{"id":"https://openalex.org/W4414175883","doi":"https://doi.org/10.1080/17538947.2025.2556235","title":"Multi-KPConv: deep learning-based LiDAR point cloud ground point extraction for complex terrains on the Loess Plateau","display_name":"Multi-KPConv: deep learning-based LiDAR point cloud ground point extraction for complex terrains on the Loess Plateau","publication_year":2025,"publication_date":"2025-09-14","ids":{"openalex":"https://openalex.org/W4414175883","doi":"https://doi.org/10.1080/17538947.2025.2556235"},"language":"en","primary_location":{"id":"doi:10.1080/17538947.2025.2556235","is_oa":true,"landing_page_url":"https://doi.org/10.1080/17538947.2025.2556235","pdf_url":null,"source":{"id":"https://openalex.org/S199162493","display_name":"International Journal of Digital Earth","issn_l":"1753-8947","issn":["1753-8947","1753-8955"],"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":"International Journal of Digital Earth","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1080/17538947.2025.2556235","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110529111","display_name":"Chao Zhu","orcid":"https://orcid.org/0000-0002-5258-4971"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Zhu","raw_affiliation_strings":["Xi'an University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an University of Science and Technology","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087786615","display_name":"Jingxiang Li","orcid":"https://orcid.org/0009-0001-9526-1523"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]},{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Jingxiang Li","raw_affiliation_strings":["University of Waterloo","Xi'an University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Xi'an University of Science and Technology","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100613889","display_name":"Jonathan Li","orcid":"https://orcid.org/0000-0001-7899-0049"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]},{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Jonathan Li","raw_affiliation_strings":["University of Waterloo","Xi'an University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Xi'an University of Science and Technology","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073608789","display_name":"Fuquan Tang","orcid":"https://orcid.org/0009-0002-1057-8175"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fuquan Tang","raw_affiliation_strings":["Ministry of Natural Resources","Xi'an University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ministry of Natural Resources","institution_ids":[]},{"raw_affiliation_string":"Xi'an University of Science and Technology","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023602494","display_name":"Dening Lu","orcid":"https://orcid.org/0000-0003-0316-0299"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Dening Lu","raw_affiliation_strings":["University of Waterloo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100681978","display_name":"Yuguang Wang","orcid":"https://orcid.org/0000-0003-1984-066X"},"institutions":[{"id":"https://openalex.org/I4210124037","display_name":"Chengdu Surveying Geotechnical Research Institute","ror":"https://ror.org/02pk6rm23","country_code":"CN","type":"facility","lineage":["https://openalex.org/I275542036","https://openalex.org/I4210124037"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuguang Wang","raw_affiliation_strings":["Jinan Geotechnical Investigation and Surveying Institute"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jinan Geotechnical Investigation and Surveying Institute","institution_ids":["https://openalex.org/I4210124037"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104196487","display_name":"Junlei Xue","orcid":null},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junlei Xue","raw_affiliation_strings":["Xi'an University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an University of Science and Technology","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101549092","display_name":"Qian Yang","orcid":"https://orcid.org/0000-0001-5519-1092"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Yang","raw_affiliation_strings":["Xi'an University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an University of Science and Technology","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108481279","display_name":"Yu Su","orcid":"https://orcid.org/0000-0003-0685-2768"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Su","raw_affiliation_strings":["Xi'an University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an University of Science and Technology","institution_ids":["https://openalex.org/I110440473"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5073608789"],"corresponding_institution_ids":["https://openalex.org/I110440473"],"apc_list":{"value":2390,"currency":"USD","value_usd":2390},"apc_paid":{"value":2390,"currency":"USD","value_usd":2390},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2094103,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":1.0,"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":1.0,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9912999868392944,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7892000079154968},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.6216999888420105},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6191999912261963},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6013000011444092},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.5385000109672546},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5188000202178955},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4745999872684479},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4555000066757202},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4097000062465668}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7892000079154968},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6216999888420105},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6191999912261963},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6013000011444092},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5877000093460083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5769000053405762},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.5385000109672546},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5188000202178955},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5031999945640564},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4745999872684479},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4555000066757202},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4097000062465668},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.36899998784065247},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.36090001463890076},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3544999957084656},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3431999981403351},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3091999888420105},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3084999918937683},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2980000078678131},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2919999957084656},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.29030001163482666},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2840999960899353},{"id":"https://openalex.org/C185515318","wikidata":"https://www.wikidata.org/wiki/Q22723","display_name":"Loess","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.26759999990463257},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.2630999982357025}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/17538947.2025.2556235","is_oa":true,"landing_page_url":"https://doi.org/10.1080/17538947.2025.2556235","pdf_url":null,"source":{"id":"https://openalex.org/S199162493","display_name":"International