{"id":"https://openalex.org/W4387801798","doi":"https://doi.org/10.1109/igarss52108.2023.10281936","title":"Seasonal Forest Disturbance Detection Using Sentinel-1 SAR & Sentinel-2 Optical Timeseries Data and Transformers","display_name":"Seasonal Forest Disturbance Detection Using Sentinel-1 SAR & Sentinel-2 Optical Timeseries Data and Transformers","publication_year":2023,"publication_date":"2023-07-16","ids":{"openalex":"https://openalex.org/W4387801798","doi":"https://doi.org/10.1109/igarss52108.2023.10281936"},"language":"en","primary_location":{"id":"doi:10.1109/igarss52108.2023.10281936","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10281936","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://edepot.wur.nl/641049","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022899478","display_name":"Adugna Mullissa","orcid":"https://orcid.org/0000-0001-7711-8523"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Adugna Mullissa","raw_affiliation_strings":["CTREES.org,Pasadena,CA,United States,91105"],"affiliations":[{"raw_affiliation_string":"CTREES.org,Pasadena,CA,United States,91105","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004918175","display_name":"Johannes Reiche","orcid":"https://orcid.org/0000-0002-4327-4349"},"institutions":[{"id":"https://openalex.org/I913481162","display_name":"Wageningen University & Research","ror":"https://ror.org/04qw24q55","country_code":"NL","type":"education","lineage":["https://openalex.org/I913481162"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Johannes Reiche","raw_affiliation_strings":["Wageningen University,Laboratory of Geo-Information Science and Remote Sensing,the Netherlands","Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, the Netherlands"],"affiliations":[{"raw_affiliation_string":"Wageningen University,Laboratory of Geo-Information Science and Remote Sensing,the Netherlands","institution_ids":["https://openalex.org/I913481162"]},{"raw_affiliation_string":"Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, the Netherlands","institution_ids":["https://openalex.org/I913481162"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042922619","display_name":"Sassan Saatchi","orcid":"https://orcid.org/0000-0001-8524-4917"},"institutions":[{"id":"https://openalex.org/I1334627681","display_name":"Jet Propulsion Laboratory","ror":"https://ror.org/027k65916","country_code":"US","type":"facility","lineage":["https://openalex.org/I122411786","https://openalex.org/I1334627681","https://openalex.org/I4210124779"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sassan Saatchi","raw_affiliation_strings":["CTREES.org,Pasadena,CA,United States,91105","NASA, Jet Propulsion Laboratory, Pasadena, CA, United States"],"affiliations":[{"raw_affiliation_string":"CTREES.org,Pasadena,CA,United States,91105","institution_ids":[]},{"raw_affiliation_string":"NASA, Jet Propulsion Laboratory, Pasadena, CA, United States","institution_ids":["https://openalex.org/I1334627681"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5022899478"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1251,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44293574,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"3122","last_page":"3124"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9994000196456909,"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":0.9994000196456909,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9988999962806702,"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/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"}}],"keywords":[{"id":"https://openalex.org/keywords/disturbance","display_name":"Disturbance (geology)","score":0.5635187029838562},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.5544047355651855},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.5389687418937683},{"id":"https://openalex.org/keywords/forest-ecology","display_name":"Forest ecology","score":0.5117204189300537},{"id":"https://openalex.org/keywords/seasonality","display_name":"Seasonality","score":0.5115700364112854},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5076709985733032},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4745134711265564},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4408462941646576},{"id":"https://openalex.org/keywords/ecosystem","display_name":"Ecosystem","score":0.4290429353713989},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.24736618995666504},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2424369752407074},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.20232558250427246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.07910043001174927}],"concepts":[{"id":"https://openalex.org/C2777601987","wikidata":"https://www.wikidata.org/wiki/Q5283581","display_name":"Disturbance (geology)","level":2,"score":0.5635187029838562},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5544047355651855},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.5389687418937683},{"id":"https://openalex.org/C73935091","wikidata":"https://www.wikidata.org/wiki/Q2249329","display_name":"Forest