{"id":"https://openalex.org/W4408258247","doi":"https://doi.org/10.1109/tencon61640.2024.10903042","title":"Evaluating Classifier Performance in Mapping Paddy Rice Fields Using Multi-Temporal SAR Data on Google Earth Engine","display_name":"Evaluating Classifier Performance in Mapping Paddy Rice Fields Using Multi-Temporal SAR Data on Google Earth Engine","publication_year":2024,"publication_date":"2024-12-01","ids":{"openalex":"https://openalex.org/W4408258247","doi":"https://doi.org/10.1109/tencon61640.2024.10903042"},"language":"en","primary_location":{"id":"doi:10.1109/tencon61640.2024.10903042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon61640.2024.10903042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON)","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/A5033046273","display_name":"Robert Martin Santiago","orcid":null},"institutions":[{"id":"https://openalex.org/I5996616","display_name":"De La Salle University","ror":"https://ror.org/04xftk194","country_code":"PH","type":"education","lineage":["https://openalex.org/I5996616"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Robert Martin Santiago","raw_affiliation_strings":["De La Salle University,Dept. of Electronics &#x0026; Computer Eng&#x2019;g,Manila,Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"De La Salle University,Dept. of Electronics &#x0026; Computer Eng&#x2019;g,Manila,Philippines","institution_ids":["https://openalex.org/I5996616"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011950148","display_name":"Eduardo Jimmy Quilang","orcid":null},"institutions":[{"id":"https://openalex.org/I166305524","display_name":"Philippine Rice Research Institute","ror":"https://ror.org/02gazz415","country_code":"PH","type":"government","lineage":["https://openalex.org/I166305524"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Eduardo Jimmy Quilang","raw_affiliation_strings":["Philippine Rice Information System, Philippine Rice Research Institute Science,City of Mu&#x00F1;oz,Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Philippine Rice Information System, Philippine Rice Research Institute Science,City of Mu&#x00F1;oz,Philippines","institution_ids":["https://openalex.org/I166305524"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007121660","display_name":"Edwin Sybingco","orcid":"https://orcid.org/0000-0003-1296-3616"},"institutions":[{"id":"https://openalex.org/I5996616","display_name":"De La Salle University","ror":"https://ror.org/04xftk194","country_code":"PH","type":"education","lineage":["https://openalex.org/I5996616"]}],"countries":["PH"],"is_corresponding":false,"raw_author_name":"Edwin Sybingco","raw_affiliation_strings":["De La Salle University,Dept. of Electronics &#x0026; Computer Eng&#x2019;g,Manila,Philippines"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"De La Salle University,Dept. of Electronics &#x0026; Computer Eng&#x2019;g,Manila,Philippines","institution_ids":["https://openalex.org/I5996616"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5209,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.79271358,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1227","last_page":"1230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12045","display_name":"Rice Cultivation and Yield Improvement","score":0.9506000280380249,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12045","display_name":"Rice Cultivation and Yield Improvement","score":0.9506000280380249,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":0.9337999820709229,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T10616","display_name":"Smart Agriculture and AI","score":0.9296000003814697,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6896618604660034},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6716996431350708},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5101032853126526},{"id":"https://openalex.org/keywords/earth-observation","display_name":"Earth observation","score":0.4948558211326599},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4158289134502411},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35746830701828003},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.16556909680366516},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10730543732643127}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6896618604660034},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6716996431350708},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5101032853126526},{"id":"https://openalex.org/C39399123","wikidata":"https://www.wikidata.org/wiki/Q1348989","display_name":"Earth