{"id":"https://openalex.org/W7114911561","doi":"https://doi.org/10.1145/3748636.3764183","title":"MVeLMA: Multimodal Vegetation Loss Modeling Architecture for Predicting Post-fire Vegetation Loss","display_name":"MVeLMA: Multimodal Vegetation Loss Modeling Architecture for Predicting Post-fire Vegetation Loss","publication_year":2025,"publication_date":"2025-11-03","ids":{"openalex":"https://openalex.org/W7114911561","doi":"https://doi.org/10.1145/3748636.3764183"},"language":null,"primary_location":{"id":"doi:10.1145/3748636.3764183","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748636.3764183","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3748636.3764183","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Meenu Ravi","orcid":"https://orcid.org/0009-0002-0616-4674"},"institutions":[{"id":"https://openalex.org/I4210137942","display_name":"D-Tech (United States)","ror":"https://ror.org/03tw6b878","country_code":"US","type":"company","lineage":["https://openalex.org/I4210137942"]},{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Meenu Ravi","raw_affiliation_strings":["Computer Science, Virginia Tech, Alexandria, Virginia, USA"],"raw_orcid":"https://orcid.org/0009-0002-0616-4674","affiliations":[{"raw_affiliation_string":"Computer Science, Virginia Tech, Alexandria, Virginia, USA","institution_ids":["https://openalex.org/I859038795","https://openalex.org/I4210137942"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shailik Sarkar","orcid":"https://orcid.org/0000-0001-6544-2262"},"institutions":[{"id":"https://openalex.org/I4210137942","display_name":"D-Tech (United States)","ror":"https://ror.org/03tw6b878","country_code":"US","type":"company","lineage":["https://openalex.org/I4210137942"]},{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shailik Sarkar","raw_affiliation_strings":["Department of Computer Science, Virginia Tech, Alexandria, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0001-6544-2262","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Virginia Tech, Alexandria, Virginia, USA","institution_ids":["https://openalex.org/I859038795","https://openalex.org/I4210137942"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yanshen Sun","orcid":"https://orcid.org/0000-0002-4185-0066"},"institutions":[{"id":"https://openalex.org/I4210137942","display_name":"D-Tech (United States)","ror":"https://ror.org/03tw6b878","country_code":"US","type":"company","lineage":["https://openalex.org/I4210137942"]},{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanshen Sun","raw_affiliation_strings":["Department of Computer Science, Virginia Tech, Alexandria, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0002-4185-0066","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Virginia Tech, Alexandria, Virginia, USA","institution_ids":["https://openalex.org/I859038795","https://openalex.org/I4210137942"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Vaishnavi Singh","orcid":"https://orcid.org/0000-0002-5569-0534"},"institutions":[{"id":"https://openalex.org/I184565670","display_name":"Georgetown University","ror":"https://ror.org/05vzafd60","country_code":"US","type":"education","lineage":["https://openalex.org/I184565670"]},{"id":"https://openalex.org/I865166595","display_name":"George Washington University Virginia Campus","ror":"https://ror.org/03ms79854","country_code":"US","type":"education","lineage":["https://openalex.org/I865166595"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vaishnavi Singh","raw_affiliation_strings":["Computer Science, Georgetown University, Alexandria, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0002-5569-0534","affiliations":[{"raw_affiliation_string":"Computer Science, Georgetown University, Alexandria, Virginia, USA","institution_ids":["https://openalex.org/I184565670","https://openalex.org/I865166595"]}]},{"author_position":"last","author":{"id":null,"display_name":"Chang-Tien Lu","orcid":"https://orcid.org/0000-0003-3675-0199"},"institutions":[{"id":"https://openalex.org/I4210137942","display_name":"D-Tech (United States)","ror":"https://ror.org/03tw6b878","country_code":"US","type":"company","lineage":["https://openalex.org/I4210137942"]},{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chang-Tien Lu","raw_affiliation_strings":["Department of Computer Science, Virginia Tech, Alexandria, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0003-3675-0199","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Virginia Tech, Alexandria, Virginia, USA","institution_ids":["https://openalex.org/I859038795","https://openalex.org/I4210137942"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.54539995,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1094","last_page":"1105"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10555","display_name":"Fire effects on ecosystems","score":0.9815000295639038,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10555","display_name":"Fire effects on ecosystems","score":0.9815000295639038,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T13388","display_name":"Rangeland and Wildlife Management","score":0.002899999963119626,"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/T10535","display_name":"Landslides and related hazards","score":0.0013000000035390258,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"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/vegetation","display_name":"Vegetation (pathology)","score":0.7441999912261963},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.6978999972343445},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4878999888896942},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4876999855041504},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.375900000333786},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.34599998593330383},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3407999873161316}],"concepts":[{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.7441999912261963},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6978999972343445},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4878999888896942},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4876999855041504},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.4812999963760376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4154999852180481},{"id":"https://openalex.org/C107826830","wikidata":"https://www.wikidata.org/wiki/Q929380","display_name":"Environmental