{"id":"https://openalex.org/W4398187739","doi":"https://doi.org/10.1109/lgrs.2024.3403835","title":"Diff-DEM: A Diffusion Probabilistic Approach to Digital Elevation Model Void Filling","display_name":"Diff-DEM: A Diffusion Probabilistic Approach to Digital Elevation Model Void Filling","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4398187739","doi":"https://doi.org/10.1109/lgrs.2024.3403835"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2024.3403835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2024.3403835","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/A5058288671","display_name":"Kyle Shih-Huang Lo","orcid":"https://orcid.org/0000-0002-0338-6469"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle Shih-Huang Lo","raw_affiliation_strings":["Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA"],"raw_orcid":"https://orcid.org/0000-0002-0338-6469","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027686327","display_name":"J\u00f6rg Peters","orcid":"https://orcid.org/0000-0002-2499-1529"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J\u00f6rg Peters","raw_affiliation_strings":["Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA"],"raw_orcid":"https://orcid.org/0000-0002-2499-1529","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I33213144"],"apc_list":null,"apc_paid":null,"fwci":1.3179,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76794585,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"21","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.951200008392334,"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"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.951200008392334,"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"}},{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9470000267028809,"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/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9420999884605408,"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/digital-elevation-model","display_name":"Digital elevation model","score":0.7246003150939941},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5695038437843323},{"id":"https://openalex.org/keywords/void","display_name":"Void (composites)","score":0.4408237338066101},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43222862482070923},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.3667031526565552},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.18263766169548035},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.14719563722610474},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.10268840193748474}],"concepts":[{"id":"https://openalex.org/C181843262","wikidata":"https://www.wikidata.org/wiki/Q640492","display_name":"Digital elevation model","level":2,"score":0.7246003150939941},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5695038437843323},{"id":"https://openalex.org/C2779772531","wikidata":"https://www.wikidata.org/wiki/Q19689164","display_name":"Void (composites)","level":2,"score":0.4408237338066101},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43222862482070923},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3667031526565552},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.18263766169548035},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.14719563722610474},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.10268840193748474},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2024.3403835","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2024.3403835","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":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310009","display_name":"University of Florida","ror":"https://ror.org/02y3ad647"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1482047413","https://openalex.org/W1599920422","https://openalex.org/W1901129140","https://openalex.org/W1990128059","https://openalex.org/W2005070893","https://openalex.org/W2072290140","https://openalex.org/W2114212443","https://openalex.org/W2125389028","https://openalex.org/W2147169375","https://openalex.org/W2157494358","https://openalex.org/W2194775991","https://openalex.org/W2614741935","https://openalex.org/W2901262527","https://openalex.org/W2936185297","https://openalex.org/W2963006576","https://openalex.org/W2991553150","https://openalex.org/W2995497465","https://openalex.org/W3106488531","https://openalex.org/W3110904424","https://openalex.org/W3212516020","https://openalex.org/W3215646032","https://openalex.org/W4214902581","https://openalex.org/W4253999117","https://openalex.org/W4298005622","https://openalex.org/W4366827602","https://openalex.org/W4367146570","https://openalex.org/W4379057906","https://openalex.org/W4385245566","https://openalex.org/W4385756611","https://openalex.org/W4387829321","https://openalex.org/W4388416602","https://openalex.org/W4388853646","https://openalex.org/W4389471355","https://openalex.org/W4389610328","https://openalex.org/W6678815747","https://openalex.org/W6779823529","https://openalex.org/W6809884996","https://openalex.org/W6858947348"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2324615561","https://openalex.org/W2086120259","https://openalex.org/W2390279801","https://openalex.org/W2245170124","https://openalex.org/W2076393078","https://openalex.org/W2358668433","https://openalex.org/W3186982001","https://openalex.org/W1984402782"],"abstract_inverted_index":{"Digital":[0],"Elevation":[1],"Models":[2],"(DEMs)":[3],"are":[4],"crucial":[5],"for":[6,26],"modeling":[7],"and":[8,58,63,85,93,118,133],"analyzing":[9],"terrestrial":[10],"environments,":[11],"but":[12],"voids":[13,29],"in":[14,50],"DEMs":[15,121],"can":[16],"compromise":[17],"their":[18],"downstream":[19],"use.":[20],"Diff-DEM":[21,67],"is":[22,90],"a":[23,32,40,47,56],"self-supervised":[24],"method":[25],"filling":[27],"DEM":[28,70],"that":[30,97],"leverages":[31],"Denoising":[33],"Diffusion":[34],"Probabilistic":[35],"Model":[36],"(DDPM).":[37],"Conditioned":[38],"on":[39,91,94],"void-containing":[41],"DEM,":[42],"the":[43,51,114],"DDPM":[44],"acts":[45],"as":[46],"transition":[48],"kernel":[49],"diffusion":[52],"reversal,":[53],"progressively":[54],"reconstructing":[55],"sharp":[57],"accurate":[59],"DEM.":[60],"Both":[61],"qualitative":[62],"quantitative":[64],"assessments":[65],"demonstrate":[66],"outperforms":[68],"existing":[69],"inpainting,":[71],"including":[72],"Generative":[73],"Adversarial":[74],"Network":[75],"(GAN)":[76],"methods,":[77],"Inverse":[78],"Distance":[79],"Weighting":[80],"(IDW),":[81],"Kriging,":[82],"LR":[83],"B-spline,":[84],"Perona-Malik":[86],"diffusion.":[87],"The":[88],"comparison":[89],"Gavriil\u2019s":[92,99],"our":[95],"benchmark":[96],"expands":[98],"dataset":[100],"from":[101,113,119],"63":[102],"to":[103,122],"217":[104],"full-size":[105],"(5051":[106],"\u00d7":[107],"5051)":[108],"10-meter":[109],"GeoTIFF":[110],"images":[111],"sourced":[112],"Norwegian":[115],"Mapping":[116],"Authority;":[117],"50":[120],"three":[123],"groups":[124],"of":[125,128],"1k":[126],"each":[127],"increasing":[129],"void":[130],"size.":[131],"Code":[132],"dataset:":[134],"https://github.com/kylelo/Diff-DEM.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}