{"id":"https://openalex.org/W4416334864","doi":"https://doi.org/10.3390/ijgi14110451","title":"DDDMNet: A DSM Difference Normalization Module Network for Urban Building Change Detection","display_name":"DDDMNet: A DSM Difference Normalization Module Network for Urban Building Change Detection","publication_year":2025,"publication_date":"2025-11-16","ids":{"openalex":"https://openalex.org/W4416334864","doi":"https://doi.org/10.3390/ijgi14110451"},"language":"en","primary_location":{"id":"doi:10.3390/ijgi14110451","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi14110451","pdf_url":"https://www.mdpi.com/2220-9964/14/11/451/pdf?version=1763281565","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"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":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2220-9964/14/11/451/pdf?version=1763281565","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025760231","display_name":"Yihang Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210144487","display_name":"Cloud Computing Center","ror":"https://ror.org/04aa0zm65","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144487"]},{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihang Fu","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen 518172, China","Guangdong Engineering Center for Social Computing and Mental Health, Shenzhen 518172, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen 518172, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4388482657"]},{"raw_affiliation_string":"Guangdong Engineering Center for Social Computing and Mental Health, Shenzhen 518172, China","institution_ids":["https://openalex.org/I4210144487"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040908982","display_name":"Yuejin Li","orcid":"https://orcid.org/0000-0003-1284-4668"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210144487","display_name":"Cloud Computing Center","ror":"https://ror.org/04aa0zm65","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144487"]},{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuejin Li","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen 518172, China","Guangdong Engineering Center for Social Computing and Mental Health, Shenzhen 518172, China"],"raw_orcid":"https://orcid.org/0000-0003-1284-4668","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen 518172, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4388482657"]},{"raw_affiliation_string":"Guangdong Engineering Center for Social Computing and Mental Health, Shenzhen 518172, China","institution_ids":["https://openalex.org/I4210144487"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100669792","display_name":"Shijie Zhang","orcid":"https://orcid.org/0000-0002-9606-9955"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210144487","display_name":"Cloud Computing Center","ror":"https://ror.org/04aa0zm65","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210144487"]},{"id":"https://openalex.org/I4388482657","display_name":"Shenzhen MSU-BIT University","ror":"https://ror.org/02q963474","country_code":null,"type":"education","lineage":["https://openalex.org/I4388482657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shijie Zhang","raw_affiliation_strings":["Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen 518172, China","Guangdong Engineering Center for Social Computing and Mental Health, Shenzhen 518172, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Research Institute, Shenzhen MSU-BIT University, Shenzhen 518172, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4388482657"]},{"raw_affiliation_string":"Guangdong Engineering Center for Social Computing and Mental Health, Shenzhen 518172, China","institution_ids":["https://openalex.org/I4210144487"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5040908982"],"corresponding_institution_ids":["https://openalex.org/I180726961","https://openalex.org/I4210144487","https://openalex.org/I4388482657"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44594423,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"11","first_page":"451","last_page":"451"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.6432999968528748,"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":0.6432999968528748,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.23420000076293945,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.01899999938905239,"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/normalization","display_name":"Normalization (sociology)","score":0.7717000246047974},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5169000029563904},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.49140000343322754},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.44530001282691956},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.38370001316070557},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.33559998869895935},{"id":"https://openalex.org/keywords/data-integrity","display_name":"Data integrity","score":0.32280001044273376},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32089999318122864}],"concepts":[{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7717000246047974},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6237999796867371},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5194000005722046},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5169000029563904},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.49140000343322754},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45969998836517334},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.44530001282691956},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.38370001316070557},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35659998655319214},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C33762810","wikidata":"https://www.wikidata.org/wiki/Q461671","display_name":"Data