{"id":"https://openalex.org/W4313576642","doi":"https://doi.org/10.3390/rs15020305","title":"A Global-Information-Constrained Deep Learning Network for Digital Elevation Model Super-Resolution","display_name":"A Global-Information-Constrained Deep Learning Network for Digital Elevation Model Super-Resolution","publication_year":2023,"publication_date":"2023-01-04","ids":{"openalex":"https://openalex.org/W4313576642","doi":"https://doi.org/10.3390/rs15020305"},"language":"en","primary_location":{"id":"doi:10.3390/rs15020305","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15020305","pdf_url":"https://www.mdpi.com/2072-4292/15/2/305/pdf?version=1673916810","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/2072-4292/15/2/305/pdf?version=1673916810","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101261979","display_name":"Xiaoyi Han","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyi Han","raw_affiliation_strings":["Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences, Wuhan 430074, China","School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101621753","display_name":"Xiaochuan Ma","orcid":"https://orcid.org/0000-0003-0362-2529"},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochuan Ma","raw_affiliation_strings":["School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045745804","display_name":"Houpu Li","orcid":"https://orcid.org/0000-0001-9698-8911"},"institutions":[{"id":"https://openalex.org/I2800710378","display_name":"Naval University of Engineering","ror":"https://ror.org/056vyez31","country_code":"CN","type":"education","lineage":["https://openalex.org/I2800710378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houpu Li","raw_affiliation_strings":["Control Engineering Laboratory, Naval University of Engineering, Wuhan 430030, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Control Engineering Laboratory, Naval University of Engineering, Wuhan 430030, China","institution_ids":["https://openalex.org/I2800710378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022463572","display_name":"Zhanlong Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I3124059619","display_name":"China University of Geosciences","ror":"https://ror.org/04gcegc37","country_code":"CN","type":"education","lineage":["https://openalex.org/I3124059619"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhanlong Chen","raw_affiliation_strings":["Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences, Wuhan 430074, China","National Engineering Research Center of Geographic Information System, Wuhan 430078, China","School of Computer Science, China University of Geosciences, Wuhan 430078, China","School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China"],"raw_orcid":"https://orcid.org/0000-0001-6373-3162","affiliations":[{"raw_affiliation_string":"Key Laboratory of Geological Survey and Evaluation of Ministry of Education, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"National Engineering Research Center of Geographic Information System, Wuhan 430078, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science, China University of Geosciences, Wuhan 430078, China","institution_ids":["https://openalex.org/I3124059619"]},{"raw_affiliation_string":"School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China","institution_ids":["https://openalex.org/I3124059619"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5022463572"],"corresponding_institution_ids":["https://openalex.org/I3124059619"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":3.0845,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.9325814,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"15","issue":"2","first_page":"305","last_page":"305"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9940000176429749,"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"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9940000176429749,"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/T10644","display_name":"Cryospheric studies and observations","score":0.9911999702453613,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9902999997138977,"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/computer-science","display_name":"Computer science","score":0.7174182534217834},{"id":"https://openalex.org/keywords/digital-elevation-model","display_name":"Digital elevation model","score":0.6257593035697937},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6143372654914856},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6020572185516357},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.5940895676612854},{"id":"https://openalex.org/keywords/bicubic-interpolation","display_name":"Bicubic interpolation","score":0.5795737504959106},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5659545660018921},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5357683300971985},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4383479654788971},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4130912125110626},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4127150774002075},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.4122891426086426},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.39575091004371643},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.31601977348327637},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2983124852180481},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2936329245567322},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.15260332822799683},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1313028335571289},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.11152660846710205}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7174182534217834},{"id":"https://openalex.org/C181843262","wikidata":"https://www.wikidata.org/wiki/Q640492","display_name":"Digital elevation model","level":2,"score":0.6257593035697937},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6143372654914856},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6020572185516357},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.5940895676612854},{"id":"https://openalex.org/C49608258","wikidata":"https://www.wikidata.org/wiki/Q611705","display_name":"Bicubic interpolation","level":4,"score":0.5795737504959106},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5659545660018921},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5357683300971985},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4383479654788971},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4130912125110626},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4127150774002075},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.4122891426086426},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39575091004371643},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31601977348327637},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2983124852180481},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2936329245567322},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.15260332822799683},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1313028335571289},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.11152660846710205},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C171836373","wikidata":"https://www.wikidata.org/wiki/Q2266329","display_name":"Linear