{"id":"https://openalex.org/W2884294411","doi":"https://doi.org/10.1080/17538947.2018.1499827","title":"Using a simulation analysis to evaluate the impact of crop mapping error on crop area estimation from stratified sampling","display_name":"Using a simulation analysis to evaluate the impact of crop mapping error on crop area estimation from stratified sampling","publication_year":2018,"publication_date":"2018-07-19","ids":{"openalex":"https://openalex.org/W2884294411","doi":"https://doi.org/10.1080/17538947.2018.1499827","mag":"2884294411"},"language":"en","primary_location":{"id":"doi:10.1080/17538947.2018.1499827","is_oa":false,"landing_page_url":"https://doi.org/10.1080/17538947.2018.1499827","pdf_url":null,"source":{"id":"https://openalex.org/S199162493","display_name":"International Journal of Digital Earth","issn_l":"1753-8947","issn":["1753-8947","1753-8955"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Digital Earth","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doaj.org/article/bd991cf9120c4814840da6fe11340da0","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5077434208","display_name":"Peijun Sun","orcid":"https://orcid.org/0000-0002-7380-2384"},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I161057412","display_name":"University of New Hampshire","ror":"https://ror.org/01rmh9n78","country_code":"US","type":"education","lineage":["https://openalex.org/I161057412"]},{"id":"https://openalex.org/I4210135981","display_name":"Louisiana Department of Natural Resources","ror":"https://ror.org/03n7hja66","country_code":"US","type":"government","lineage":["https://openalex.org/I4210135981"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Peijun Sun","raw_affiliation_strings":["Department of Natural Resources & the Environment, University of New Hampshire, Durham, NH, USA","Institute of Remote Sensing and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing, People\u2019s Republic of China","State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing, People\u2019s Republic of China"],"affiliations":[{"raw_affiliation_string":"Department of Natural Resources & the Environment, University of New Hampshire, Durham, NH, USA","institution_ids":["https://openalex.org/I161057412","https://openalex.org/I4210135981"]},{"raw_affiliation_string":"Institute of Remote Sensing and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing, People\u2019s Republic of China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing, People\u2019s Republic of China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941","https://openalex.org/I4210128053","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022247838","display_name":"Russell G. Congalton","orcid":"https://orcid.org/0000-0003-3891-2163"},"institutions":[{"id":"https://openalex.org/I4210135981","display_name":"Louisiana Department of Natural Resources","ror":"https://ror.org/03n7hja66","country_code":"US","type":"government","lineage":["https://openalex.org/I4210135981"]},{"id":"https://openalex.org/I161057412","display_name":"University of New Hampshire","ror":"https://ror.org/01rmh9n78","country_code":"US","type":"education","lineage":["https://openalex.org/I161057412"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Russell G. Congalton","raw_affiliation_strings":["Department of Natural Resources & the Environment, University of New Hampshire, Durham, NH, USA"],"affiliations":[{"raw_affiliation_string":"Department of Natural Resources & the Environment, University of New Hampshire, Durham, NH, USA","institution_ids":["https://openalex.org/I161057412","https://openalex.org/I4210135981"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078753250","display_name":"Yaozhong Pan","orcid":"https://orcid.org/0000-0002-2307-2715"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaozhong Pan","raw_affiliation_strings":["Institute of Remote Sensing and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing, People\u2019s Republic of China","State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing, People\u2019s Republic of China"],"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing, People\u2019s Republic of China","institution_ids":["https://openalex.org/I25254941"]},{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing, People\u2019s Republic of China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I25254941","https://openalex.org/I4210128053","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077434208","https://openalex.org/A5078753250"],"corresponding_institution_ids":["https://openalex.org/I161057412","https://openalex.org/I19820366","https://openalex.org/I25254941","https://openalex.org/I4210128053","https://openalex.org/I4210135981","https://openalex.org/I4210166112"],"apc_list":{"value":2390,"currency":"USD","value_usd":2390},"apc_paid":null,"fwci":0.5821,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.71321969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"12","issue":"9","first_page":"1046","last_page":"1066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9973000288009644,"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":0.9973000288009644,"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/T10770","display_name":"Soil