{"id":"https://openalex.org/W2774337550","doi":"https://doi.org/10.1109/igarss.2017.8127326","title":"Feature extraction and machine learning for the classification of active cropland in the Aral Sea Basin","display_name":"Feature extraction and machine learning for the classification of active cropland in the Aral Sea Basin","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2774337550","doi":"https://doi.org/10.1109/igarss.2017.8127326","mag":"2774337550"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2017.8127326","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8127326","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5052953948","display_name":"Dimo Dimov","orcid":"https://orcid.org/0000-0001-8649-9508"},"institutions":[{"id":"https://openalex.org/I25974101","display_name":"University of W\u00fcrzburg","ror":"https://ror.org/00fbnyb24","country_code":"DE","type":"education","lineage":["https://openalex.org/I25974101"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Dimo Dimov","raw_affiliation_strings":["Department of Remote Sensing, University of W\u00fcrzburg","MapTailor Geospatial Consulting GbR, Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Remote Sensing, University of W\u00fcrzburg","institution_ids":["https://openalex.org/I25974101"]},{"raw_affiliation_string":"MapTailor Geospatial Consulting GbR, Bonn, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091004151","display_name":"Fabian L\u00f6w","orcid":"https://orcid.org/0000-0002-0632-890X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fabian Low","raw_affiliation_strings":["MapTailor Geospatial Consulting GbR, Bonn, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MapTailor Geospatial Consulting GbR, Bonn, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108187656","display_name":"Mirzahayot Ibrakhimov","orcid":null},"institutions":[{"id":"https://openalex.org/I4401041613","display_name":"Khorezm Rural Advisory Support Service","ror":"https://ror.org/04m053216","country_code":null,"type":"facility","lineage":["https://openalex.org/I4401041613"]}],"countries":["UZ"],"is_corresponding":false,"raw_author_name":"Mirzahayot Ibrakhimov","raw_affiliation_strings":["Khorezm Rural Advisory Support Service, Urgench, Uzbekistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Khorezm Rural Advisory Support Service, Urgench, Uzbekistan","institution_ids":["https://openalex.org/I4401041613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5097466683","display_name":"Sarah-Schonbrodt-Stitt","orcid":null},"institutions":[{"id":"https://openalex.org/I25974101","display_name":"University of W\u00fcrzburg","ror":"https://ror.org/00fbnyb24","country_code":"DE","type":"education","lineage":["https://openalex.org/I25974101"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sarah-Schonbrodt-Stitt","raw_affiliation_strings":["Department of Remote Sensing, University of W\u00fcrzburg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Remote Sensing, University of W\u00fcrzburg","institution_ids":["https://openalex.org/I25974101"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047627769","display_name":"Christopher Conrad","orcid":"https://orcid.org/0000-0002-0807-7059"},"institutions":[{"id":"https://openalex.org/I25974101","display_name":"University of W\u00fcrzburg","ror":"https://ror.org/00fbnyb24","country_code":"DE","type":"education","lineage":["https://openalex.org/I25974101"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christopher Conrad","raw_affiliation_strings":["Department of Remote Sensing, University of W\u00fcrzburg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Remote Sensing, University of W\u00fcrzburg","institution_ids":["https://openalex.org/I25974101"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4644,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.85843451,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"3","issue":null,"first_page":"1804","last_page":"1807"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9926000237464905,"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":0.9926000237464905,"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":0.9916999936103821,"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":0.9765999913215637,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6154190301895142},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.567414402961731},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5178097486495972},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4899863302707672},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4335455596446991},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.4222317337989807},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.41772282123565674},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.41733431816101074},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.416459858417511},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4101378321647644},