integrity","level":2,"score":0.32280001044273376},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32089999318122864},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C2778597888","wikidata":"https://www.wikidata.org/wiki/Q172169","display_name":"3D city models","level":3,"score":0.28690001368522644},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.28209999203681946},{"id":"https://openalex.org/C83931994","wikidata":"https://www.wikidata.org/wiki/Q1149653","display_name":"Building automation","level":2,"score":0.2802000045776367},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.25839999318122864}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/ijgi14110451","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi14110451","pdf_url":"https://www.mdpi.com/2220-9964/14/11/451/pdf?version=1763281565","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"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":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0cef73f17db34503b930f969d680dee4","is_oa":true,"landing_page_url":"https://doaj.org/article/0cef73f17db34503b930f969d680dee4","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":"ISPRS International Journal of Geo-Information, Vol 14, Iss 11, p 451 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/ijgi14110451","is_oa":true,"landing_page_url":"https://doi.org/10.3390/ijgi14110451","pdf_url":"https://www.mdpi.com/2220-9964/14/11/451/pdf?version=1763281565","source":{"id":"https://openalex.org/S2764431341","display_name":"ISPRS International Journal of Geo-Information","issn_l":"2220-9964","issn":["2220-9964"],"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":"ISPRS International Journal of Geo-Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416334864.pdf","grobid_xml":"https://content.openalex.org/works/W4416334864.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1828186598","https://openalex.org/W2049981393","https://openalex.org/W2074063769","https://openalex.org/W2085665642","https://openalex.org/W2153538582","https://openalex.org/W2313572248","https://openalex.org/W2326674917","https://openalex.org/W2421256883","https://openalex.org/W2620693754","https://openalex.org/W2801305081","https://openalex.org/W2811144660","https://openalex.org/W2895794596","https://openalex.org/W2896365540","https://openalex.org/W2908048833","https://openalex.org/W2940726923","https://openalex.org/W2941529264","https://openalex.org/W3027225766","https://openalex.org/W3036453075","https://openalex.org/W3120467244","https://openalex.org/W3123813572","https://openalex.org/W3138516171","https://openalex.org/W3194968429","https://openalex.org/W4200020949","https://openalex.org/W4205695458","https://openalex.org/W4210544941","https://openalex.org/W4225105850","https://openalex.org/W4288901840","https://openalex.org/W4311849222","https://openalex.org/W4312549298","https://openalex.org/W4315781153","https://openalex.org/W4319300062","https://openalex.org/W4319596959","https://openalex.org/W4362472800","https://openalex.org/W4375870087"],"related_works":[],"abstract_inverted_index":{"Urban":[0],"building":[1],"change":[2,110],"detection":[3],"(UBCD)":[4],"is":[5,66,179],"essential":[6],"for":[7,190],"urban":[8,197],"planning,":[9],"land-use":[10],"monitoring,":[11],"and":[12,26,51,57,78,92,115,128,195],"smart":[13],"city":[14,193],"analytics,":[15],"yet":[16],"bi-temporal":[17],"optical":[18],"methods":[19],"remain":[20],"limited":[21],"by":[22],"spectral":[23],"confusion,":[24],"occlusions,":[25],"weak":[27],"sensitivity":[28],"to":[29,82,120,165],"structural":[30,86],"change.":[31],"To":[32],"overcome":[33],"these":[34],"challenges,":[35],"we":[36],"propose":[37],"DDDMNet,":[38],"a":[39,96],"lightweight":[40],"deep":[41],"learning":[42],"framework":[43],"that":[44,144,177],"fuses":[45],"multi-source":[46,146],"inputs\u2014including":[47],"DSM,":[48],"dnDSM,":[49,149],"DOM,":[50],"NDVI\u2014to":[52],"jointly":[53],"model":[54,81],"geometric,":[55],"spectral,":[56],"environmental":[58],"cues.":[59],"A":[60],"core":[61],"component":[62],"of":[63],"the":[64,67,80],"network":[65],"DSM":[68],"Difference":[69],"Normalization":[70],"Module":[71],"(DDDM),":[72],"which":[73],"explicitly":[74],"normalizes":[75],"elevation":[76],"differences":[77],"directs":[79],"focus":[83],"on":[84],"height-related":[85],"variations":[87],"such":[88],"as":[89],"rooftop":[90],"additions":[91],"demolition.":[93],"Embedded":[94],"into":[95],"TinyCD":[97],"backbone,":[98],"DDDMNet":[99,117,178],"achieves":[100,118],"efficient":[101],"inference":[102],"with":[103],"low":[104],"memory":[105],"cost":[106],"while":[107],"preserving":[108],"detail-level":[109],"fidelity.":[111],"Across":[112],"LEVIR-CD,":[113],"WHU-CD,":[114],"DSIFN,":[116],"up":[119],"93.32%":[121],"F1-score,":[122],"89.05%":[123],"Intersection":[124],"over":[125],"Union":[126],"(IoU),":[127],"99.61%":[129],"Overall":[130],"Accuracy":[131],"(OA),":[132],"demonstrating":[133],"consistently":[134],"strong":[135,188],"performance":[136],"across":[137],"diverse":[138,200],"benchmarks.":[139],"Ablation":[140],"analysis":[141],"further":[142],"shows":[143],"removing":[145,159],"fusion,":[147],"DDDM,":[148],"or":[150],"morphological":[151],"refinement":[152],"causes":[153],"notable":[154],"drops":[155],"in":[156,171],"performance\u2014for":[157],"example,":[158],"DDDM":[160],"reduces":[161],"IoU":[162],"from":[163],"88.12%":[164],"74.62%,":[166],"underscoring":[167],"its":[168],"critical":[169],"role":[170],"geometric":[172],"normalization.":[173],"These":[174],"results":[175],"demonstrate":[176],"not":[180],"only":[181],"accurate":[182],"but":[183],"also":[184],"practically":[185],"deployable,":[186],"offering":[187],"potential":[189],"scalable":[191],"3D":[192],"updates":[194],"long-term":[196],"monitoring":[198],"under":[199],"data":[201],"conditions.":[202]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-11-18T00:00:00"}
