{"id":"https://openalex.org/W2966041446","doi":"https://doi.org/10.3390/rs11151786","title":"Progressive Cascaded Convolutional Neural Networks for Single Tree Detection with Google Earth Imagery","display_name":"Progressive Cascaded Convolutional Neural Networks for Single Tree Detection with Google Earth Imagery","publication_year":2019,"publication_date":"2019-07-30","ids":{"openalex":"https://openalex.org/W2966041446","doi":"https://doi.org/10.3390/rs11151786","mag":"2966041446"},"language":"en","primary_location":{"id":"doi:10.3390/rs11151786","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11151786","pdf_url":"https://www.mdpi.com/2072-4292/11/15/1786/pdf?version=1564743222","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/2072-4292/11/15/1786/pdf?version=1564743222","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100753296","display_name":"Tianyang Dong","orcid":"https://orcid.org/0000-0002-2231-1569"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyang Dong","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102665107","display_name":"Yuqi Shen","orcid":"https://orcid.org/0009-0008-9114-8743"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqi Shen","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100409868","display_name":"Jian Zhang","orcid":"https://orcid.org/0000-0001-6520-9006"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Zhang","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087136560","display_name":"Ye Yang","orcid":"https://orcid.org/0000-0003-2606-5059"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Ye","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030881288","display_name":"Jing Fan","orcid":"https://orcid.org/0000-0001-8777-4604"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jing Fan","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5030881288"],"corresponding_institution_ids":["https://openalex.org/I55712492"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.8941,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.71446893,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":"11","issue":"15","first_page":"1786","last_page":"1786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T13568","display_name":"Wood and Agarwood Research","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9965000152587891,"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/computer-science","display_name":"Computer science","score":0.7932432889938354},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6987622380256653},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6171001195907593},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6066602468490601},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5060185790061951},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.47966980934143066},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4513043165206909},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4430176913738251},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4210105538368225},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4159530997276306},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3296738862991333},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10480725765228271},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09535801410675049}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7932432889938354},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6987622380256653},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6171001195907593},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6066602468490601},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5060185790061951},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.47966980934143066},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4513043165206909},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4430176913738251},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4210105538368225},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4159530997276306},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3296738862991333},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10480725765228271},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09535801410675049},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs11151786","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11151786","pdf_url":"https://www.mdpi.com/2072-4292/11/15/1786/pdf?version=1564743222","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:8cf96de9fcea41d28e25d71ea8ef6bb5","is_oa":true,"landing_page_url":"https://doaj.org/article/8cf96de9fcea41d28e25d71ea8ef6bb5","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 11, Iss 15, p 1786 (2019)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/11/15/1786/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs11151786","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","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs11151786","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11151786","pdf_url":"https://www.mdpi.com/2072-4292/11/15/1786/pdf?version=1564743222","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":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.49000000953674316},{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.41999998688697815}],"awards":[{"id":"https://openalex.org/G1251679134","display_name":null,"funder_award_id":"No. 61672414","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":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2966041446.pdf","grobid_xml":"https://content.openalex.org/works/W2966041446.