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3552526831626892},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2037903368473053}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6154190301895142},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.567414402961731},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5178097486495972},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4899863302707672},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4335455596446991},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.4222317337989807},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.41772282123565674},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.41733431816101074},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.416459858417511},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4101378321647644},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3552526831626892},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2037903368473053},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss.2017.8127326","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2017.8127326","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},{"id":"pmh:oai:elib.dlr.de:115961","is_oa":false,"landing_page_url":"https://elib.dlr.de/115961/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Konferenzbeitrag"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1984792953","https://openalex.org/W2047191928","https://openalex.org/W2067191022","https://openalex.org/W2084502283","https://openalex.org/W2108597246","https://openalex.org/W2179290474","https://openalex.org/W2411930473","https://openalex.org/W2503759777","https://openalex.org/W4302190632","https://openalex.org/W6685336383","https://openalex.org/W6715087026"],"related_works":["https://openalex.org/W4285411112","https://openalex.org/W2085033728","https://openalex.org/W2171299904","https://openalex.org/W2922442631","https://openalex.org/W2053596378","https://openalex.org/W1982025852","https://openalex.org/W2168523118","https://openalex.org/W2106540031","https://openalex.org/W2047970610","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Agricultural":[0],"monitoring":[1],"over":[2],"large":[3,27],"areas":[4],"such":[5,32,233],"as":[6,33,234],"the":[7,11,36,76,79,83,116,167,176,184,235],"irrigation":[8],"zones":[9],"of":[10,45,78,110,118,142,178,223,237],"Aral":[12],"Sea":[13],"Basin":[14],"(ASB)":[15],"needs":[16],"Remote":[17],"Sensing":[18],"imagery":[19,56],"with":[20,62,100,107,213],"a":[21,26,108,126],"high":[22],"temporal":[23],"resolution":[24,55],"and":[25,74,98,134,196,241],"swath":[28],"width.":[29],"Satellite":[30],"sensors":[31],"MODIS":[34],"or":[35,218],"upcoming":[37],"Sentinel-3":[38],"suits":[39],"these":[40],"requirements.":[41],"A":[42,156],"clear":[43],"discrimination":[44],"active":[46,80,179,224],"cropland":[47,81,180,225],"coverage":[48],"however":[49],"is":[50,137,160,181,191],"impossible":[51],"using":[52],"low":[53],"spatial":[54],"due":[57,193],"to":[58,115,139,148,162,194,205],"mixed":[59],"pixel":[60],"effects":[61],"other":[63],"landcover":[64],"types.":[65],"In":[66],"this":[67],"paper":[68],"we":[69],"utilized":[70],"Landsat":[71,102,112],"8":[72],"data":[73,121,212],"present":[75],"derivation":[77],"in":[82,104],"ASB":[84],"for":[85,122,152,186,226],"3":[86],"consecutive":[87],"years":[88],"(2014-2016).":[89],"Each":[90],"observed":[91],"year":[92],"comprises":[93],"two":[94],"growing":[95],"seasons":[96],"(spring":[97],"summer)":[99],"40":[101],"scenes":[103],"each":[105,227],"season,":[106],"total":[109],"240":[111],"scenes.":[113,220],"Due":[114],"lack":[117],"adequate":[119],"in-situ":[120],"remote":[123],"agricultural":[124,143],"regions,":[125],"feature":[127],"extraction":[128,177,222],"method":[129],"based":[130],"on":[131,210],"image":[132,153],"segmentation":[133],"k-means":[135],"clustering":[136],"applied":[138],"delineate":[140],"samples":[141],"fields":[144],"which":[145,190],"are":[146],"forwarded":[147],"machine":[149,207],"learning":[150,208],"algorithms":[151],"classification":[154],"including.":[155],"simple":[157],"markovian":[158],"logic":[159],"used":[161],"introduce":[163],"prior":[164],"distribution":[165],"values":[166],"following":[168],"observation":[169],"year.":[170],"The":[171,221],"results":[172],"clearly":[173],"show,":[174],"that":[175],"possible":[182],"without":[183],"need":[185],"time":[187],"series":[188],"data,":[189],"limited":[192],"clouds":[195],"acquisition":[197],"date":[198],"irregularity.":[199],"Model":[200],"transferability":[201],"tests":[202],"were":[203],"performed":[204],"assess":[206],"inference":[209],"unseen":[211],"training":[214],"datasets":[215],"from":[216],"adjacent":[217],"non-adjacent":[219],"season":[228],"also":[229],"yielded":[230],"secondary":[231],"information":[232],"assessment":[236],"land":[238],"use":[239],"intensities":[240],"crop":[242],"rotation":[243],"patterns.":[244]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}