observation","level":3,"score":0.4948558211326599},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4158289134502411},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35746830701828003},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.16556909680366516},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10730543732643127},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tencon61640.2024.10903042","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tencon61640.2024.10903042","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TENCON 2024 - 2024 IEEE Region 10 Conference (TENCON)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.5799999833106995,"display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2725897987","https://openalex.org/W2909241094","https://openalex.org/W2914315876","https://openalex.org/W2979729205","https://openalex.org/W2980530181","https://openalex.org/W2983090166","https://openalex.org/W2986339177","https://openalex.org/W2989237842","https://openalex.org/W3004142839","https://openalex.org/W3016213868","https://openalex.org/W3028248982","https://openalex.org/W3028441658","https://openalex.org/W3039696540","https://openalex.org/W3073623721","https://openalex.org/W3089681013","https://openalex.org/W3114226933","https://openalex.org/W3119089275","https://openalex.org/W3121078207","https://openalex.org/W3125359252","https://openalex.org/W3131081724","https://openalex.org/W3132493672","https://openalex.org/W3132790173","https://openalex.org/W3135196696","https://openalex.org/W3137356499","https://openalex.org/W3155326714","https://openalex.org/W3158568413","https://openalex.org/W3162003722","https://openalex.org/W3197307708","https://openalex.org/W3198115293","https://openalex.org/W3198186793","https://openalex.org/W3198696756","https://openalex.org/W3199089714","https://openalex.org/W3203247629","https://openalex.org/W3205982288","https://openalex.org/W3206745924","https://openalex.org/W4206581955","https://openalex.org/W4224250287","https://openalex.org/W4225506592","https://openalex.org/W4290052862","https://openalex.org/W4296006148"],"related_works":["https://openalex.org/W2033914206","https://openalex.org/W2042327336","https://openalex.org/W2357875252","https://openalex.org/W126533163","https://openalex.org/W2507965015","https://openalex.org/W4380629442","https://openalex.org/W1994815372","https://openalex.org/W2249146193","https://openalex.org/W3020946232","https://openalex.org/W3039495454"],"abstract_inverted_index":{"Mapping":[0],"paddy":[1,142,167,177],"rice":[2,8,168,178],"fields":[3],"is":[4,11],"crucial":[5],"for":[6,13],"monitoring":[7],"production,":[9],"which":[10,124],"vital":[12],"food":[14],"security":[15],"and":[16,60,74,79,104],"economic":[17],"stability.":[18],"Prior":[19],"studies":[20],"have":[21],"utilized":[22],"remote":[23],"sensing":[24],"data":[25,134],"along":[26],"with":[27,98,127],"various":[28],"machine":[29],"learning":[30],"algorithms":[31],"to":[32,116,119,136,171],"accomplish":[33],"this":[34,51],"task.":[35],"However,":[36],"the":[37,82,91,96,128,131,138,148,152,162,173],"performance":[38,112],"of":[39,102,108,130,141,147,154,166,175],"these":[40],"classifiers":[41,150],"under":[42],"different":[43],"conditions":[44],"remains":[45],"an":[46,99,156],"area":[47],"worth":[48],"investigating.":[49],"In":[50],"study,":[52],"rice-growing":[53],"areas":[54],"are":[55],"delineated":[56],"from":[57],"other":[58],"crops":[59],"land":[61],"cover":[62],"types":[63],"using":[64],"multi-temporal":[65,132],"synthetic":[66],"aperture":[67],"radar":[68,164],"(SAR)":[69],"imageries":[70],"recorded":[71],"by":[72],"Sentinel-1":[73],"classification":[75],"algorithms\u2014Na\u00efve":[76],"Bayes,":[77],"CART,":[78],"Random":[80],"Forest\u2014on":[81],"Google":[83],"Earth":[84],"Engine":[85],"(GEE)":[86],"platform.":[87],"Results":[88],"show":[89],"that":[90],"random":[92],"forest":[93],"classifier":[94],"outperforms":[95],"others":[97],"overall":[100],"accuracy":[101,174],"85.90%":[103],"a":[105],"kappa":[106],"coefficient":[107],"0.7180.":[109],"This":[110],"superior":[111],"can":[113],"be":[114],"attributed":[115],"its":[117],"capability":[118],"handle":[120],"complex,":[121],"high-dimensional":[122],"data,":[123],"aligns":[125],"well":[126],"properties":[129],"SAR":[133],"used":[135],"observe":[137],"growth":[139],"cycle":[140],"rice.":[143],"The":[144],"differing":[145],"performances":[146],"three":[149],"underscored":[151],"importance":[153],"selecting":[155],"appropriate":[157],"algorithm,":[158],"especially":[159],"when":[160],"leveraging":[161],"distinctive":[163],"signatures":[165],"over":[169],"time,":[170],"enhance":[172],"mapping":[176],"fields.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