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1483870316","https://openalex.org/W1969779781","https://openalex.org/W1970781304","https://openalex.org/W1985333706","https://openalex.org/W2013360540","https://openalex.org/W2014603102","https://openalex.org/W2017949714","https://openalex.org/W2019118234","https://openalex.org/W2027532349","https://openalex.org/W2065447829","https://openalex.org/W2070277296","https://openalex.org/W2090435005","https://openalex.org/W2112739286","https://openalex.org/W2120480077","https://openalex.org/W2144158466","https://openalex.org/W2147842585","https://openalex.org/W2151843154","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2168481151","https://openalex.org/W2187802600","https://openalex.org/W2265127172","https://openalex.org/W2564734887","https://openalex.org/W2565950292","https://openalex.org/W2613718673","https://openalex.org/W2621663019","https://openalex.org/W2625817666","https://openalex.org/W2764034829","https://openalex.org/W2782522152","https://openalex.org/W2964153894","https://openalex.org/W3102619772","https://openalex.org/W6654081142","https://openalex.org/W6713134421","https://openalex.org/W6998817079"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W1972035260","https://openalex.org/W4399188509"],"abstract_inverted_index":{"High-resolution":[0],"remote":[1,41],"sensing":[2,42],"images":[3,43],"can":[4],"not":[5,250],"only":[6,251],"help":[7],"forestry":[8],"administrative":[9],"departments":[10],"achieve":[11],"high-precision":[12],"forest":[13,20,194,263],"resource":[14],"surveys,":[15],"wood":[16],"yield":[17],"estimations":[18],"and":[19,44,61,77,82,109,117,139,152,188,205,213,228,255,285],"mapping":[21],"but":[22,257],"also":[23,258],"provide":[24],"decision-making":[25],"support":[26],"for":[27,75,101],"urban":[28],"greening":[29],"projects.":[30],"Many":[31],"scholars":[32],"have":[33,56],"studied":[34],"ways":[35],"to":[36,115,148,155,160,177,262],"detect":[37,118],"single":[38,52,102,165],"trees":[39],"from":[40],"proposed":[45],"many":[46,57],"detection":[47,54,104,216,246],"methods.":[48,292],"However,":[49],"the":[50,69,73,128,140,144,150,156,162,170,179,186,214,222,244,274],"existing":[51,291],"tree":[53,103,119,166,215],"methods":[55],"errors":[58],"of":[59,72,132,164,172,181,190,218],"commission":[60],"omission":[62],"in":[63,143,197,273],"complex":[64],"scenes,":[65],"close":[66],"values":[67],"on":[68],"digital":[70],"data":[71],"image":[74],"background":[76],"trees,":[78],"unclear":[79],"canopy":[80],"contour":[81],"abnormal":[83],"shape":[84],"caused":[85],"by":[86,282],"illumination":[87],"shadows.":[88],"To":[89,184],"solve":[90],"these":[91],"problems,":[92],"this":[93,126],"paper":[94],"presents":[95],"progressive":[96,112,230],"cascaded":[97,231],"convolutional":[98,225,232],"neural":[99,226,233],"networks":[100,135],"with":[105,121,265,289],"Google":[106],"Earth":[107],"imagery":[108],"adopts":[110],"three":[111,133,193,275],"classification":[113,123],"branches":[114,145],"train":[116],"samples":[120,151],"different":[122,219,266],"difficulties.":[124],"In":[125,168],"method,":[127,192],"feature":[129,157],"extraction":[130,158],"modules":[131],"CNN":[134],"are":[136,235],"progressively":[137],"cascaded,":[138],"network":[141,227],"layer":[142],"determined":[146],"whether":[147],"filter":[149],"feed":[153],"back":[154],"module":[159],"improve":[161,178],"precision":[163,254],"detection.":[167],"addition,":[169],"mechanism":[171],"two-phase":[173],"training":[174],"is":[175,280],"used":[176],"efficiency":[180],"model":[182],"training.":[183],"verify":[185],"validity":[187],"practicability":[189],"our":[191,229,241],"plots":[195,276],"located":[196],"Hangzhou":[198],"City,":[199],"China,":[200],"Phang":[201],"Nga":[202],"Province,":[203],"Thailand":[204],"Florida,":[206],"USA":[207],"were":[208],"selected":[209],"as":[210],"test":[211],"areas,":[212],"results":[217,238],"methods,":[220],"including":[221],"region-growing,":[223],"template-matching,":[224],"network,":[234],"presented.":[236],"The":[237,269],"indicate":[239],"that":[240],"method":[242,249],"has":[243,252,259],"best":[245],"performance.":[247],"Our":[248],"higher":[253],"recall":[256],"good":[260],"robustness":[261],"scenes":[264],"complexity":[267],"levels.":[268],"F1":[270],"measure":[271],"analysis":[272],"was":[277],"81.0%,":[278],"which":[279],"improved":[281],"14.5%,":[283],"18.9%":[284],"5.0%,":[286],"respectively,":[287],"compared":[288],"other":[290]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
