{"id":"https://openalex.org/W4312378717","doi":"https://doi.org/10.1109/igarss46834.2022.9883703","title":"Evaluation of Evapotranspiration Classification Using Self Organizing Maps and Weather Research and Forecasting Variables","display_name":"Evaluation of Evapotranspiration Classification Using Self Organizing Maps and Weather Research and Forecasting Variables","publication_year":2022,"publication_date":"2022-07-17","ids":{"openalex":"https://openalex.org/W4312378717","doi":"https://doi.org/10.1109/igarss46834.2022.9883703"},"language":"en","primary_location":{"id":"doi:10.1109/igarss46834.2022.9883703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883703","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","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/A5053518376","display_name":"Mar\u00eda Solis-Aulestia","orcid":"https://orcid.org/0000-0002-1327-6458"},"institutions":[{"id":"https://openalex.org/I3130401523","display_name":"Universidad Yachay Tech","ror":"https://ror.org/04jjswc10","country_code":"EC","type":"education","lineage":["https://openalex.org/I3130401523"]}],"countries":["EC"],"is_corresponding":true,"raw_author_name":"Maria Solis-Aulestia","raw_affiliation_strings":["Yachay Tech University, Hacienda San José y Proyecto Yachay,Urcuquí,Ecuador,100115"],"affiliations":[{"raw_affiliation_string":"Yachay Tech University, Hacienda San José y Proyecto Yachay,Urcuquí,Ecuador,100115","institution_ids":["https://openalex.org/I3130401523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071753179","display_name":"Israel Pineda","orcid":"https://orcid.org/0000-0002-3950-2169"},"institutions":[{"id":"https://openalex.org/I3130401523","display_name":"Universidad Yachay Tech","ror":"https://ror.org/04jjswc10","country_code":"EC","type":"education","lineage":["https://openalex.org/I3130401523"]}],"countries":["EC"],"is_corresponding":false,"raw_author_name":"Israel Pineda","raw_affiliation_strings":["Yachay Tech University, Hacienda San José y Proyecto Yachay,Urcuquí,Ecuador,100115"],"affiliations":[{"raw_affiliation_string":"Yachay Tech University, Hacienda San José y Proyecto Yachay,Urcuquí,Ecuador,100115","institution_ids":["https://openalex.org/I3130401523"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020556068","display_name":"E. J. Piispa","orcid":"https://orcid.org/0000-0002-5054-0457"},"institutions":[{"id":"https://openalex.org/I165368041","display_name":"University of Iceland","ror":"https://ror.org/01db6h964","country_code":"IS","type":"education","lineage":["https://openalex.org/I165368041"]}],"countries":["IS"],"is_corresponding":false,"raw_author_name":"Elisa J. Piispa","raw_affiliation_strings":["University of Iceland,Reykjavík,Iceland"],"affiliations":[{"raw_affiliation_string":"University of Iceland,Reykjavík,Iceland","institution_ids":["https://openalex.org/I165368041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056413922","display_name":"Scott L. Williams","orcid":null},"institutions":[{"id":"https://openalex.org/I10052268","display_name":"New Mexico State University","ror":"https://ror.org/00hpz7z43","country_code":"US","type":"education","lineage":["https://openalex.org/I10052268"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Scott L. Williams","raw_affiliation_strings":["New Mexico State University,Las Cruces,New Mexico,USA - retired","New Mexico State University, Las Cruces, New Mexico, USA - retired"],"affiliations":[{"raw_affiliation_string":"New Mexico State University,Las Cruces,New Mexico,USA - retired","institution_ids":["https://openalex.org/I10052268"]},{"raw_affiliation_string":"New Mexico State University, Las Cruces, New Mexico, USA - retired","institution_ids":["https://openalex.org/I10052268"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5053518376"],"corresponding_institution_ids":["https://openalex.org/I3130401523"],"apc_list":null,"apc_paid":null,"fwci":1.3941,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.80651341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3195","last_page":"3198"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10266","display_name":"Plant Water Relations and Carbon Dynamics","score":0.9998999834060669,"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/T10266","display_name":"Plant Water Relations and Carbon Dynamics","score":0.9998999834060669,"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/T10330","display_name":"Hydrology and Watershed Management Studies","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"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/T10466","display_name":"Meteorological Phenomena and Simulations","score":0.9944999814033508,"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/weather-research-and-forecasting-model","display_name":"Weather Research and Forecasting Model","score":0.8953697681427002},{"id":"https://openalex.org/keywords/evapotranspiration","display_name":"Evapotranspiration","score":0.6570522785186768},{"id":"https://openalex.org/keywords/noon","display_name":"Noon","score":0.5184963941574097},{"id":"https://openalex.org/keywords/weather-forecasting","display_name":"Weather forecasting","score":0.5037423968315125},{"id":"https://openalex.org/keywords/amazon-rainforest","display_name":"Amazon rainforest","score":0.5000064373016357},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.498354434967041},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4775432050228119},{"id":"https://openalex.org/keywords/self-organizing-map","display_name":"Self-organizing map","score":0.45784395933151245},{"id":"https://openalex.org/keywords/raw-data","display_name":"Raw