Journal of Digital Earth","issn_l":"1753-8947","issn":["1753-8947","1753-8955"],"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":"International Journal of Digital Earth","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9770ebbe8e60487d9695cb0b423d8ee4","is_oa":true,"landing_page_url":"https://doaj.org/article/9770ebbe8e60487d9695cb0b423d8ee4","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":"International Journal of Digital Earth, Vol 18, Iss 2 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/17538947.2025.2556235","is_oa":true,"landing_page_url":"https://doi.org/10.1080/17538947.2025.2556235","pdf_url":null,"source":{"id":"https://openalex.org/S199162493","display_name":"International Journal of Digital Earth","issn_l":"1753-8947","issn":["1753-8947","1753-8955"],"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":"International Journal of Digital Earth","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1362688521","display_name":null,"funder_award_id":"52274168","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":69,"referenced_works":["https://openalex.org/W1986522259","https://openalex.org/W2001014393","https://openalex.org/W2022512855","https://openalex.org/W2033943689","https://openalex.org/W2059803199","https://openalex.org/W2064577520","https://openalex.org/W2156067790","https://openalex.org/W2211722331","https://openalex.org/W2229319020","https://openalex.org/W2281077011","https://openalex.org/W2322716129","https://openalex.org/W2331281248","https://openalex.org/W2436494909","https://openalex.org/W2482292354","https://openalex.org/W2609946960","https://openalex.org/W2770046775","https://openalex.org/W2795281239","https://openalex.org/W2806332096","https://openalex.org/W2810240468","https://openalex.org/W2889895098","https://openalex.org/W2915222188","https://openalex.org/W2920270730","https://openalex.org/W2942454403","https://openalex.org/W2949650786","https://openalex.org/W2952789225","https://openalex.org/W2953358601","https://openalex.org/W2963121255","https://openalex.org/W2963226018","https://openalex.org/W2964253930","https://openalex.org/W2965190089","https://openalex.org/W2972321983","https://openalex.org/W2975950300","https://openalex.org/W2979750740","https://openalex.org/W2990138404","https://openalex.org/W2991443709","https://openalex.org/W2996413211","https://openalex.org/W3007809903","https://openalex.org/W3008485484","https://openalex.org/W3016889634","https://openalex.org/W3042043818","https://openalex.org/W3042189766","https://openalex.org/W3082771827","https://openalex.org/W3092072004","https://openalex.org/W3103830808","https://openalex.org/W3104568842","https://openalex.org/W3122633743","https://openalex.org/W3174562789","https://openalex.org/W3205586691","https://openalex.org/W3210255049","https://openalex.org/W4221163288","https://openalex.org/W4221163325","https://openalex.org/W4236965008","https://openalex.org/W4285791146","https://openalex.org/W4286784083","https://openalex.org/W4289107490","https://openalex.org/W4289730488","https://openalex.org/W4293509836","https://openalex.org/W4297836999","https://openalex.org/W4300807687","https://openalex.org/W4300921873","https://openalex.org/W4313648184","https://openalex.org/W4317107733","https://openalex.org/W4320176508","https://openalex.org/W4361802179","https://openalex.org/W4381513994","https://openalex.org/W4393207075","https://openalex.org/W4393639582","https://openalex.org/W4394628423","https://openalex.org/W4407590893"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"extraction":[1,66],"of":[2,41,171,187],"ground":[3,64,177],"points":[4,178],"from":[5,147],"LiDAR":[6],"point":[7,32,52,65,90,111,140],"clouds":[8,33],"provides":[9],"important":[10,139],"data":[11,122],"for":[12,120],"understanding":[13],"terrain":[14],"changes":[15],"and":[16,137,156,173],"supports":[17],"decision-making":[18],"in":[19,48,152,169,179],"ecological":[20],"disaster":[21],"prevention.":[22],"Recently,":[23],"deep":[24],"learning":[25],"models":[26,168],"have":[27],"been":[28],"used":[29],"to":[30,55,80,102,114,132],"process":[31],"directly,":[34],"with":[35],"a":[36,67,73,108],"focus":[37],"on":[38,88,97,145],"semantic":[39,76,117],"segmentation":[40,77],"urban":[42],"scenes":[43],"using":[44,51],"RGB":[45,57],"features.":[46,141],"However,":[47],"complex":[49,180],"terrains,":[50],"cloud":[53],"images":[54],"generate":[56],"features":[58,95],"often":[59],"introduces":[60],"noise,":[61],"making":[62],"high-precision":[63],"difficult":[68],"task.":[69],"This":[70],"paper":[71],"presents":[72],"new":[74],"point-based":[75],"network,":[78],"Multi-KPConv,":[79],"overcome":[81],"these":[82],"challenges.":[83],"Unlike":[84],"methods":[85],"that":[86,163],"rely":[87],"color":[89],"clouds,":[91],"Multi-KPConv":[92,144,164],"uses":[93],"shallow":[94],"based":[96],"domain":[98],"knowledge":[99],"as":[100,183],"input":[101],"the":[103,125,148,157,184,188],"network.":[104],"The":[105],"network":[106],"employs":[107],"multi-dimensional":[109],"kernel":[110],"convolutional":[112],"architecture":[113],"extract":[115],"high-level":[116],"features,":[118],"allowing":[119],"better":[121],"interpretation.":[123],"Additionally,":[124],"SimAM":[126],"3D":[127],"attention":[128],"mechanism":[129],"is":[130],"integrated":[131],"adaptively":[133],"refine":[134],"feature":[135],"contributions":[136],"highlight":[138],"We":[142],"evaluate":[143],"datasets":[146],"Dafosi":[149],"mining":[150],"area":[151],"China\u2019s":[153],"Loess":[154,189],"Plateau":[155],"STPLS3D":[158],"dataset.":[159],"Experimental":[160],"results":[161],"show":[162],"outperforms":[165],"current":[166],"state-of-the-art":[167],"terms":[170],"generalization":[172],"robustness,":[174],"effectively":[175],"extracting":[176],"terrain,":[181],"such":[182],"gully":[185],"areas":[186],"Plateau.":[190]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
