{"id":"https://openalex.org/W2771397190","doi":"https://doi.org/10.1109/igarss.2017.8128073","title":"Monitoring of disturbed land based on convolution neural network","display_name":"Monitoring of disturbed land based on convolution neural network","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2771397190","doi":"https://doi.org/10.1109/igarss.2017.8128073","mag":"2771397190"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2017.8128073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8128073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057518342","display_name":"Tao Sun","orcid":"https://orcid.org/0000-0001-5277-8699"},"institutions":[{"id":"https://openalex.org/I4210092032","display_name":"China Institute of Water Resources and Hydropower Research","ror":"https://ror.org/00m4czf33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092032"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tao Sun","raw_affiliation_strings":["China Institute of Water Resources and Hydropower Research"],"affiliations":[{"raw_affiliation_string":"China Institute of Water Resources and Hydropower Research","institution_ids":["https://openalex.org/I4210092032"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103019736","display_name":"Yu Zhao","orcid":"https://orcid.org/0000-0002-5916-585X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yu Zhao","raw_affiliation_strings":["Beijing Soil and Water Conservation Center"],"affiliations":[{"raw_affiliation_string":"Beijing Soil and Water Conservation Center","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041685800","display_name":"Changjun Liu","orcid":"https://orcid.org/0000-0003-4146-9510"},"institutions":[{"id":"https://openalex.org/I4210092032","display_name":"China Institute of Water Resources and Hydropower Research","ror":"https://ror.org/00m4czf33","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210092032"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changjun Liu","raw_affiliation_strings":["China Institute of Water Resources and Hydropower Research"],"affiliations":[{"raw_affiliation_string":"China Institute of Water Resources and Hydropower Research","institution_ids":["https://openalex.org/I4210092032"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019302461","display_name":"Gang Fu","orcid":"https://orcid.org/0000-0001-8443-4604"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Fu","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058594445","display_name":"Zhou Rong","orcid":"https://orcid.org/0000-0003-3542-7453"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rong Zhou","raw_affiliation_strings":["Beijing Soil and Water Conservation Center"],"affiliations":[{"raw_affiliation_string":"Beijing Soil and Water Conservation Center","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001840961","display_name":"Fangxiao Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fangxiao Chen","raw_affiliation_strings":["Beijing Soil and Water Conservation Center"],"affiliations":[{"raw_affiliation_string":"Beijing Soil and Water Conservation Center","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026820435","display_name":"Daming Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daming Lu","raw_affiliation_strings":["Beijing Soil and Water Conservation Center"],"affiliations":[{"raw_affiliation_string":"Beijing Soil and Water Conservation Center","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012489033","display_name":"Yaguang Gong","orcid":"https://orcid.org/0009-0009-6502-9262"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yaguang Gong","raw_affiliation_strings":["Beijing Soil and Water Conservation Center"],"affiliations":[{"raw_affiliation_string":"Beijing Soil and Water Conservation Center","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038197875","display_name":"Wenbo Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenbo Fu","raw_affiliation_strings":["Huazhong University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100435848","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0002-0961-0441"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["Huazhong University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5057518342"],"corresponding_institution_ids":["https://openalex.org/I4210092032"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11004654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"7","issue":null,"first_page":"4790","last_page":"4793"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9629999995231628,"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"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9629999995231628,"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"}},{"id":"https://openalex.org/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9448000192642212,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13717","display_name":"Advanced Algorithms and Applications","score":0.9447000026702881,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7449884414672852},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6522833704948425},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.6499241590499878},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6484067440032959},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43131890892982483},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.421497642993927},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.4163849949836731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36898329854011536},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07062855362892151},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.06655919551849365},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.06417426466941833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7449884414672852},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6522833704948425},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.6499241590499878},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6484067440032959},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43131890892982483},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.421497642993927},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.4163849949836731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36898329854011536},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07062855362892151},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.06655919551849365},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.06417426466941833}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2017.8128073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8128073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W1973711118","https://openalex.org/W2153366199","https://openalex.org/W2359185941"],"related_works":["https://openalex.org/W4399671601","https://openalex.org/W1992962589","https://openalex.org/W3032871857","https://openalex.org/W1743191351","https://openalex.org/W3104633800","https://openalex.org/W3023567978","https://openalex.org/W3044778482","https://openalex.org/W230091440","https://openalex.org/W3040494141","https://openalex.org/W2964954556"],"abstract_inverted_index":{"With":[0],"the":[1,46,50,66,73,83,86,89,101,106,114,123],"acceleration":[2],"of":[3,49,75,78,85,88,105,116,125,129],"China's":[4],"modernization,":[5],"soil":[6],"erosion":[7],"caused":[8],"by":[9],"illegal":[10],"activities":[11],"in":[12,127],"production":[13],"and":[14,21,24,55,103,110],"construction":[15,52],"projects":[16],"is":[17,26,120,132],"becoming":[18],"serious.":[19],"Timely":[20],"effective":[22],"monitoring":[23,29,77,128],"supervision":[25],"necessary.":[27],"Traditional":[28],"methods":[30],"have":[31],"many":[32],"shortcomings,":[33],"such":[34],"as":[35],"long":[36],"period,":[37],"limited":[38,40],"precision,":[39],"terrain.":[41],"So":[42],"it":[43],"can't":[44],"demonstrate":[45],"real":[47],"situation":[48],"project":[51],"area":[53],"timely":[54],"effectively.":[56],"This":[57],"paper":[58],"attempts":[59],"to":[60,71],"apply":[61],"remote":[62],"sensing":[63],"technique,":[64],"combining":[65],"Convolution":[67],"Neural":[68],"Network(CNN)":[69],"method,":[70],"achieve":[72],"purpose":[74],"intelligent":[76],"disturbed":[79],"lands.":[80],"By":[81],"investigating":[82],"effect":[84],"application":[87,124],"convolutional":[90],"neural":[91],"network":[92],"model":[93,107],"with":[94,113],"different":[95],"training":[96,117],"volumes,":[97],"results":[98],"showing":[99],"that":[100,122],"accuracy":[102],"efficiency":[104],"are":[108],"more":[109,111],"high":[112],"increase":[115],"volumes.":[118],"It":[119],"proved":[121],"CNN":[126],"land":[130],"disturbance":[131],"effective.":[133]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