interpolation","level":3,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs15020305","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15020305","pdf_url":"https://www.mdpi.com/2072-4292/15/2/305/pdf?version=1673916810","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:5c71abc0126e457895902ccbd04de85e","is_oa":true,"landing_page_url":"https://doaj.org/article/5c71abc0126e457895902ccbd04de85e","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"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 15, Iss 2, p 305 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/15/2/305/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs15020305","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; Volume 15; Issue 2; Pages: 305","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs15020305","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs15020305","pdf_url":"https://www.mdpi.com/2072-4292/15/2/305/pdf?version=1673916810","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":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8399999737739563}],"awards":[{"id":"https://openalex.org/G564516415","display_name":null,"funder_award_id":"GLAB2022ZR06","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6457507649","display_name":null,"funder_award_id":"42122025","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6887970928","display_name":null,"funder_award_id":"41871305","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4313576642.pdf"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W1512040619","https://openalex.org/W1533861849","https://openalex.org/W1665214252","https://openalex.org/W1677182931","https://openalex.org/W1745334888","https://openalex.org/W1836465849","https://openalex.org/W1840106123","https://openalex.org/W1885185971","https://openalex.org/W1903029394","https://openalex.org/W1981418425","https://openalex.org/W1993971295","https://openalex.org/W2008926204","https://openalex.org/W2025343193","https://openalex.org/W2027252311","https://openalex.org/W2062577170","https://openalex.org/W2073817609","https://openalex.org/W2074984119","https://openalex.org/W2082302033","https://openalex.org/W2089055951","https://openalex.org/W2090075397","https://openalex.org/W2102148524","https://openalex.org/W2102812780","https://openalex.org/W2103997799","https://openalex.org/W2147169375","https://openalex.org/W2154286323","https://openalex.org/W2156047020","https://openalex.org/W2156935079","https://openalex.org/W2160207806","https://openalex.org/W2160535745","https://openalex.org/W2194775991","https://openalex.org/W2298770932","https://openalex.org/W2328510092","https://openalex.org/W2415472909","https://openalex.org/W2476548250","https://openalex.org/W2489507420","https://openalex.org/W2548377017","https://openalex.org/W2592962403","https://openalex.org/W2601564443","https://openalex.org/W2884367402","https://openalex.org/W2919115771","https://openalex.org/W2936185297","https://openalex.org/W2963470893","https://openalex.org/W2963925437","https://openalex.org/W2990613095","https://openalex.org/W3017210109","https://openalex.org/W3122522954","https://openalex.org/W3124269386","https://openalex.org/W3124539583","https://openalex.org/W3133696297","https://openalex.org/W3140854437","https://openalex.org/W3182256037","https://openalex.org/W3185807047","https://openalex.org/W3187798970","https://openalex.org/W4206491044","https://openalex.org/W4225275192","https://openalex.org/W4232489867","https://openalex.org/W4249073844","https://openalex.org/W4280654353","https://openalex.org/W4312704068","https://openalex.org/W6697614014","https://openalex.org/W6763509872","https://openalex.org/W6790690058"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W4382618745","https://openalex.org/W1973775000","https://openalex.org/W2748922771","https://openalex.org/W2785996895","https://openalex.org/W1987128138"],"abstract_inverted_index":{"High-resolution":[0],"DEMs":[1],"can":[2,8],"provide":[3],"accurate":[4],"geographic":[5],"information":[6,63,118],"and":[7,17,121,148,170,187],"be":[9],"widely":[10],"used":[11,154],"in":[12],"hydrological":[13],"analysis,":[14],"path":[15],"planning,":[16],"urban":[18],"design.":[19],"As":[20],"the":[21,29,49,61,67,78,130,138,149,157,161,165,173,188,195,202,206],"main":[22],"complementary":[23],"means":[24],"of":[25,60,71,88,115,160,176,208],"producing":[26],"high-resolution":[27],"DEMs,":[28],"DEM":[30,50,106],"super-resolution":[31,51],"(SR)":[32],"method":[33,52,113,132,178],"based":[34,53],"on":[35,54],"deep":[36,55,72,102,203],"learning":[37,56,73,103,204],"has":[38,74],"reached":[39],"a":[40,58,86,100,116,122,145,180],"bottleneck.":[41],"The":[42,127,142],"reason":[43],"for":[44,105],"this":[45,96],"phenomenon":[46],"is":[47,153,191,211],"that":[48],"lacks":[57],"part":[59],"global":[62,89,117,135],"it":[64],"requires.":[65],"Specifically,":[66,109],"multilevel":[68],"aggregation":[69],"process":[70],"difficulty":[75],"sufficiently":[76],"capturing":[77],"low-level":[79],"features":[80,159],"with":[81,91,164,194,201],"dependencies,":[82],"which":[83,152],"leads":[84],"to":[85,133,155,183,215],"lack":[87],"relationships":[90],"high-level":[92],"information.":[93],"To":[94],"address":[95],"problem,":[97],"we":[98],"propose":[99],"global-information-constrained":[101],"network":[104],"SR":[107],"(GISR).":[108],"our":[110,177,209],"proposed":[111],"GISR":[112],"consists":[114],"supplement":[119,134],"module":[120,147],"local":[123],"feature":[124],"generation":[125,189],"module.":[126],"former":[128],"uses":[129],"Kriging":[131],"information,":[136],"considering":[137],"spatial":[139],"autocorrelation":[140],"rule.":[141],"latter":[143],"includes":[144],"residual":[146],"PixelShuffle":[150],"module,":[151],"restore":[156],"detailed":[158],"terrain.":[162],"Compared":[163],"bicubic,":[166],"Kriging,":[167],"SRCNN,":[168],"SRResNet,":[169],"TfaSR":[171],"methods,":[172],"experimental":[174],"results":[175,210],"show":[179],"better":[181],"ability":[182],"retain":[184],"terrain":[185],"features,":[186],"effect":[190],"more":[192],"consistent":[193],"ground":[196],"truth":[197],"DEM.":[198],"Meanwhile,":[199],"compared":[200],"method,":[205],"RMSE":[207],"improved":[212],"by":[213],"20.5%":[214],"68.8%.":[216]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":4}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2023-01-06T00:00:00"}
