https://openalex.org/W4211151614","https://openalex.org/W4244798043","https://openalex.org/W4361866086","https://openalex.org/W4251969024","https://openalex.org/W4250793136"],"abstract_inverted_index":{"In":[0],"machine":[1,33],"learning-based":[2,34],"fractional":[3,7,53,72,90,102,128,147,257,281],"cover":[4,8,54,73,91,103,129,148,164,258,282],"estimation,":[5,259],"the":[6,19,22,30,52,76,87,95,100,109,120,125,132,136,142,146,151,155,159,183,190,196,239,245,250,254,275],"distribution":[9,55,74,97,111],"in":[10,48,56,75,154,253,280],"training":[11,37,57,77,137,156,270],"samples":[12,58],"critically":[13],"influences":[14],"model":[15,278],"construction":[16],"and,":[17],"consequently":[18],"accuracy":[20,88,173,194,217,255],"of":[21,32,89,104,127,150,213,241,249,256,268,277],"estimations.":[23],"While":[24],"some":[25],"studies":[26],"have":[27],"descriptively":[28],"compared":[29],"accuracies":[31],"estimations":[35],"across":[36],"sets":[38],"derived":[39],"from":[40],"different":[41],"sampling":[42],"methods,":[43],"a":[44],"significant":[45],"gap":[46,67],"remains":[47],"quantitatively":[49],"analyzing":[50],"how":[51],"affects":[59],"accuracy.":[60],"This":[61],"study":[62],"aims":[63],"to":[64,98,263],"bridge":[65],"this":[66],"by":[68],"introducing":[69],"descriptors":[70,85,117,215],"for":[71,112,131],"set":[78,157],"and":[79,86,108,138,141,186,188,193,206,225,235,271],"establishing":[80],"mathematical":[81],"relationships":[82,181],"between":[83,135,182,189],"these":[84,214,242],"estimation.":[92,283],"We":[93],"employed":[94],"Dirichlet":[96],"characterize":[99],"joint":[101],"multiple":[105],"land":[106],"classes":[107],"Beta":[110],"single-class":[113],"cover.":[114],"Subsequently,":[115],"two":[116],"were":[118,200,218],"developed:":[119],"Kullback-Leibler":[121],"(KL)":[122],"divergence,":[123,199],"measuring":[124],"similarity":[126],"distributions":[130,149],"target":[133,152],"class":[134,153],"test":[139,178,272],"sets,":[140,273],"geometric":[143,191],"angle,":[144],"representing":[145],"at":[158,195],"same":[160,197],"KL":[161,184,198,251],"divergence.":[162],"Fractional":[163],"estimation":[165],"was":[166],"performed":[167],"using":[168,202,221,232],"random":[169],"forest":[170],"regression,":[171],"with":[172],"assessed":[174],"on":[175,216],"an":[176],"independent":[177],"set.":[179],"The":[180,210],"divergence":[185,252],"accuracy,":[187],"angle":[192],"modeled":[201],"univariate":[203],"linear":[204],"models":[205],"harmonic":[207,223],"models,":[208],"respectively.":[209],"combined":[211],"effects":[212],"further":[219],"analyzed":[220],"coupled":[222],"analysis":[224],"generalized":[226],"additive":[227],"models.":[228,243],"Our":[229],"experimental":[230],"results,":[231],"both":[233,269],"simulated":[234],"real":[236],"data,":[237],"demonstrated":[238],"effectiveness":[240],"Given":[244],"strong":[246],"explanatory":[247],"power":[248],"we":[260],"encourage":[261],"researchers":[262],"report":[264],"detailed":[265],"statistical":[266],"information":[267],"enriching":[274],"understanding":[276],"performance":[279]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-15T08:34:33.830935","created_date":"2025-10-10T00:00:00"}
