{"id":"https://openalex.org/W2792131875","doi":"https://doi.org/10.1117/12.2288745","title":"Comparison of inversion accuracy of soil copper content from vegetation indices under different spectral resolution","display_name":"Comparison of inversion accuracy of soil copper content from vegetation indices under different spectral resolution","publication_year":2018,"publication_date":"2018-03-08","ids":{"openalex":"https://openalex.org/W2792131875","doi":"https://doi.org/10.1117/12.2288745","mag":"2792131875"},"language":"en","primary_location":{"id":"doi:10.1117/12.2288745","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2288745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications","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/A5005113911","display_name":"Kun Shang","orcid":"https://orcid.org/0000-0003-0137-0081"},"institutions":[{"id":"https://openalex.org/I2799486974","display_name":"China Geological Survey","ror":"https://ror.org/04wtq2305","country_code":"CN","type":"other","lineage":["https://openalex.org/I2799486974"]},{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Shang","raw_affiliation_strings":["China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China); China Univ. of Geosciences (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China); China Univ. of Geosciences (China)","institution_ids":["https://openalex.org/I2799486974","https://openalex.org/I3125743391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077436600","display_name":"Zhongqing Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I2799486974","display_name":"China Geological Survey","ror":"https://ror.org/04wtq2305","country_code":"CN","type":"other","lineage":["https://openalex.org/I2799486974"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongqing Sun","raw_affiliation_strings":["China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)","China Univ. of Geosciences (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)","institution_ids":["https://openalex.org/I2799486974"]},{"raw_affiliation_string":"China Univ. of Geosciences (China)","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113877444","display_name":"Lingjun Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I2799486974","display_name":"China Geological Survey","ror":"https://ror.org/04wtq2305","country_code":"CN","type":"other","lineage":["https://openalex.org/I2799486974"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingjun Jia","raw_affiliation_strings":["China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)","China Univ. of Geosciences (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"China Aero Geophysical Survey and Remote Sensing Ctr. for Land and Resources (China)","institution_ids":["https://openalex.org/I2799486974"]},{"raw_affiliation_string":"China Univ. of Geosciences (China)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.02699831,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"168","last_page":"168"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9922000169754028,"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"}},"topics":[{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9922000169754028,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.98089998960495,"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/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9688000082969666,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.710800051689148},{"id":"https://openalex.org/keywords/inversion","display_name":"Inversion (geology)","score":0.6909267902374268},{"id":"https://openalex.org/keywords/soil-science","display_name":"Soil science","score":0.653880774974823},{"id":"https://openalex.org/keywords/vegetation-index","display_name":"Vegetation Index","score":0.6014776229858398},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5509440898895264},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5466012954711914},{"id":"https://openalex.org/keywords/copper","display_name":"Copper","score":0.44489943981170654},{"id":"https://openalex.org/keywords/enhanced-vegetation-index","display_name":"Enhanced vegetation index","score":0.44100335240364075},{"id":"https://openalex.org/keywords/high-resolution","display_name":"High resolution","score":0.42739975452423096},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2941252589225769},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.19835546612739563},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.16809675097465515},{"id":"https://openalex.org/keywords/geomorphology","display_name":"Geomorphology","score":0.07603013515472412},{"id":"https://openalex.org/keywords/metallurgy","display_name":"Metallurgy","score":0.0712435245513916}],"concepts":[{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.710800051689148},{"id":"https://openalex.org/C1893757","wikidata":"https://www.wikidata.org/wiki/Q3653001","display_name":"Inversion (geology)","level":3,"score":0.6909267902374268},{"id":"https://openalex.org/C159390177","wikidata":"https://www.wikidata.org/wiki/Q9161265","display_name":"Soil science","level":1,"score":0.653880774974823},{"id":"https://openalex.org/C2780376076","wikidata":"https://www.wikidata.org/wiki/Q1499458","display_name":"Vegetation Index","level":4,"score":0.6014776229858398},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5509440898895264},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5466012954711914},{"id":"https://openalex.org/C544778455","wikidata":"https://www.wikidata.org/wiki/Q753","display_name":"Copper","level":2,"score":0.44489943981170654},{"id":"https://openalex.org/C78869512","wikidata":"https://www.wikidata.org/wiki/Q5378810","display_name":"Enhanced vegetation index","level":5,"score":0.44100335240364075},{"id":"https://openalex.org/C3020199158","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"High resolution","level":2,"score":0.42739975452423096},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2941252589225769},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.19835546612739563},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.16809675097465515},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.07603013515472412},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0712435245513916},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","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:10.1117/12.2288745","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2288745","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2171400093","https://openalex.org/W3017461794","https://openalex.org/W2115853453","https://openalex.org/W2387342003","https://openalex.org/W2362091011","https://openalex.org/W4322775963","https://openalex.org/W2374309310","https://openalex.org/W127347482","https://openalex.org/W2376348986","https://openalex.org/W2045721522"],"abstract_inverted_index":{"Remote":[0],"sensing":[1],"inversion":[2,44,84,110],"of":[3,16,37,43,45,67,86,101,112],"heavy":[4,20,34,46,70],"metal":[5,21,35,47,71],"in":[6,49,89,116],"vegetation":[7,17,27,38,78,94,126],"leaves":[8],"is":[9,52,59,75],"generally":[10],"based":[11],"on":[12],"the":[13,33,41,83,117,125],"physiological":[14],"characteristics":[15],"spectrum":[18],"under":[19,128],"stress,":[22],"and":[23,106,124],"empirical":[24],"models":[25],"with":[26,77],"indices":[28,95,127],"are":[29],"established":[30,76],"to":[31,97,133],"inverse":[32],"content":[36,48,115],"leaves.":[39],"However,":[40],"research":[42],"vegetation-covered":[50,90,118],"soil":[51,91,113],"still":[53],"rare.":[54],"In":[55],"this":[56],"study,":[57],"Pulang":[58],"chosen":[60],"as":[61],"study":[62],"area.":[63],"The":[64,109],"regression":[65],"model":[66],"a":[68,121],"typical":[69],"element,":[72],"copper":[73,114],"(Cu),":[74],"indices.":[79],"We":[80],"mainly":[81],"investigate":[82],"accuracies":[85],"Cu":[87],"element":[88],"by":[92],"different":[93],"according":[96],"specific":[98],"spectral":[99,130],"resolutions":[100],"ASD":[102,129],"(Analytical":[103],"Spectral":[104],"Device)":[105],"Hyperion":[107],"data.":[108],"results":[111],"area":[119],"shows":[120],"good":[122],"accuracy,":[123],"resolution":[131],"correspond":[132],"better":[134],"results.":[135]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}