{"id":"https://openalex.org/W1578967902","doi":"https://doi.org/10.1109/lgrs.2015.2423496","title":"Improvement of the Example-Regression-Based Super-Resolution Land Cover Mapping Algorithm","display_name":"Improvement of the Example-Regression-Based Super-Resolution Land Cover Mapping Algorithm","publication_year":2015,"publication_date":"2015-05-04","ids":{"openalex":"https://openalex.org/W1578967902","doi":"https://doi.org/10.1109/lgrs.2015.2423496","mag":"1578967902"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2015.2423496","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2423496","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5034678630","display_name":"Yihang Zhang","orcid":"https://orcid.org/0009-0008-9446-5111"},"institutions":[{"id":"https://openalex.org/I4210105990","display_name":"Institute of Geodesy and Geophysics","ror":"https://ror.org/01gkn6j11","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210105990"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yihang Zhang","raw_affiliation_strings":["Institute of Geodesy and Geophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China","Inst. of Geodesy & Geophys., Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Geodesy and Geophysics, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210105990","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Inst. of Geodesy & Geophys., Wuhan, China","institution_ids":["https://openalex.org/I4210105990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112724341","display_name":"Yun Du","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210105990","display_name":"Institute of Geodesy and Geophysics","ror":"https://ror.org/01gkn6j11","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210105990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Du","raw_affiliation_strings":["Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China","Inst. of Geodesy & Geophys., Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China","institution_ids":["https://openalex.org/I4210105990","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Inst. of Geodesy & Geophys., Wuhan, China","institution_ids":["https://openalex.org/I4210105990"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012444471","display_name":"Feng Ling","orcid":"https://orcid.org/0000-0002-0685-4897"},"institutions":[{"id":"https://openalex.org/I4210105990","display_name":"Institute of Geodesy and Geophysics","ror":"https://ror.org/01gkn6j11","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210105990"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Ling","raw_affiliation_strings":["Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China","Inst. of Geodesy & Geophys., Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China","institution_ids":["https://openalex.org/I4210105990","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Inst. of Geodesy & Geophys., Wuhan, China","institution_ids":["https://openalex.org/I4210105990"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100369688","display_name":"Xiaodong Li","orcid":"https://orcid.org/0000-0001-8285-8446"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210105990","display_name":"Institute of Geodesy and Geophysics","ror":"https://ror.org/01gkn6j11","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210105990"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaodong Li","raw_affiliation_strings":["Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China","Inst. of Geodesy & Geophys., Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan, China","institution_ids":["https://openalex.org/I4210105990","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Inst. of Geodesy & Geophys., Wuhan, China","institution_ids":["https://openalex.org/I4210105990"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5034678630"],"corresponding_institution_ids":["https://openalex.org/I4210105990","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":2.133,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.85918553,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"12","issue":"8","first_page":"1740","last_page":"1744"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9970999956130981,"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":0.9970999956130981,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/land-cover","display_name":"Land cover","score":0.6451594233512878},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6347326040267944},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6051028370857239},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5678165555000305},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5123547315597534},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5076087713241577},{"id":"https://openalex.org/keywords/fraction","display_name":"Fraction (chemistry)","score":0.504829466342926},{"id":"https://openalex.org/keywords/speckle-pattern","display_name":"Speckle pattern","score":0.49692562222480774},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4450734853744507},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.44216880202293396},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34140920639038086},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24909496307373047},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.14652162790298462},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11212590336799622},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.09136995673179626}],"concepts":[{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.6451594233512878},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6347326040267944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6051028370857239},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5678165555000305},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5123547315597534},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5076087713241577},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.504829466342926},{"id":"https://openalex.org/C102290492","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle pattern","level":2,"score":0.49692562222480774},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4450734853744507},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.44216880202293396},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34140920639038086},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24909496307373047},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.14652162790298462},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11212590336799622},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.09136995673179626},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2015.2423496","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2423496","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"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":21,"referenced_works":["https://openalex.org/W402415036","https://openalex.org/W1987216185","https://openalex.org/W2002087357","https://openalex.org/W2011699662","https://openalex.org/W2014739240","https://openalex.org/W2017036863","https://openalex.org/W2021899548","https://openalex.org/W2024733560","https://openalex.org/W2026461463","https://openalex.org/W2026999441","https://openalex.org/W2037133124","https://openalex.org/W2048147566","https://openalex.org/W2050830693","https://openalex.org/W2065646058","https://openalex.org/W2073626642","https://openalex.org/W2087380704","https://openalex.org/W2089038605","https://openalex.org/W2136579598","https://openalex.org/W2151747974","https://openalex.org/W2162060765","https://openalex.org/W6613893036"],"related_works":["https://openalex.org/W2018008899","https://openalex.org/W2793402697","https://openalex.org/W2967406116","https://openalex.org/W2093785611","https://openalex.org/W2042019967","https://openalex.org/W2019193285","https://openalex.org/W1993402303","https://openalex.org/W2615806692","https://openalex.org/W2080965330","https://openalex.org/W2547534968"],"abstract_inverted_index":{"Super-resolution":[0],"mapping":[1],"(SRM)":[2],"is":[3,87,112,131,143],"a":[4,8,22],"method":[5],"for":[6,187],"generating":[7],"fine-resolution":[9,23,100],"land":[10,24,33,39,101],"cover":[11,25,34,40,102],"map":[12,26,103],"from":[13,37],"coarse-resolution":[14],"fraction":[15,49,95,107,155],"images.":[16,156],"Example-regression-based":[17],"SRM":[18,44,71,79,141,148,163,184],"algorithms":[19,45,149],"can":[20,165],"estimate":[21],"with":[27,145,168],"detailed":[28],"spatial":[29,35,175],"information":[30],"by":[31],"learning":[32],"patterns":[36],"available":[38],"maps.":[41],"Existing":[42],"example-regression-based":[43,70],"are":[46],"sensitive":[47],"to":[48,89,114,133],"errors,":[50],"and":[51,59,104,153,171,179],"the":[52,77,91,94,98,105,116,122,126,135,161,183],"results":[53,158,167,185],"often":[54],"include":[55],"many":[56],"linear":[57,172],"artifacts":[58],"speckles.":[60],"To":[61],"overcome":[62],"these":[63],"shortcomings,":[64],"this":[65],"study":[66],"proposes":[67],"an":[68],"improved":[69],"algorithm.":[72],"The":[73,84,109,128,139],"objective":[74],"function":[75],"of":[76,97,121],"proposed":[78,140,162],"algorithm":[80,142,164],"comprises":[81],"three":[82],"terms.":[83],"first":[85],"term":[86,111,130],"used":[88,113,132,186],"minimize":[90],"difference":[92],"between":[93],"values":[96,120],"estimated":[99],"input":[106],"values.":[108],"second":[110],"maximize":[115],"class":[117],"membership":[118],"possibility":[119],"fine":[123],"pixels":[124],"in":[125],"result.":[127],"final":[129],"make":[134],"result":[136],"locally":[137],"smooth.":[138],"compared":[144],"several":[146],"popular":[147],"using":[150],"both":[151],"synthetic":[152],"real":[154],"Experimental":[157],"indicate":[159],"that":[160],"produce":[166],"less":[169],"speckles":[170],"artifacts,":[173],"more":[174],"details,":[176],"smoother":[177],"boundaries,":[178],"higher":[180],"accuracies":[181],"than":[182],"comparison.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
