{"id":"https://openalex.org/W4318484122","doi":"https://doi.org/10.3390/rs15030750","title":"Comparing Machine Learning Algorithms for Pixel/Object-Based Classifications of Semi-Arid Grassland in Northern China Using Multisource Medium Resolution Imageries","display_name":"Comparing Machine Learning Algorithms for Pixel/Object-Based Classifications of Semi-Arid Grassland in Northern China Using Multisource Medium Resolution Imageries","publication_year":2023,"publication_date":"2023-01-28","ids":{"openalex":"https://openalex.org/W4318484122","doi":"https://doi.org/10.3390/rs15030750"},"language":"en","primary_location":{"id":"doi:10.3390/rs15030750","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15030750","pdf_url":"https://www.mdpi.com/2072-4292/15/3/750/pdf?version=1674891325","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/15/3/750/pdf?version=1674891325","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008181168","display_name":"Nitu Wu","orcid":"https://orcid.org/0000-0001-8724-7521"},"institutions":[{"id":"https://openalex.org/I120379545","display_name":"Inner Mongolia Agricultural University","ror":"https://ror.org/015d0jq83","country_code":"CN","type":"education","lineage":["https://openalex.org/I120379545"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nitu Wu","raw_affiliation_strings":["Key Laboratory of Grassland Resources of the Ministry of Education, College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010011, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Grassland Resources of the Ministry of Education, College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010011, China","institution_ids":["https://openalex.org/I120379545"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037552669","display_name":"Lu\u00eds Guilherme Teixeira Crusiol","orcid":"https://orcid.org/0000-0002-2387-964X"},"institutions":[{"id":"https://openalex.org/I199691007","display_name":"Brazilian Agricultural Research Corporation","ror":"https://ror.org/0482b5b22","country_code":"BR","type":"government","lineage":["https://openalex.org/I199691007"]},{"id":"https://openalex.org/I4210156828","display_name":"Agricultural Research Corporation","ror":"https://ror.org/0590dv991","country_code":"SD","type":"nonprofit","lineage":["https://openalex.org/I4210156828"]}],"countries":["BR","SD"],"is_corresponding":false,"raw_author_name":"Lu\u00eds Guilherme Teixeira Crusiol","raw_affiliation_strings":["Embrapa Soja (National Soybean Research Center\u2014Brazilian Agricultural Research Corporation), Londrina 86001-970, Brazil","Embrapa Soja (National Soybean Research Center-Brazilian Agricultural Research Corporation), Londrina 86001-970, Brazil"],"affiliations":[{"raw_affiliation_string":"Embrapa Soja (National Soybean Research Center\u2014Brazilian Agricultural Research Corporation), Londrina 86001-970, Brazil","institution_ids":["https://openalex.org/I199691007","https://openalex.org/I4210156828"]},{"raw_affiliation_string":"Embrapa Soja (National Soybean Research Center-Brazilian Agricultural Research Corporation), Londrina 86001-970, Brazil","institution_ids":["https://openalex.org/I199691007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046553993","display_name":"Guixiang Liu","orcid":"https://orcid.org/0000-0003-0033-9824"},"institutions":[{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210156847","display_name":"Institute of Grassland Research","ror":"https://ror.org/04vmpjr08","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987","https://openalex.org/I4210156847"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guixiang Liu","raw_affiliation_strings":["Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot 010010, China"],"affiliations":[{"raw_affiliation_string":"Institute of Grassland Research, Chinese Academy of Agricultural Sciences, Hohhot 010010, China","institution_ids":["https://openalex.org/I4210156847","https://openalex.org/I4210138501"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020538176","display_name":"Deji Wuyun","orcid":"https://orcid.org/0000-0001-5890-1758"},"institutions":[{"id":"https://openalex.org/I4210108914","display_name":"Institute of Agricultural Resources and Regional Planning","ror":"https://ror.org/01nrzdp21","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210108914","https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]},{"id":"https://openalex.org/I4210138501","display_name":"Chinese Academy of Agricultural Sciences","ror":"https://ror.org/0313jb750","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210138501","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deji Wuyun","raw_affiliation_strings":["Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China"],"affiliations":[{"raw_affiliation_string":"Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China","institution_ids":["https://openalex.org/I4210108914","https://openalex.org/I4210138501"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030835959","display_name":"Guodong Han","orcid":"https://orcid.org/0000-0002-9311-3607"},"institutions":[{"id":"https://openalex.org/I120379545","display_name":"Inner Mongolia Agricultural University","ror":"https://ror.org/015d0jq83","country_code":"CN","type":"education","lineage":["https://openalex.org/I120379545"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guodong Han","raw_affiliation_strings":["Key Laboratory of Grassland Resources of the Ministry of Education, College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010011, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Grassland