{"id":"https://openalex.org/W3175626522","doi":"https://doi.org/10.3390/rs13122354","title":"Fusion of China ZY-1 02D Hyperspectral Data and Multispectral Data: Which Methods Should Be Used?","display_name":"Fusion of China ZY-1 02D Hyperspectral Data and Multispectral Data: Which Methods Should Be Used?","publication_year":2021,"publication_date":"2021-06-16","ids":{"openalex":"https://openalex.org/W3175626522","doi":"https://doi.org/10.3390/rs13122354","mag":"3175626522"},"language":"en","primary_location":{"id":"doi:10.3390/rs13122354","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13122354","pdf_url":"https://www.mdpi.com/2072-4292/13/12/2354/pdf?version=1624417287","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/2072-4292/13/12/2354/pdf?version=1624417287","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102013884","display_name":"Lu Han","orcid":"https://orcid.org/0000-0003-4808-5018"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Lu","raw_affiliation_strings":["College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China","College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China","Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"],"affiliations":[{"raw_affiliation_string":"College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078950132","display_name":"Danyu Qiao","orcid":null},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danyu Qiao","raw_affiliation_strings":["College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China","College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China","Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"],"affiliations":[{"raw_affiliation_string":"College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100405254","display_name":"Yongxin Li","orcid":"https://orcid.org/0000-0003-2914-6583"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongxin Li","raw_affiliation_strings":["Logistics Support Department, Capital Normal University, Beijing 100048, China"],"affiliations":[{"raw_affiliation_string":"Logistics Support Department, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101417517","display_name":"Shuang Wu","orcid":"https://orcid.org/0000-0002-5996-4600"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Wu","raw_affiliation_strings":["College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China","College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China","Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"],"affiliations":[{"raw_affiliation_string":"College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037042702","display_name":"Lei Deng","orcid":"https://orcid.org/0000-0002-4574-7381"},"institutions":[{"id":"https://openalex.org/I96852419","display_name":"Capital Normal University","ror":"https://ror.org/005edt527","country_code":"CN","type":"education","lineage":["https://openalex.org/I96852419"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei Deng","raw_affiliation_strings":["College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China","College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China","Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China"],"affiliations":[{"raw_affiliation_string":"College of Geospatial Information Science and Technology, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]},{"raw_affiliation_string":"Key Laboratory of 3D Information Acquisition and Application, Capital Normal University, Beijing 100048, China","institution_ids":["https://openalex.org/I96852419"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5037042702"],"corresponding_institution_ids":["https://openalex.org/I96852419"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.9946,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.87649547,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"13","issue":"12","first_page":"2354","last_page":"2354"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998999834060669,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9993000030517578,"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/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.995199978351593,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.7446175813674927},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6649050116539001},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.639965295791626},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5821481943130493},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5694437623023987},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.56695955991745},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4564597010612488},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33851051330566406},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1725345253944397},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08906242251396179}],"concepts":[{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7446175813674927},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6649050116539001},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.639965295791626},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5821481943130493},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5694437623023987},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.56695955991745},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4564597010612488},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33851051330566406},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1725345253944397},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08906242251396179}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs13122354","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13122354","pdf_url":"https://www.mdpi.com/2072-4292/13/12/2354/pdf?version=1624417287","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:1d9cae9ea51d4069aa9c0e2713050ae4","is_oa":true,"landing_page_url":"https://doaj.org/article/1d9cae9ea51d4069aa9c0e2713050ae4","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 13, Iss 12, p 2354 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/13/12/2354/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs13122354","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/rs13122354","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13122354","pdf_url":"https://www.mdpi.com/2072-4292/13/12/2354/pdf?version=1624417287","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":[],"awards":[{"id":"https://openalex.org/G3805003622","display_name":null,"funder_award_id":"21220030003","funder_id":"https://openalex.org/F4320310931","funder_display_name":"Capital Normal University"}],"funders":[{"id":"https://openalex.org/F4320310931","display_name":"Capital Normal University","ror":"https://ror.org/005edt527"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3175626522.pdf","grobid_xml":"https://content.openalex.org/works/W3175626522.