Geostatistics and Mapping","score":0.9933000206947327,"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"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9779999852180481,"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/estimation","display_name":"Estimation","score":0.7073484063148499},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6848608255386353},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.638008177280426},{"id":"https://openalex.org/keywords/small-area-estimation","display_name":"Small area estimation","score":0.6349390745162964},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5951720476150513},{"id":"https://openalex.org/keywords/thematic-map","display_name":"Thematic map","score":0.5867420434951782},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5741536617279053},{"id":"https://openalex.org/keywords/stratified-sampling","display_name":"Stratified sampling","score":0.5565261840820312},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.4773864150047302},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.40817010402679443},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3375388979911804},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.31836986541748047},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1884687840938568},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1473211944103241},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.07819882035255432},{"id":"https://openalex.org/keywords/ecology","display_name":"Ecology","score":0.07692873477935791}],"concepts":[{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.7073484063148499},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6848608255386353},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.638008177280426},{"id":"https://openalex.org/C129963666","wikidata":"https://www.wikidata.org/wiki/Q17105857","display_name":"Small area estimation","level":3,"score":0.6349390745162964},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5951720476150513},{"id":"https://openalex.org/C93692415","wikidata":"https://www.wikidata.org/wiki/Q1502030","display_name":"Thematic map","level":2,"score":0.5867420434951782},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5741536617279053},{"id":"https://openalex.org/C49898467","wikidata":"https://www.wikidata.org/wiki/Q1517706","display_name":"Stratified sampling","level":2,"score":0.5565261840820312},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.4773864150047302},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.40817010402679443},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3375388979911804},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.31836986541748047},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1884687840938568},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1473211944103241},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.07819882035255432},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.07692873477935791},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1080/17538947.2018.1499827","is_oa":false,"landing_page_url":"https://doi.org/10.1080/17538947.2018.1499827","pdf_url":null,"source":{"id":"https://openalex.org/S199162493","display_name":"International Journal of Digital Earth","issn_l":"1753-8947","issn":["1753-8947","1753-8955"],"is_oa":false,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Digital Earth","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:bd991cf9120c4814840da6fe11340da0","is_oa":true,"landing_page_url":"https://doaj.org/article/bd991cf9120c4814840da6fe11340da0","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Digital Earth, Vol 12, Iss 9, Pp 1046-1066 (2019)","raw_type":"article"},{"id":"pmh:oai:scholars.unh.edu:faculty_pubs-2300","is_oa":false,"landing_page_url":"https://www.tandfonline.com/doi/full/10.1080/17538947.2018.1499827","pdf_url":null,"source":{"id":"https://openalex.org/S4377196362","display_name":"University of New Hampshire Scholars Repository (University of New Hampshire at Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I179093154","host_organization_name":"University of New Hampshire at Manchester","host_organization_lineage":["https://openalex.org/I179093154"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Faculty Publications","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:doaj.org/article:bd991cf9120c4814840da6fe11340da0","is_oa":true,"landing_page_url":"https://doaj.org/article/bd991cf9120c4814840da6fe11340da0","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Digital Earth, Vol 12, Iss 9, Pp 1046-1066 (2019)","raw_type":"article"},"sustainable_development_goals":[{"display_name":"Zero