ecology","level":3,"score":0.5117204189300537},{"id":"https://openalex.org/C125403950","wikidata":"https://www.wikidata.org/wiki/Q2111082","display_name":"Seasonality","level":2,"score":0.5115700364112854},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5076709985733032},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4745134711265564},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4408462941646576},{"id":"https://openalex.org/C110872660","wikidata":"https://www.wikidata.org/wiki/Q37813","display_name":"Ecosystem","level":2,"score":0.4290429353713989},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.24736618995666504},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2424369752407074},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.20232558250427246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.07910043001174927},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss52108.2023.10281936","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss52108.2023.10281936","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:library.wur.nl:wurpubs/620602","is_oa":true,"landing_page_url":"https://research.wur.nl/en/publications/seasonal-forest-disturbance-detection-using-sentinel-1-sar-amp-se","pdf_url":"https://edepot.wur.nl/641049","source":{"id":"https://openalex.org/S4210201231","display_name":"Socio-Environmental Systems Modeling","issn_l":"2663-3027","issn":["2663-3027"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9798350331745","raw_type":"Article in monograph or in proceedings"}],"best_oa_location":{"id":"pmh:oai:library.wur.nl:wurpubs/620602","is_oa":true,"landing_page_url":"https://research.wur.nl/en/publications/seasonal-forest-disturbance-detection-using-sentinel-1-sar-amp-se","pdf_url":"https://edepot.wur.nl/641049","source":{"id":"https://openalex.org/S4210201231","display_name":"Socio-Environmental Systems Modeling","issn_l":"2663-3027","issn":["2663-3027"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"ISBN: 9798350331745","raw_type":"Article in monograph or in proceedings"},"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387801798.pdf"},"referenced_works_count":8,"referenced_works":["https://openalex.org/W1981213426","https://openalex.org/W2288373547","https://openalex.org/W2766826930","https://openalex.org/W2903282641","https://openalex.org/W2944851425","https://openalex.org/W3163231391","https://openalex.org/W4385245566","https://openalex.org/W6739901393"],"related_works":["https://openalex.org/W2038604956","https://openalex.org/W2296560746","https://openalex.org/W2338222801","https://openalex.org/W2347583731","https://openalex.org/W2106602008","https://openalex.org/W2067832159","https://openalex.org/W2153353177","https://openalex.org/W3156121563","https://openalex.org/W1431410746","https://openalex.org/W4301756917"],"abstract_inverted_index":{"Tropical":[0],"seasonal":[1,35,96,127,177,182],"forests":[2],"make":[3,130],"up":[4],"40%":[5],"of":[6,57,69,81,87,173],"the":[7,19,22,40,55,58,85,108,156,162,171],"globally":[8,78],"available":[9],"forest":[10,36,41,93,97,115,119,135,158,166,178],"stock":[11],"and":[12,44,49,75,79],"play":[13],"an":[14,131],"essential":[15],"role":[16],"in":[17,21,99,107,161,180,185],"regulating":[18],"variability":[20],"global":[23],"carbon":[24,42],"cycle.":[25],"Therefore,":[26,118],"there":[27],"is":[28,103,112],"a":[29,66,181],"strong":[30],"need":[31],"to":[32,38,45,129,153,164,175],"persistently":[33],"monitor":[34],"changes":[37,98],"understand":[39],"fluctuation":[43,106],"better":[46],"conserve":[47],"biodiversity":[48],"enforce":[50],"laws.":[51],"In":[52,137],"this":[53,138],"regard,":[54,139],"advent":[56],"European":[59],"Space":[60],"Agency":[61],"(ESA)":[62],"Copernicus":[63],"program":[64],"avails":[65],"dense":[67,100],"time-series":[68],"both":[70],"Synthetic":[71],"Aperture":[72],"Radar":[73],"(SAR)":[74],"optical":[76],"images,":[77],"free":[80],"charge,":[82],"that":[83,111],"enables":[84],"exploitation":[86],"these":[88,126],"images":[89],"for":[90,125,144],"near":[91],"real-time":[92],"monitoring.":[94],"Detecting":[95],"time-series,":[101],"however,":[102],"complicated":[104],"by":[105,114],"detected":[109],"signal":[110,163],"induced":[113],"phenology":[116],"change.":[117],"disturbance":[120,179],"detection":[121],"methods":[122],"should":[123],"account":[124],"fluctuations":[128],"accurate":[132],"inference":[133],"about":[134],"disturbances.":[136,167],"deep":[140],"learning":[141],"approaches":[142],"designed":[143],"sequential":[145],"data":[146],"such":[147],"as":[148],"Transformers":[149,174],"can":[150],"be":[151],"used":[152],"implicitly":[154],"learn":[155],"natural":[157],"seasonality":[159],"pattern":[160],"detect":[165,176],"This":[168],"abstract":[169],"demonstrates":[170],"efficacy":[172],"dry-forest":[183],"region":[184],"Bolivia.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-12T08:34:05.389933","created_date":"2025-10-10T00:00:00"}