{"id":"https://openalex.org/W2066069035","doi":"https://doi.org/10.1145/1601966.1601976","title":"Phenological event detection from multitemporal image data","display_name":"Phenological event detection from multitemporal image data","publication_year":2009,"publication_date":"2009-06-28","ids":{"openalex":"https://openalex.org/W2066069035","doi":"https://doi.org/10.1145/1601966.1601976","mag":"2066069035"},"language":"en","primary_location":{"id":"doi:10.1145/1601966.1601976","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1601966.1601976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data","raw_type":"proceedings-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/A5065410886","display_name":"Ranga Raju Vatsavai","orcid":"https://orcid.org/0000-0002-7083-0267"},"institutions":[{"id":"https://openalex.org/I1289243028","display_name":"Oak Ridge National Laboratory","ror":"https://ror.org/01qz5mb56","country_code":"US","type":"facility","lineage":["https://openalex.org/I1289243028","https://openalex.org/I1330989302","https://openalex.org/I39565521","https://openalex.org/I4210159294"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ranga Raju Vatsavai","raw_affiliation_strings":["Oak Ridge National Laboratory, Oak Ridge, TN","Oak Ridge National Laboratory, Oak Ridge, TN#TAB#"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory, Oak Ridge, TN","institution_ids":["https://openalex.org/I1289243028"]},{"raw_affiliation_string":"Oak Ridge National Laboratory, Oak Ridge, TN#TAB#","institution_ids":["https://openalex.org/I1289243028"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5065410886"],"corresponding_institution_ids":["https://openalex.org/I1289243028"],"apc_list":null,"apc_paid":null,"fwci":0.9466,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.77333174,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"49","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9993000030517578,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9896000027656555,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/phenology","display_name":"Phenology","score":0.8200985193252563},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6379881501197815},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.5951780080795288},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5649973154067993},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5636172294616699},{"id":"https://openalex.org/keywords/vegetation","display_name":"Vegetation (pathology)","score":0.5078471302986145},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.4944443702697754},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.48513469099998474},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4831940233707428},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.43978869915008545},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43911847472190857},{"id":"https://openalex.org/keywords/climate-change","display_name":"Climate change","score":0.3203296661376953},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.27883732318878174},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2070390284061432},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.15742215514183044},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.14740613102912903}],"concepts":[{"id":"https://openalex.org/C51417038","wikidata":"https://www.wikidata.org/wiki/Q272737","display_name":"Phenology","level":2,"score":0.8200985193252563},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6379881501197815},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.5951780080795288},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5649973154067993},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5636172294616699},{"id":"https://openalex.org/C2776133958","wikidata":"https://www.wikidata.org/wiki/Q7918366","display_name":"Vegetation (pathology)","level":2,"score":0.5078471302986145},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.4944443702697754},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.48513469099998474},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4831940233707428},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.43978869915008545},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43911847472190857},{"id":"https://openalex.org/C132651083","wikidata":"https://www.wikidata.org/wiki/Q7942","display_name":"Climate change","level":2,"score":0.3203296661376953},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.27883732318878174},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2070390284061432},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.15742215514183044},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.14740613102912903},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1601966.1601976","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1601966.1601976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1486632395","https://openalex.org/W1584380153","https://openalex.org/W1964293905","https://openalex.org/W1967687158","https://openalex.org/W1993395103","https://openalex.org/W2005073772","https://openalex.org/W2093033924","https://openalex.org/W2119513445","https://openalex.org/W2160566385","https://openalex.org/W2312997001"],"related_works":["https://openalex.org/W3207046288","https://openalex.org/W3023446922","https://openalex.org/W4324030030","https://openalex.org/W1980260791","https://openalex.org/W4385533602","https://openalex.org/W2373524250","https://openalex.org/W4206027277","https://openalex.org/W3189212133","https://openalex.org/W4382239404","https://openalex.org/W2803445926"],"abstract_inverted_index":{"Monitoring":[0],"biomass":[1],"over":[2],"large":[3],"geographic":[4],"regions":[5],"for":[6,16,53,89],"seasonal":[7],"changes":[8,78,84],"in":[9],"vegetation":[10],"and":[11,48,74],"crop":[12],"phenology":[13],"is":[14,62],"important":[15],"many":[17],"applications.":[18],"In":[19],"this":[20],"paper":[21],"we":[22],"a":[23,25],"present":[24],"novel":[26],"clustering":[27],"based":[28],"change":[29],"detection":[30],"method":[31],"using":[32],"MODIS":[33],"NDVI":[34],"time":[35],"series":[36],"data.":[37],"We":[38],"used":[39,64],"well":[40],"known":[41],"EM":[42],"technique":[43],"to":[44,65,76],"find":[45],"GMM":[46],"parameters":[47],"Bayesian":[49],"Information":[50],"Criteria":[51],"(BIC)":[52],"determining":[54],"the":[55,67],"number":[56],"of":[57,108],"clusters.":[58],"KL":[59],"Divergence":[60],"measure":[61],"then":[63],"establish":[66],"cluster":[68],"correspondence":[69],"across":[70],"two":[71,81],"years":[72],"(2001":[73],"2006)":[75],"determine":[77],"between":[79,99],"these":[80],"years.":[82],"The":[83],"identified":[85],"were":[86],"further":[87],"analyzed":[88],"understanding":[90],"phenological":[91,101],"events.":[92],"This":[93],"preliminary":[94],"study":[95],"shows":[96],"interesting":[97],"relationships":[98],"key":[100],"events":[102],"such":[103],"as":[104],"onset,":[105],"length,":[106],"end":[107],"growing":[109],"seasons.":[110]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}