{"id":"https://openalex.org/W2547498053","doi":"https://doi.org/10.1109/igarss.2016.7729507","title":"Surface reflectance auto retrieval model based on hyperspectral remotely sensed images","display_name":"Surface reflectance auto retrieval model based on hyperspectral remotely sensed images","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2547498053","doi":"https://doi.org/10.1109/igarss.2016.7729507","mag":"2547498053"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2016.7729507","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7729507","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","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/A5088740924","display_name":"Hang Yang","orcid":"https://orcid.org/0000-0001-6027-1337"},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"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":"Hang Yang","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, Beijing, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I4210128053","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115603648","display_name":"Lifu Zhang","orcid":"https://orcid.org/0000-0002-3533-9966"},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"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":"Lifu Zhang","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, Beijing, CN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, Beijing, CN","institution_ids":["https://openalex.org/I4210128053","https://openalex.org/I4210166112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039314517","display_name":"Xun Jian","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"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":"Xun Jian","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing","institution_ids":["https://openalex.org/I4210128053","https://openalex.org/I4210166112"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109304964","display_name":"Tong Qingxi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"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":"Tong Qingxi","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing","institution_ids":["https://openalex.org/I4210128053","https://openalex.org/I4210166112"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25804913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1970","last_page":"1972"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9937999844551086,"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":0.9883000254631042,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8607784509658813},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.8312107920646667},{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.6838089227676392},{"id":"https://openalex.org/keywords/atmospheric-correction","display_name":"Atmospheric correction","score":0.5611250996589661},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5254963040351868},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.4730645418167114},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.46301576495170593},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4042056202888489},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2846824526786804},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12309974431991577},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11449900269508362},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.10929214954376221}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8607784509658813},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.8312107920646667},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.6838089227676392},{"id":"https://openalex.org/C2778329001","wikidata":"https://www.wikidata.org/wiki/Q4817104","display_name":"Atmospheric correction","level":3,"score":0.5611250996589661},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5254963040351868},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.4730645418167114},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.46301576495170593},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4042056202888489},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2846824526786804},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12309974431991577},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11449900269508362},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.10929214954376221},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C109007969","wikidata":"https://www.wikidata.org/wiki/Q749565","display_name":"Structural basin","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2016.7729507","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7729507","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W1967437037","https://openalex.org/W1977066218","https://openalex.org/W1979407902","https://openalex.org/W2069674806","https://openalex.org/W2073786624","https://openalex.org/W2107045929","https://openalex.org/W2125763679","https://openalex.org/W2161245744","https://openalex.org/W2163698947"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2350520172","https://openalex.org/W2343343867","https://openalex.org/W4327563490","https://openalex.org/W2383658474"],"abstract_inverted_index":{"This":[0,156],"method":[1,77,80,135],"presented":[2],"in":[3,137],"this":[4,31,138],"paper":[5,72,139],"was":[6],"tested":[7],"using":[8,78],"CASI&SASI":[9],"data":[10,45],"collected":[11],"from":[12,41,151],"a":[13,159],"site":[14],"at":[15],"the":[16,42,63,75,83,99,134,163,168],"Huailai":[17],"County,":[18],"Hebei":[19],"Province,":[20],"China.":[21],"Various":[22],"methods":[23],"for":[24,143],"retrieving":[25],"AOT":[26,40],"and":[27,53,61,115,124,130,147],"CWV":[28,89],"specific":[29],"to":[30,81,162],"region":[32],"were":[33],"assessed.":[34],"Results":[35],"show":[36,118],"that":[37],"retrieval":[38,84,150],"of":[39,69,85,103,112,170,172],"remote":[43,105,153],"sensing":[44,106,154],"required":[46],"establishing":[47],"empirical":[48],"relationships":[49],"between":[50],"465.6nm,":[51],"659nm":[52],"2105nm":[54],"augmented":[55],"by":[56],"ground-based":[57],"reflectance":[58,108,149,165],"validation":[59],"data,":[60],"minimizing":[62],"merit":[64],"function":[65],"based":[66],"on":[67],"optimization":[68],"AOT@550nm.":[70],"The":[71,87],"also":[73],"extends":[74],"SODA":[76],"Powell's":[79],"optimize":[82],"CWV.":[86],"resultant":[88],"image":[90],"shows":[91],"relatively":[92],"less":[93],"residual":[94],"surface":[95,107,148,164],"features":[96],"compared":[97],"with":[98,109,126],"standard":[100],"methods.":[101],"Comparison":[102],"derived":[104],"ground":[110],"spectra":[111],"comparable":[113],"vegetation":[114],"soil":[116],"targets":[117],"significant":[119],"correlations":[120],"(R2)":[121],"is":[122,140],"0.942":[123],"0.786,":[125],"RMSE":[127],"being":[128],"0.0387":[129],"0.0406":[131],"respectively.":[132],"Therefore,":[133],"proposed":[136],"reliable":[141],"enough":[142],"integrated":[144],"atmospheric":[145,174],"correction":[146],"hyperspectral":[152],"data.":[155],"case":[157],"provides":[158],"good":[160],"reference":[161],"inversion":[166],"under":[167],"condition":[169],"lack":[171],"synchronized":[173],"parameters.":[175]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