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W788877107","https://openalex.org/W814229429","https://openalex.org/W1584663654","https://openalex.org/W1974307287","https://openalex.org/W1980777339","https://openalex.org/W1988952689","https://openalex.org/W1991460509","https://openalex.org/W1996201635","https://openalex.org/W2001298023","https://openalex.org/W2010679177","https://openalex.org/W2018560460","https://openalex.org/W2027319213","https://openalex.org/W2040774201","https://openalex.org/W2070987367","https://openalex.org/W2097130407","https://openalex.org/W2106891293","https://openalex.org/W2132844602","https://openalex.org/W2144436897","https://openalex.org/W2152254169","https://openalex.org/W2160344148","https://openalex.org/W2163607262","https://openalex.org/W2171108951","https://openalex.org/W2303172903","https://openalex.org/W2361026302","https://openalex.org/W2363458427","https://openalex.org/W2523210664","https://openalex.org/W2524304244","https://openalex.org/W2548791488","https://openalex.org/W2605042243","https://openalex.org/W2622007554","https://openalex.org/W2625894731","https://openalex.org/W2742541878","https://openalex.org/W2773041763","https://openalex.org/W2792365373","https://openalex.org/W2802753788","https://openalex.org/W2917943389","https://openalex.org/W2944395072","https://openalex.org/W2963284277","https://openalex.org/W2963442801","https://openalex.org/W2980017917","https://openalex.org/W2985833605","https://openalex.org/W2997685753","https://openalex.org/W3010650493","https://openalex.org/W3016256189","https://openalex.org/W3016410830","https://openalex.org/W3024816816","https://openalex.org/W3025464543","https://openalex.org/W3047955358","https://openalex.org/W3114279824","https://openalex.org/W3128416105","https://openalex.org/W3194377366","https://openalex.org/W4385279333","https://openalex.org/W4385533128","https://openalex.org/W6623032828","https://openalex.org/W6770307128","https://openalex.org/W6775950665"],"related_works":["https://openalex.org/W2022304901","https://openalex.org/W2018850895","https://openalex.org/W1987483041","https://openalex.org/W2988577871","https://openalex.org/W4391030644","https://openalex.org/W4205174160","https://openalex.org/W2317401237","https://openalex.org/W1990800631","https://openalex.org/W2167120702","https://openalex.org/W2011962637"],"abstract_inverted_index":{"ZY-1":[0,77,107,112,184,203,242],"02D":[1,78,108,113,185,204,243],"is":[2,86],"China\u2019s":[3],"first":[4],"civil":[5],"hyperspectral":[6],"(HS)":[7],"operational":[8],"satellite,":[9],"developed":[10],"independently":[11],"and":[12,38,59,123,135,160,174,188,193,211,214],"successfully":[13],"launched":[14],"in":[15,132],"2019.":[16],"It":[17],"can":[18,196],"collect":[19],"HS":[20,79,109,186,205,244],"data":[21,80,85,110,115,141,206,245],"with":[22,81,111],"a":[23,32,39,74,99,234],"spatial":[24,67,90,117,200,223],"resolution":[25,58,68,91,201],"of":[26,35,42,106,138,183,202,228,241],"30":[27],"m,":[28],"166":[29],"spectral":[30,33,57,94,209,219],"bands,":[31],"range":[34],"400~2500":[36],"nm,":[37],"swath":[40,61],"width":[41],"60":[43],"km.":[44],"Its":[45],"competitive":[46],"advantages":[47],"over":[48],"other":[49],"on-orbit":[50],"or":[51],"planned":[52],"satellites":[53],"are":[54,177],"its":[55,71],"high":[56,218],"large":[60],"width.":[62],"Unfortunately,":[63],"the":[64,104,136,181,199,238],"relatively":[65],"low":[66],"may":[69],"limit":[70],"applications.":[72],"As":[73],"result,":[75],"fusing":[76],"high-spatial-resolution":[82],"multispectral":[83],"(MS)":[84],"required":[87],"to":[88],"improve":[89,198],"while":[92],"maintaining":[93],"fidelity.":[95],"This":[96],"paper":[97],"conducted":[98],"comprehensive":[100],"evaluation":[101],"study":[102,230],"on":[103,120],"fusion":[105,142,182],"MS":[114,189],"(10-m":[116],"resolution),":[118],"based":[119],"visual":[121],"interpretation":[122],"quantitative":[124],"metrics.":[125],"Datasets":[126],"from":[127],"Hebei,":[128],"China,":[129],"were":[130,165],"used":[131],"this":[133,229],"experiment,":[134],"performances":[137],"six":[139],"common":[140],"methods,":[143],"namely":[144],"Gram-Schmidt":[145],"(GS),":[146],"High":[147],"Pass":[148],"Filter":[149],"(HPF),":[150],"Nearest-Neighbor":[151],"Diffusion":[152],"(NND),":[153],"Modified":[154],"Intensity-Hue-Saturation":[155],"(IHS),":[156],"Wavelet":[157,213],"Transform":[158],"(Wavelet),":[159],"Color":[161],"Normalized":[162],"Sharping":[163],"(Brovey),":[164],"compared.":[166],"The":[167,226],"experimental":[168],"results":[169,216],"show":[170],"that:":[171],"(1)":[172],"HPF":[173],"GS":[175],"methods":[176,195],"better":[178],"suited":[179],"for":[180,237],"Data":[187],"Data,":[190],"(2)":[191],"IHS":[192],"Brovey":[194],"well":[197],"but":[207,221],"introduce":[208],"distortion,":[210],"(3)":[212],"NND":[215],"have":[217],"fidelity":[220],"poor":[222],"detail":[224],"representation.":[225],"findings":[227],"could":[231],"serve":[232],"as":[233],"good":[235],"reference":[236],"practical":[239],"application":[240],"fusion.":[246]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}