hunger","score":0.5199999809265137,"id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320307552","display_name":"Cornelia de Lange Syndrome Foundation","ror":"https://ror.org/05avjmd23"},{"id":"https://openalex.org/F4320332785","display_name":"National Agricultural Statistics Service","ror":"https://ror.org/04dpymk59"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":60,"referenced_works":["https://openalex.org/W181107242","https://openalex.org/W309671427","https://openalex.org/W325842402","https://openalex.org/W787719558","https://openalex.org/W1098496330","https://openalex.org/W1543713962","https://openalex.org/W1597114888","https://openalex.org/W1984011424","https://openalex.org/W1991861340","https://openalex.org/W1998046114","https://openalex.org/W1998269430","https://openalex.org/W2000179198","https://openalex.org/W2001267978","https://openalex.org/W2004611847","https://openalex.org/W2008085934","https://openalex.org/W2011868515","https://openalex.org/W2013360540","https://openalex.org/W2026879105","https://openalex.org/W2031561163","https://openalex.org/W2034183584","https://openalex.org/W2035222601","https://openalex.org/W2037146323","https://openalex.org/W2040667072","https://openalex.org/W2040998916","https://openalex.org/W2045685519","https://openalex.org/W2057479110","https://openalex.org/W2058723831","https://openalex.org/W2087670708","https://openalex.org/W2088133484","https://openalex.org/W2090482185","https://openalex.org/W2093902012","https://openalex.org/W2099456005","https://openalex.org/W2102388577","https://openalex.org/W2103212156","https://openalex.org/W2104088267","https://openalex.org/W2104346840","https://openalex.org/W2111512695","https://openalex.org/W2114009539","https://openalex.org/W2133941557","https://openalex.org/W2137977421","https://openalex.org/W2167619573","https://openalex.org/W2282484194","https://openalex.org/W2324992469","https://openalex.org/W2326996716","https://openalex.org/W2365381953","https://openalex.org/W2513566916","https://openalex.org/W2548388936","https://openalex.org/W2552805558","https://openalex.org/W2556159429","https://openalex.org/W2561235410","https://openalex.org/W2561750000","https://openalex.org/W2562161991","https://openalex.org/W2578830027","https://openalex.org/W2584444164","https://openalex.org/W2588205580","https://openalex.org/W2751983466","https://openalex.org/W2753474338","https://openalex.org/W2955312500","https://openalex.org/W4210628276","https://openalex.org/W4299827484"],"related_works":["https://openalex.org/W3002907611","https://openalex.org/W1562146597","https://openalex.org/W2291311298","https://openalex.org/W2378021067","https://openalex.org/W2500514401","https://openalex.org/W2347703439","https://openalex.org/W138756022","https://openalex.org/W2365305234","https://openalex.org/W2154622657","https://openalex.org/W2132503437"],"abstract_inverted_index":{"To":[0],"analyze":[1],"the":[2,38,44,47,51,55,66,72,85,88,95,99,149,152,182],"efficiency":[3,40,104],"of":[4,12,46,87,97,151,181,184],"area":[5],"estimations":[6],"(i.e.":[7,75],"estimation":[8,32,39,77,103,119,172],"accuracy":[9],"and":[10,50,60,125,174],"variation":[11],"estimation)":[13],"impacted":[14],"by":[15,43],"crop":[16,67,89,185,200],"mapping":[17,68,186],"error,":[18],"we":[19],"simulated":[20],"error":[21,52,61,69,100,127,187],"at":[22],"eight":[23],"levels":[24],"for":[25,158,190],"thematic":[26],"maps":[27,142],"using":[28],"a":[29,121],"stratified":[30],"sampling":[31,80,175],"methodology.":[33],"The":[34,91,154],"results":[35,92],"show":[36],"that":[37,64,94,139],"is":[41,105,188],"influenced":[42],"combination":[45],"sample":[48,58,123,156],"size":[49,59,124,157],"level.":[53],"Evaluating":[54],"trade-offs":[56],"between":[57],"level":[62,70,101,128],"showed":[63],"reducing":[65],"provides":[71],"most":[73],"benefit":[74],"higher":[76,118],"efficiency).":[78],"Further,":[79],"performance":[81],"differed":[82],"based":[83],"on":[84,102],"heterogeneity":[86,150],"area.":[90,153,201],"demonstrated":[93],"influence":[96],"increasing":[98],"more":[106],"detrimental":[107],"in":[108,112,134],"heterogeneous":[109,135],"areas":[110,160],"than":[111],"homogeneous":[113],"ones.":[114],"Therefore,":[115],"to":[116,147,166,193,197],"obtain":[117],"efficiency,":[120,173],"larger":[122],"lower":[126],"or":[129],"both":[130],"are":[131],"needed,":[132],"especially":[133],"areas.":[136],"We":[137],"suggest":[138],"existing":[140],"land-cover":[141],"should":[143],"first":[144],"be":[145,163],"used":[146],"determine":[148],"appropriate":[155],"these":[159],"then":[161],"can":[162],"determined":[164],"according":[165],"all":[167],"three":[168],"factors:":[169],"heterogeneity,":[170],"expected":[171],"budget.":[176],"Overall,":[177],"extending":[178],"our":[179,195],"understanding":[180],"impacts":[183],"necessary":[189],"decision":[191],"making":[192],"improve":[194],"ability":[196],"effectively":[198],"estimate":[199]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}