{"id":"https://openalex.org/W2584042228","doi":"https://doi.org/10.1109/bigdata.2016.7840735","title":"Scalable nearest neighbor based hierarchical change detection framework for crop monitoring","display_name":"Scalable nearest neighbor based hierarchical change detection framework for crop monitoring","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2584042228","doi":"https://doi.org/10.1109/bigdata.2016.7840735","mag":"2584042228"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2016.7840735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840735","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Big Data (Big 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/A5101797800","display_name":"Zexi Chen","orcid":"https://orcid.org/0000-0001-9549-9323"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zexi Chen","raw_affiliation_strings":["North Carolina State University, 890 Oval Dr, Raleigh, NC 27606"],"affiliations":[{"raw_affiliation_string":"North Carolina State University, 890 Oval Dr, Raleigh, NC 27606","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065410886","display_name":"Ranga Raju Vatsavai","orcid":"https://orcid.org/0000-0002-7083-0267"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ranga Raju Vatsavai","raw_affiliation_strings":["North Carolina State University, 890 Oval Dr, Raleigh, NC 27606"],"affiliations":[{"raw_affiliation_string":"North Carolina State University, 890 Oval Dr, Raleigh, NC 27606","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018612636","display_name":"Bharathkumar Ramachandra","orcid":"https://orcid.org/0000-0001-9671-6430"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bharathkumar Ramachandra","raw_affiliation_strings":["North Carolina State University, 890 Oval Dr, Raleigh, NC 27606"],"affiliations":[{"raw_affiliation_string":"North Carolina State University, 890 Oval Dr, Raleigh, NC 27606","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100381867","display_name":"Qiang Zhang","orcid":"https://orcid.org/0000-0001-8389-4713"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiang Zhang","raw_affiliation_strings":["North Carolina State University, 890 Oval Dr, Raleigh, NC 27606"],"affiliations":[{"raw_affiliation_string":"North Carolina State University, 890 Oval Dr, Raleigh, NC 27606","institution_ids":["https://openalex.org/I137902535"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111835525","display_name":"Nagendra Singh","orcid":null},"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":false,"raw_author_name":"Nagendra Singh","raw_affiliation_strings":["Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN 37831"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN 37831","institution_ids":["https://openalex.org/I1289243028"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079418386","display_name":"Sreenivas R. Sukumar","orcid":"https://orcid.org/0000-0003-4031-2888"},"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":false,"raw_author_name":"Sreenivas Sukumar","raw_affiliation_strings":["Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN 37831"],"affiliations":[{"raw_affiliation_string":"Oak Ridge National Laboratory, 1 Bethel Valley Rd, Oak Ridge, TN 37831","institution_ids":["https://openalex.org/I1289243028"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101797800"],"corresponding_institution_ids":["https://openalex.org/I137902535"],"apc_list":null,"apc_paid":null,"fwci":0.9012,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.79348263,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"351","issue":null,"first_page":"1309","last_page":"1314"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9986000061035156,"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":0.9986000061035156,"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":0.9975000023841858,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.8032267093658447},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7328312397003174},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5471538305282593},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5263979434967041},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5091056227684021},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3558594882488251},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3546912670135498},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.35314667224884033},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24905571341514587},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.16287559270858765}],"concepts":[{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.8032267093658447},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7328312397003174},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5471538305282593},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5263979434967041},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5091056227684021},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3558594882488251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3546912670135498},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.35314667224884033},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24905571341514587},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.16287559270858765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2016.7840735","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2016.7840735","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W2036798369","https://openalex.org/W2055425291","https://openalex.org/W2066069035","https://openalex.org/W2089441588","https://openalex.org/W2105756833","https://openalex.org/W2125588903","https://openalex.org/W2170140722","https://openalex.org/W2989983865","https://openalex.org/W6636950212"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W2376528221","https://openalex.org/W196800607","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W2015705630","https://openalex.org/W2355368334","https://openalex.org/W2073313993"],"abstract_inverted_index":{"Monitoring":[0],"biomass":[1],"over":[2],"large":[3],"geographic":[4],"regions":[5,157],"for":[6,15,59,70,107],"changes":[7,110,179],"in":[8,19,46,159,180],"vegetation":[9,20],"and":[10,29,35,41,62,138,173],"cropping":[11],"patterns":[12],"is":[13,43,80,148],"important":[14],"many":[16],"applications.":[17],"Changes":[18],"happen":[21],"due":[22],"to":[23,31,81,182],"reasons":[24],"ranging":[25],"from":[26,118],"climate":[27],"change":[28,47,53,83,94,104,139,156],"damages":[30],"new":[32],"government":[33],"policies":[34],"regulations.":[36],"Remote":[37],"sensing":[38],"imagery":[39],"(multi-spectral":[40],"multi-temporal)":[42],"widely":[44,169],"used":[45,170],"pattern":[48],"mapping":[49],"studies.":[50],"Existing":[51],"bi-temporal":[52],"detection":[54,105,140],"techniques":[55,66],"are":[56,67],"better":[57],"suited":[58,69],"multi-spectral":[60],"images":[61],"time":[63,100,120],"series":[64,101,121],"based":[65,103,136],"more":[68],"analyzing":[71],"multi-temporal":[72],"images.":[73],"A":[74],"key":[75],"contribution":[76],"of":[77,93,115,127],"this":[78,91],"work":[79],"define":[82],"as":[84],"hierarchical":[85,130],"rather":[86],"than":[87],"boolean.":[88],"Based":[89],"on":[90],"definition":[92],"pattern,":[95],"we":[96,150],"developed":[97],"a":[98],"novel":[99],"similarity":[102,142],"framework":[106,125],"identifying":[108],"inter-annual":[109],"by":[111],"exploiting":[112],"phenological":[113],"properties":[114],"growing":[116],"crops":[117],"satellite":[119],"imagery.":[122],"The":[123],"proposed":[124,146,184],"consists":[126],"three":[128],"components:":[129],"clustering":[131,172],"tree":[132],"construction,":[133],"nearest":[134],"neighbor":[135],"classification,":[137],"using":[141,153],"hierarchy.":[143],"Though":[144],"the":[145,160,168],"approach":[147],"unsupervised,":[149],"present":[151],"evaluation":[152,174],"manually":[154],"induced":[155],"embedded":[158],"real":[161],"dataset.":[162],"We":[163],"compare":[164],"our":[165,183],"method":[166],"with":[167],"K-Means":[171,177],"shows":[175],"that":[176],"over-detects":[178],"comparison":[181],"method.":[185]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