Resources of the Ministry of Education, College of Grassland, Resources and Environment, Inner Mongolia Agricultural University, Hohhot 010011, China","institution_ids":["https://openalex.org/I120379545"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5030835959"],"corresponding_institution_ids":["https://openalex.org/I120379545"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":5.3971,"has_fulltext":true,"cited_by_count":22,"citation_normalized_percentile":{"value":0.95719015,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"15","issue":"3","first_page":"750","last_page":"750"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9986000061035156,"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":0.9986000061035156,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9839000105857849,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.6934400796890259},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6875312328338623},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.64913409948349},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6066830158233643},{"id":"https://openalex.org/keywords/cohens-kappa","display_name":"Cohen's kappa","score":0.5676709413528442},{"id":"https://openalex.org/keywords/grassland","display_name":"Grassland","score":0.5036711096763611},{"id":"https://openalex.org/keywords/arid","display_name":"Arid","score":0.4995763301849365},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4923490285873413},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4731648564338684},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4703863859176636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4617834687232971},{"id":"https://openalex.org/keywords/spectral-bands","display_name":"Spectral bands","score":0.4457443952560425},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42972078919410706},{"id":"https://openalex.org/keywords/multispectral-pattern-recognition","display_name":"Multispectral pattern recognition","score":0.42956677079200745},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2358425259590149},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.23249202966690063},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1444174349308014},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12685814499855042}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.6934400796890259},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6875312328338623},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.64913409948349},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6066830158233643},{"id":"https://openalex.org/C163864269","wikidata":"https://www.wikidata.org/wiki/Q1107106","display_name":"Cohen's kappa","level":2,"score":0.5676709413528442},{"id":"https://openalex.org/C2775835988","wikidata":"https://www.wikidata.org/wiki/Q1006733","display_name":"Grassland","level":2,"score":0.5036711096763611},{"id":"https://openalex.org/C150772632","wikidata":"https://www.wikidata.org/wiki/Q1330709","display_name":"Arid","level":2,"score":0.4995763301849365},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4923490285873413},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4731648564338684},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4703863859176636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4617834687232971},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.4457443952560425},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42972078919410706},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.42956677079200745},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2358425259590149},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.23249202966690063},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1444174349308014},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12685814499855042},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15030750","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15030750","pdf_url":"https://www.mdpi.com/2072-4292/15/3/750/pdf?version=1674891325","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f8d7f6d0d8d54ae9b76ebe2ad36ddd34","is_oa":true,"landing_page_url":"https://doaj.org/article/f8d7f6d0d8d54ae9b76ebe2ad36ddd34","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":"Remote Sensing, Vol 15, Iss 3, p 750 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/3/750/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15030750","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 15; Issue 3; Pages: 750","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15030750","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15030750","pdf_url":"https://www.mdpi.com/2072-4292/15/3/750/pdf?version=1674891325","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5986206885","display_name":null,"funder_award_id":"IRT_17R59","funder_id":"https://openalex.org/F4320321106","funder_display_name":"Ministry of Education of the People's Republic of