resource management","level":1,"score":0.4059000015258789},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.375900000333786},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.34599998593330383},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3407999873161316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.320499986410141},{"id":"https://openalex.org/C110872660","wikidata":"https://www.wikidata.org/wiki/Q37813","display_name":"Ecosystem","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C64107356","wikidata":"https://www.wikidata.org/wiki/Q295046","display_name":"Ecosystem model","level":3,"score":0.2962000072002411},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C29376679","wikidata":"https://www.wikidata.org/wiki/Q241741","display_name":"Wildlife","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.26429998874664307},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.2583000063896179}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3748636.3764183","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748636.3764183","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3748636.3764183","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748636.3764183","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.7811064124107361}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W145098650","https://openalex.org/W1940872118","https://openalex.org/W2064675550","https://openalex.org/W2084744129","https://openalex.org/W2111688235","https://openalex.org/W2606466198","https://openalex.org/W2787931125","https://openalex.org/W2794163602","https://openalex.org/W2893995718","https://openalex.org/W2936752304","https://openalex.org/W2955786086","https://openalex.org/W2964121744","https://openalex.org/W2964406534","https://openalex.org/W2997047947","https://openalex.org/W3008626511","https://openalex.org/W3023897562","https://openalex.org/W3118532264","https://openalex.org/W3138424759","https://openalex.org/W3161820035","https://openalex.org/W3214261469","https://openalex.org/W4205464866","https://openalex.org/W4225363088","https://openalex.org/W4281393096","https://openalex.org/W4283023047","https://openalex.org/W4291824800","https://openalex.org/W4293059524","https://openalex.org/W4293375396","https://openalex.org/W4294189281","https://openalex.org/W4308500233","https://openalex.org/W4310064234","https://openalex.org/W4313070860","https://openalex.org/W4360980560","https://openalex.org/W4363647732","https://openalex.org/W4376270005","https://openalex.org/W4377231865","https://openalex.org/W4386747494","https://openalex.org/W4388482316","https://openalex.org/W4391809618","https://openalex.org/W4393377413","https://openalex.org/W4394710601","https://openalex.org/W4395009837","https://openalex.org/W4399262691","https://openalex.org/W4399267973","https://openalex.org/W4399802203","https://openalex.org/W4402989352","https://openalex.org/W4403847109","https://openalex.org/W4403993149","https://openalex.org/W4404886563","https://openalex.org/W4404960932","https://openalex.org/W4406460198","https://openalex.org/W4406946769","https://openalex.org/W4408219062","https://openalex.org/W4408242948","https://openalex.org/W4408858305","https://openalex.org/W4408937668","https://openalex.org/W4409260756","https://openalex.org/W4410004185","https://openalex.org/W4416878691","https://openalex.org/W6910865527","https://openalex.org/W6967342698"],"related_works":[],"abstract_inverted_index":{"Understanding":[0],"post-wildfire":[1,139],"vegetation":[2,93,140,145],"loss":[3,94,146],"is":[4,13,56],"critical":[5],"for":[6],"developing":[7],"effective":[8],"ecological":[9,172],"recovery":[10,156,177],"strategies":[11],"and":[12,21,45,105,134,175],"often":[14],"challenging":[15],"due":[16],"to":[17,24,90,110,149,166],"the":[18,26,40,164],"extended":[19],"time":[20],"effort":[22],"required":[23],"capture":[25,111],"evolving":[27],"ecosystem":[28],"features.":[29],"Recent":[30],"works":[31],"in":[32,53,63,70,137],"this":[33,54,74,161],"area":[34],"have":[35,163],"not":[36],"fully":[37],"explored":[38],"all":[39],"contributing":[41],"factors,":[42],"their":[43],"modalities,":[44],"interactions":[46],"with":[47],"each":[48],"other.":[49],"Furthermore,":[50,142],"most":[51],"research":[52],"domain":[55],"limited":[57],"by":[58],"a":[59,78,100,106],"lack":[60],"of":[61,160],"interpretability":[62],"predictive":[64],"modeling,":[65],"making":[66],"it":[67],"less":[68],"useful":[69],"real-world":[71],"settings.":[72],"In":[73],"work,":[75],"we":[76,125,143],"propose":[77],"novel":[79],"end-to-end":[80],"ML":[81],"pipeline":[82,104],"called":[83],"MVeLMA":[84,98],"(Multimodal":[85],"Vegetation":[86],"Loss":[87],"Modeling":[88],"Architecture)":[89],"predict":[91],"county-wise":[92],"from":[95],"fire":[96],"events.":[97],"uses":[99],"multimodal":[101],"feature":[102],"integration":[103],"stacked":[107],"ensemble-based":[108],"architecture":[109],"different":[112],"modalities":[113],"while":[114],"also":[115],"incorporating":[116],"uncertainty":[117],"estimation":[118],"through":[119],"probabilistic":[120],"modeling.":[121],"Through":[122],"comprehensive":[123],"experiments,":[124],"show":[126],"that":[127],"our":[128],"model":[129],"outperforms":[130],"several":[131],"state-of-the-art":[132],"(SOTA)":[133],"baseline":[135],"models":[136],"predicting":[138],"loss.":[141],"generate":[144],"confidence":[147],"maps":[148],"identify":[150],"high-risk":[151],"counties,":[152],"thereby":[153],"helping":[154],"targeted":[155],"efforts.":[157],"The":[158],"findings":[159],"work":[162],"potential":[165],"inform":[167],"future":[168],"disaster":[169],"relief":[170],"planning,":[171],"policy":[173],"development,":[174],"wildlife":[176],"management.":[178]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-12T00:00:00"}
