{"id":"https://openalex.org/W2050755221","doi":"https://doi.org/10.1109/tgrs.2013.2247612","title":"MAP-MRF Approach to Landsat ETM+ SLC-Off Image Classification","display_name":"MAP-MRF Approach to Landsat ETM+ SLC-Off Image Classification","publication_year":2013,"publication_date":"2013-03-27","ids":{"openalex":"https://openalex.org/W2050755221","doi":"https://doi.org/10.1109/tgrs.2013.2247612","mag":"2050755221"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2013.2247612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2013.2247612","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5032109361","display_name":"Xiaolin Zhu","orcid":"https://orcid.org/0000-0001-6967-786X"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaolin Zhu","raw_affiliation_strings":["Department of Geography, The Ohio State University, Columbus, OH, USA","Dept. of Geogr., Ohio State Univ., Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography, The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Dept. of Geogr., Ohio State Univ., Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091312239","display_name":"Desheng Liu","orcid":"https://orcid.org/0000-0003-2480-9712"},"institutions":[{"id":"https://openalex.org/I52357470","display_name":"The Ohio State University","ror":"https://ror.org/00rs6vg23","country_code":"US","type":"education","lineage":["https://openalex.org/I52357470"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Desheng Liu","raw_affiliation_strings":["Department of Geography and the Department of Statistics, The Ohio State University, Columbus, OH, USA","Dept. of Geogr., Ohio State Univ., Columbus, OH, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Geography and the Department of Statistics, The Ohio State University, Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]},{"raw_affiliation_string":"Dept. of Geogr., Ohio State Univ., Columbus, OH, USA","institution_ids":["https://openalex.org/I52357470"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I52357470"],"apc_list":null,"apc_paid":null,"fwci":4.3356,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.9477786,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"52","issue":"2","first_page":"1131","last_page":"1141"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9988999962806702,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9988999962806702,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9959999918937683,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9952999949455261,"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/land-cover","display_name":"Land cover","score":0.7360772490501404},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6727758646011353},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.6545976400375366},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.631729245185852},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.5985093116760254},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5911586284637451},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5525597333908081},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.468193382024765},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46144193410873413},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4535634219646454},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.43338465690612793},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3019181489944458},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.2850768268108368},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16744109988212585},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1525128185749054},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.11629101634025574},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09211063385009766}],"concepts":[{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.7360772490501404},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6727758646011353},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.6545976400375366},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.631729245185852},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.5985093116760254},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5911586284637451},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5525597333908081},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.468193382024765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46144193410873413},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4535634219646454},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.43338465690612793},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3019181489944458},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.2850768268108368},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16744109988212585},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1525128185749054},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.11629101634025574},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09211063385009766},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2013.2247612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2013.2247612","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W113248618","https://openalex.org/W1526428665","https://openalex.org/W1651266332","https://openalex.org/W1963768209","https://openalex.org/W1965992386","https://openalex.org/W1978145340","https://openalex.org/W1979210946","https://openalex.org/W1993472818","https://openalex.org/W1997980023","https://openalex.org/W2001547114","https://openalex.org/W2014907398","https://openalex.org/W2020999234","https://openalex.org/W2024416496","https://openalex.org/W2046485672","https://openalex.org/W2050830693","https://openalex.org/W2065533253","https://openalex.org/W2078974732","https://openalex.org/W2081399384","https://openalex.org/W2085793179","https://openalex.org/W2087120756","https://openalex.org/W2093378913","https://openalex.org/W2100486264","https://openalex.org/W2109048734","https://openalex.org/W2111311858","https://openalex.org/W2125325727","https://openalex.org/W2126012534","https://openalex.org/W2126013952","https://openalex.org/W2136251662","https://openalex.org/W2138973222","https://openalex.org/W2139745272","https://openalex.org/W2141775747","https://openalex.org/W2158065679","https://openalex.org/W2166302761","https://openalex.org/W2398616379","https://openalex.org/W4251080014","https://openalex.org/W4302190632","https://openalex.org/W6604724360","https://openalex.org/W6631266481","https://openalex.org/W6712703161"],"related_works":["https://openalex.org/W2546871836","https://openalex.org/W2136485282","https://openalex.org/W1675950995","https://openalex.org/W2082199675","https://openalex.org/W2081155276","https://openalex.org/W2151888018","https://openalex.org/W2182824541","https://openalex.org/W2118926325","https://openalex.org/W2883251030","https://openalex.org/W2050755221"],"abstract_inverted_index":{"Land":[0],"cover":[1,44,186,206],"classification":[2,59,115,154,166],"is":[3,53,160],"an":[4,168,183],"important":[5],"application":[6,36],"of":[7,37,92,139,156,165],"Landsat":[8,27,38],"images.":[9,148],"Unfortunately,":[10],"the":[11,35,55,62,78,90,102,132,140,153,157,172,204],"scan-line":[12],"corrector":[13],"(SLC)":[14],"failure":[15],"in":[16,25,89,199],"2003":[17],"causes":[18],"about":[19],"22%":[20],"pixels":[21],"to":[22,196,203],"remain":[23],"unscanned":[24,56,124],"each":[26],"7":[28,39],"ETM+":[29,40,120],"image.":[30],"This":[31,94],"problem":[32,52],"seriously":[33],"limits":[34],"images":[41,121,201],"for":[42,49,67,74,117,135],"land":[43,185,205],"classification.":[45,207],"A":[46],"common":[47],"strategy":[48],"addressing":[50],"this":[51],"filling":[54,123],"gaps":[57,125,198],"before":[58],"work.":[60],"However,":[61],"simple":[63],"and":[64,87,108,194],"high-speed":[65],"methods":[66,80],"gap-filling":[68,79,174],"cannot":[69],"yield":[70],"satisfactory":[71],"results,":[72],"especially":[73],"heterogeneous":[75],"landscapes,":[76],"while":[77],"with":[81],"high":[82],"accuracy":[83,155],"are":[84],"often":[85],"complicated":[86,133],"inefficient":[88],"use":[91],"time.":[93],"paper":[95],"develops":[96],"a":[97,104],"new":[98],"method":[99,129,142,159],"based":[100],"on":[101],"maximum":[103],"posteriori":[105],"decision":[106],"rule":[107],"Markov":[109],"random":[110],"field":[111],"theory":[112],"(the":[113],"MAP-MRF":[114],"framework)":[116],"classifying":[118],"SLC-off":[119,147,200],"without":[122,191],"beforehand.":[126],"The":[127,137,149],"proposed":[128,141,158],"efficiently":[130],"avoids":[131],"process":[134],"gap-filling.":[136],"performance":[138],"was":[143],"validated":[144],"by":[145,171],"simulated":[146],"results":[150],"show":[151],"that":[152,164,182],"even":[161],"higher":[162],"than":[163],"from":[167],"image":[169],"filled":[170],"precise":[173],"algorithm":[175],"neighborhood":[176],"similar":[177],"pixel":[178],"interpolator,":[179],"which":[180],"indicates":[181],"accurate":[184],"map":[187],"can":[188],"be":[189],"generated":[190],"spending":[192],"time":[193],"effort":[195],"fill":[197],"prior":[202]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}