China"}],"funders":[{"id":"https://openalex.org/F4320321106","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4318484122.pdf"},"referenced_works_count":74,"referenced_works":["https://openalex.org/W1980146641","https://openalex.org/W1991129553","https://openalex.org/W1994230782","https://openalex.org/W1996777760","https://openalex.org/W2002258037","https://openalex.org/W2002576912","https://openalex.org/W2005156666","https://openalex.org/W2010885577","https://openalex.org/W2023045419","https://openalex.org/W2028276885","https://openalex.org/W2032536435","https://openalex.org/W2044465660","https://openalex.org/W2044609898","https://openalex.org/W2046708214","https://openalex.org/W2054284355","https://openalex.org/W2054412564","https://openalex.org/W2059623224","https://openalex.org/W2063623478","https://openalex.org/W2077509829","https://openalex.org/W2082081125","https://openalex.org/W2084413241","https://openalex.org/W2084668217","https://openalex.org/W2116409775","https://openalex.org/W2122111042","https://openalex.org/W2127348003","https://openalex.org/W2132424470","https://openalex.org/W2143426320","https://openalex.org/W2143682935","https://openalex.org/W2152334070","https://openalex.org/W2166516820","https://openalex.org/W2168809519","https://openalex.org/W2194775991","https://openalex.org/W2247062920","https://openalex.org/W2297871613","https://openalex.org/W2525592260","https://openalex.org/W2753671860","https://openalex.org/W2788079077","https://openalex.org/W2887816568","https://openalex.org/W2906150950","https://openalex.org/W2911964244","https://openalex.org/W2913586827","https://openalex.org/W2914169501","https://openalex.org/W2969662039","https://openalex.org/W2969945043","https://openalex.org/W2978632912","https://openalex.org/W2979509742","https://openalex.org/W2985495555","https://openalex.org/W3006233966","https://openalex.org/W3015526299","https://openalex.org/W3047353780","https://openalex.org/W3088162569","https://openalex.org/W3092609815","https://openalex.org/W3126691167","https://openalex.org/W3144605824","https://openalex.org/W3163231391","https://openalex.org/W3167864888","https://openalex.org/W3170002058","https://openalex.org/W3174961191","https://openalex.org/W3187443852","https://openalex.org/W3196108668","https://openalex.org/W3197833481","https://openalex.org/W3205027094","https://openalex.org/W3214418685","https://openalex.org/W4200415528","https://openalex.org/W4206336768","https://openalex.org/W4213113494","https://openalex.org/W4239510810","https://openalex.org/W4283024644","https://openalex.org/W6645190923","https://openalex.org/W6650946648","https://openalex.org/W6748504360","https://openalex.org/W6753958927","https://openalex.org/W6784204135","https://openalex.org/W6801380442"],"related_works":["https://openalex.org/W2128126485","https://openalex.org/W2969881582","https://openalex.org/W4382563209","https://openalex.org/W2905390890","https://openalex.org/W2160357252","https://openalex.org/W2136117185","https://openalex.org/W2073959551","https://openalex.org/W2800266504","https://openalex.org/W2090253159","https://openalex.org/W2035433763"],"abstract_inverted_index":{"Knowledge":[0],"of":[1,38,59,79,116,176],"grassland":[2,13,52,89,262],"classification":[3,53,94],"in":[4,46,55,163,224,252],"a":[5,148],"timely":[6],"and":[7,16,76,92,108,132,154,173,178,185,194,198,201,217,232],"accurate":[8],"manner":[9],"is":[10,24],"essential":[11],"for":[12,27,86],"resource":[14],"management":[15],"utilization.":[17],"Although":[18],"remote":[19],"sensing":[20],"imagery":[21],"analysis":[22],"technology":[23],"widely":[25,81],"applied":[26],"land":[28,151],"cover":[29,152],"classification,":[30,166,183,212,226,254],"few":[31],"studies":[32],"have":[33],"systematically":[34],"compared":[35],"the":[36,51,66,73,77,117,144,159,164,169,239,261],"performance":[37],"commonly":[39],"used":[40,82],"methods":[41,95,146],"on":[42],"semi-arid":[43,88],"native":[44],"grasslands":[45],"northern":[47],"China.":[48],"This":[49],"renders":[50],"work":[54],"this":[56,64],"region":[57],"devoid":[58],"applicable":[60],"technical":[61],"references.":[62],"In":[63,181,210],"study,":[65],"central":[67],"Xilingol":[68],"(China)":[69],"was":[70],"selected":[71],"as":[72,248],"study":[74],"area,":[75],"performances":[78],"four":[80],"machine":[83,103],"learning":[84],"algorithms":[85],"mapping":[87],"under":[90],"pixel-based":[91,160,165,211],"object-based":[93,145,182,225,253],"were":[96,114,235,246],"compared:":[97],"random":[98],"forest":[99],"(RF),":[100],"support":[101],"vector":[102],"(SVM),":[104],"k-nearest":[105],"neighbor":[106],"(KNN),":[107],"naive":[109],"Bayes":[110],"(NB).":[111],"The":[112,139],"features":[113,219,234],"composed":[115],"Landsat":[118],"OLI":[119],"multispectral":[120,213,227],"data,":[121],"spectral":[122,215,229],"indices,":[123,216,230],"Sentinel":[124,242],"SAR":[125,244],"C":[126],"bands,":[127,214,228],"topographic,":[128],"position":[129,233],"(coordinates),":[130],"geometric,":[131],"grey-level":[133],"co-occurrence":[134],"matrix":[135],"(GLCM)":[136],"texture":[137],"variables.":[138],"findings":[140],"demonstrated":[141],"that":[142,241],"(1)":[143],"depicted":[147],"more":[149,236],"realistic":[150],"distribution":[153],"had":[155],"greater":[156],"accuracy":[157],"than":[158,206],"methods;":[161],"(2)":[162],"RF":[167,184],"performed":[168,203],"best,":[170],"with":[171,192],"OA":[172,193],"Kappa":[174,195],"values":[175],"96.32%":[177],"0.95,":[179],"respectively.":[180],"SVM":[186],"presented":[187],"no":[188,257],"statistically":[189],"different":[190],"predictions,":[191],"exceeding":[196],"97.5%":[197],"0.97,":[199],"respectively,":[200],"both":[202],"significantly":[204,220],"better":[205],"other":[207],"algorithms.":[208],"(3)":[209],"geographic":[218],"distinguished":[221],"grassland,":[222],"whereas,":[223],"elevation,":[231],"prominent.":[237],"Despite":[238],"fact":[240],"1":[243],"variables":[245],"chosen":[247],"an":[249],"effective":[250],"variable":[251],"they":[255],"made":[256],"significant":[258],"contribution":[259],"to":[260],"distinction.":[263]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":9}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2023-01-30T00:00:00"}