data","score":0.4491710662841797},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4166721701622009},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3839491605758667},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3707171678543091},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3400908410549164},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3246198296546936},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.23150664567947388},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10581836104393005},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.09100830554962158}],"concepts":[{"id":"https://openalex.org/C133204551","wikidata":"https://www.wikidata.org/wiki/Q838305","display_name":"Weather Research and Forecasting Model","level":2,"score":0.8953697681427002},{"id":"https://openalex.org/C176783924","wikidata":"https://www.wikidata.org/wiki/Q828158","display_name":"Evapotranspiration","level":2,"score":0.6570522785186768},{"id":"https://openalex.org/C58650310","wikidata":"https://www.wikidata.org/wiki/Q168182","display_name":"Noon","level":2,"score":0.5184963941574097},{"id":"https://openalex.org/C21001229","wikidata":"https://www.wikidata.org/wiki/Q182868","display_name":"Weather forecasting","level":2,"score":0.5037423968315125},{"id":"https://openalex.org/C535291247","wikidata":"https://www.wikidata.org/wiki/Q177567","display_name":"Amazon rainforest","level":2,"score":0.5000064373016357},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.498354434967041},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4775432050228119},{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.45784395933151245},{"id":"https://openalex.org/C132964779","wikidata":"https://www.wikidata.org/wiki/Q2110223","display_name":"Raw data","level":2,"score":0.4491710662841797},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4166721701622009},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3839491605758667},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3707171678543091},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3400908410549164},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3246198296546936},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.23150664567947388},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10581836104393005},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.09100830554962158},{"id":"https://openalex.org/C91586092","wikidata":"https://www.wikidata.org/wiki/Q757520","display_name":"Atmospheric sciences","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss46834.2022.9883703","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss46834.2022.9883703","pdf_url":null,"source":{"id":"https://openalex.org/S4363604196","display_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","score":0.7699999809265137,"display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W260519431","https://openalex.org/W1580822624","https://openalex.org/W1888992623","https://openalex.org/W1969336359","https://openalex.org/W1975768883","https://openalex.org/W2003123646","https://openalex.org/W2016237711","https://openalex.org/W2033942510","https://openalex.org/W2057255563","https://openalex.org/W2063851248","https://openalex.org/W2064184542","https://openalex.org/W2093901628","https://openalex.org/W2106239356","https://openalex.org/W2115736287","https://openalex.org/W2167453193","https://openalex.org/W2242464395","https://openalex.org/W2569758175","https://openalex.org/W2899363336","https://openalex.org/W2951772479"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W3082873205","https://openalex.org/W2928925641","https://openalex.org/W1972452083","https://openalex.org/W216433883","https://openalex.org/W2886566961","https://openalex.org/W4293203914","https://openalex.org/W2360003197","https://openalex.org/W2996371099"],"abstract_inverted_index":{"Remotely":[0],"sensed":[1],"data":[2,26,70],"and":[3,31,80,94,98,117],"Artificial":[4],"Intelligence":[5],"provide":[6,53],"an":[7],"avenue":[8],"to":[9,38,52],"Standard":[10],"Evaporation":[11],"(ETo)":[12],"classification.":[13],"Hence,":[14],"we":[15],"developed":[16],"a":[17,49,54,64,83,128,137],"methodology":[18],"for":[19,78,90],"classifying":[20],"ETo":[21,58,131],"using":[22],"Self-Organizing":[23],"Maps":[24],"on":[25],"from":[27,36,71],"the":[28,115,124],"Weather":[29],"Research":[30],"Forecasting":[32],"(WRF)":[33],"model":[34],"obtained":[35],"March":[37],"October,":[39],"2020,":[40],"at":[41,75,146],"3":[42],"km":[43],"resolution":[44],"over":[45,142],"Ecuador.":[46],"This":[47],"is":[48],"preliminary":[50],"effort":[51],"visual":[55],"comparison":[56],"of":[57,101,106,140],"classified":[59,102],"maps":[60],"under":[61],"different":[62,99],"scenarios:":[63],"\u2018shallow\u2019":[65],"learning":[66,85,126],"that":[67,86],"takes":[68],"only":[69],"one":[72,79],"time":[73],"slice":[74],"12:00":[76],"noon":[77],"three":[81,91],"months;":[82,92],"\u2018deeper\u2019":[84,125],"considers":[87],"hourly":[88],"slices":[89],"raw":[93],"pre-processed":[95],"WRF":[96],"variables;":[97],"numbers":[100],"classes.":[103],"The":[104],"results":[105],"these":[107],"exercises":[108],"show":[109],"overall":[110],"stable":[111,130],"mountainous":[112],"classification,":[113],"while":[114],"Amazonia":[116],"Western":[118],"regions":[119,135],"appear":[120],"more":[121,129],"volatile.":[122],"Moreover,":[123],"produces":[127],"classification":[132],"in":[133],"all":[134],"with":[136],"decreased":[138],"migration":[139],"classes":[141],"time,":[143],"as":[144],"presented":[145],"http://www.yachay.openfabtech.org/somETo/description.php":[147]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}