{"id":"https://openalex.org/W2003793388","doi":"https://doi.org/10.1109/igarss.2010.5652887","title":"Forest biomass estimation in northeastern China using ALOS PALSAR data combined radiative transfer model","display_name":"Forest biomass estimation in northeastern China using ALOS PALSAR data combined radiative transfer model","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2003793388","doi":"https://doi.org/10.1109/igarss.2010.5652887","mag":"2003793388"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2010.5652887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2010.5652887","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101581220","display_name":"Zhifeng Guo","orcid":"https://orcid.org/0000-0003-0937-7667"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhifeng Guo","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Beijing Normal University, Beijing, China","State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, China#TAB#","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111912245","display_name":"Wenjian Ni","orcid":"https://orcid.org/0000-0003-1611-4582"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjian Ni","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Beijing Normal University, Beijing, China","State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, China#TAB#","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101891404","display_name":"Guoqing Sun","orcid":"https://orcid.org/0000-0002-5388-6402"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guoqing Sun","raw_affiliation_strings":["Department of Geography, University of Maryland, MD, USA","Department of Geography, University of Maryland, 20742, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, University of Maryland, MD, USA","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Department of Geography, University of Maryland, 20742, USA","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1497","last_page":"1500"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9991999864578247,"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":0.9991999864578247,"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/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.9991000294685364,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9955999851226807,"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/remote-sensing","display_name":"Remote sensing","score":0.5973769426345825},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5934783220291138},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5217365026473999},{"id":"https://openalex.org/keywords/forest-inventory","display_name":"Forest inventory","score":0.519159197807312},{"id":"https://openalex.org/keywords/lookup-table","display_name":"Lookup table","score":0.4829672873020172},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.4249264597892761},{"id":"https://openalex.org/keywords/biomass","display_name":"Biomass (ecology)","score":0.415168821811676},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.2723236083984375},{"id":"https://openalex.org/keywords/forest-management","display_name":"Forest management","score":0.2466382086277008},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21986934542655945},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2020326554775238},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.19432449340820312},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.13595125079154968},{"id":"https://openalex.org/keywords/agroforestry","display_name":"Agroforestry","score":0.12041029334068298}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5973769426345825},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5934783220291138},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5217365026473999},{"id":"https://openalex.org/C147103442","wikidata":"https://www.wikidata.org/wiki/Q1423188","display_name":"Forest inventory","level":3,"score":0.519159197807312},{"id":"https://openalex.org/C134835016","wikidata":"https://www.wikidata.org/wiki/Q690265","display_name":"Lookup table","level":2,"score":0.4829672873020172},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.4249264597892761},{"id":"https://openalex.org/C115540264","wikidata":"https://www.wikidata.org/wiki/Q2945560","display_name":"Biomass (ecology)","level":2,"score":0.415168821811676},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2723236083984375},{"id":"https://openalex.org/C28631016","wikidata":"https://www.wikidata.org/wiki/Q372561","display_name":"Forest management","level":2,"score":0.2466382086277008},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21986934542655945},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2020326554775238},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.19432449340820312},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.13595125079154968},{"id":"https://openalex.org/C54286561","wikidata":"https://www.wikidata.org/wiki/Q397350","display_name":"Agroforestry","level":1,"score":0.12041029334068298},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2010.5652887","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2010.5652887","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2027768728","https://openalex.org/W2044927495","https://openalex.org/W2085288093","https://openalex.org/W2103269515","https://openalex.org/W2105781415","https://openalex.org/W2135902118","https://openalex.org/W2144883091","https://openalex.org/W2146097313","https://openalex.org/W2149406408","https://openalex.org/W2162307584","https://openalex.org/W2169402217","https://openalex.org/W4256689006","https://openalex.org/W6683720778"],"related_works":["https://openalex.org/W2798215405","https://openalex.org/W2990962948","https://openalex.org/W2084169748","https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W2127529229","https://openalex.org/W2359776416","https://openalex.org/W2047973478","https://openalex.org/W2355515259","https://openalex.org/W1985233539"],"abstract_inverted_index":{"Forest":[0],"above":[1],"ground":[2,130],"biomass":[3,37,121,176],"(AGB)":[4],"is":[5,18,45,48,193],"an":[6],"important":[7],"variable":[8],"for":[9,20],"evaluating":[10],"ecosystem":[11],"function":[12],"and":[13,26,47,66,96,110,137,159],"structure":[14],"across":[15],"landscape,":[16],"which":[17],"necessary":[19],"studying":[21],"forest":[22,30,36,42,63,69,78,84,124,165,180],"productivity,":[23],"carbon":[24],"balance":[25],"nutrient":[27],"allocation":[28],"in":[29],"ecosystem.":[31],"In":[32],"this":[33,90],"study,":[34],"a":[35,77],"estimate":[38],"technique":[39],"based":[40,88],"on":[41,89],"backscattering":[43,71,81],"database":[44,91],"developed,":[46],"used":[49,114],"to":[50,75,115,132],"retrieve":[51],"AGB":[52,85,142],"of":[53,104,140,188],"Changbai":[54],"mountain":[55],"area":[56,192],"from":[57,123,148],"ALOS":[58],"PALSAR":[59,149],"dual-polarization":[60],"data.":[61],"The":[62,120,144,168],"growth":[64],"model":[65,72],"the":[67,117,134,138,141,155,174,183,189],"3D":[68],"radar":[70,80],"were":[73,113],"combined":[74],"build":[76],"multi-polarization":[79],"database.":[82],"Then":[83],"was":[86,127],"estimated":[87],"using":[92],"statistic":[93],"regression":[94,157],"method":[95,158,163,172],"look":[97],"up":[98],"table":[99],"(LUT)":[100],"method.":[101],"Two":[102],"types":[103],"LUT":[105,162,171],"searching":[106],"methods":[107,136],"(nearest":[108],"distance":[109,111,161,169],"threshold)":[112],"find":[116],"accurate":[118],"results.":[119],"retrieved":[122],"inventory":[125,181],"data":[126,151],"taken":[128],"as":[129],"truth":[131],"evaluate":[133],"inversion":[135,145],"precision":[139],"estimation.":[143],"results":[146],"derived":[147],"FBD":[150],"shows":[152],"that":[153],"both":[154],"statistical":[156],"nearest":[160],"underestimate":[164],"aboveground":[166],"biomass.":[167],"threshold":[170],"gives":[173],"better":[175],"estimation":[177],"compared":[178],"with":[179],"data,":[182],"mean":[184],"absolute":[185],"error":[186],"(MAE)":[187],"whole":[190],"research":[191],"less":[194],"than":[195],"10":[196],"Ton/ha.":[197]},"counts_by_year":[{"year":2016,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}