{"id":"https://openalex.org/W2777003700","doi":"https://doi.org/10.3390/rs10010031","title":"Comparison of Different Machine Learning Approaches for Monthly Satellite-Based Soil Moisture Downscaling over Northeast China","display_name":"Comparison of Different Machine Learning Approaches for Monthly Satellite-Based Soil Moisture Downscaling over Northeast China","publication_year":2017,"publication_date":"2017-12-25","ids":{"openalex":"https://openalex.org/W2777003700","doi":"https://doi.org/10.3390/rs10010031","mag":"2777003700"},"language":"en","primary_location":{"id":"doi:10.3390/rs10010031","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10010031","pdf_url":"https://www.mdpi.com/2072-4292/10/1/31/pdf?version=1514204044","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/10/1/31/pdf?version=1514204044","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042672435","display_name":"Yangxiaoyue Liu","orcid":"https://orcid.org/0000-0003-3762-117X"},"institutions":[{"id":"https://openalex.org/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]},{"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/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangxiaoyue Liu","raw_affiliation_strings":["State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China","University of Chinese Academy of Sciences, Beijing 100049, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210160793","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112545101","display_name":"Yaping Yang","orcid":null},"institutions":[{"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/I4210141657","display_name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application","ror":"https://ror.org/045yewh40","country_code":"CN","type":"facility","lineage":["https://openalex.org/I152031979","https://openalex.org/I4210141657"]},{"id":"https://openalex.org/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaping Yang","raw_affiliation_strings":["Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China","State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China","institution_ids":["https://openalex.org/I4210141657"]},{"raw_affiliation_string":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210160793","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063344744","display_name":"Wenlong Jing","orcid":"https://orcid.org/0000-0001-8021-3943"},"institutions":[{"id":"https://openalex.org/I4210147158","display_name":"Guangzhou Institute of Geography","ror":"https://ror.org/03tbxt129","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210147158"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenlong Jing","raw_affiliation_strings":["Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou 510070, China","Guangzhou Institute of Geography, Guangzhou 510070, China","Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou 510070, China","institution_ids":[]},{"raw_affiliation_string":"Guangzhou Institute of Geography, Guangzhou 510070, China","institution_ids":["https://openalex.org/I4210147158"]},{"raw_affiliation_string":"Key Laboratory of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046677224","display_name":"Xiafang Yue","orcid":null},"institutions":[{"id":"https://openalex.org/I4210141657","display_name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application","ror":"https://ror.org/045yewh40","country_code":"CN","type":"facility","lineage":["https://openalex.org/I152031979","https://openalex.org/I4210141657"]},{"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/I4210160793","display_name":"Institute of Geographic Sciences and Natural Resources Research","ror":"https://ror.org/04t1cdb72","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210160793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiafang Yue","raw_affiliation_strings":["Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China","State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"],"affiliations":[{"raw_affiliation_string":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China","institution_ids":["https://openalex.org/I4210141657"]},{"raw_affiliation_string":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China","institution_ids":["https://openalex.org/I4210160793","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5112545101"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210141657","https://openalex.org/I4210160793"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":3.1411,"has_fulltext":false,"cited_by_count":94,"citation_normalized_percentile":{"value":0.91423214,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"10","issue":"1","first_page":"31","last_page":"31"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":1.0,"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/T11333","display_name":"Climate change and permafrost","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10644","display_name":"Cryospheric studies and observations","score":0.9958999752998352,"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/downscaling","display_name":"Downscaling","score":0.7359226942062378},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.6648149490356445},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.6404882669448853},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.4658988416194916},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.4544315040111542},{"id":"https://openalex.org/keywords/climatology","display_name":"Climatology","score":0.42526814341545105},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.39909854531288147},{"id":"https://openalex.org/keywords/precipitation","display_name":"Precipitation","score":0.3644196391105652},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.3137609660625458},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3066134452819824},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.302557110786438},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18439733982086182},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1839858889579773},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.14006423950195312},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13904526829719543}],"concepts":[{"id":"https://openalex.org/C41156917","wikidata":"https://www.wikidata.org/wiki/Q682831","display_name":"Downscaling","level":3,"score":0.7359226942062378},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.6648149490356445},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6404882669448853},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.4658988416194916},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.4544315040111542},{"id":"https://openalex.org/C49204034","wikidata":"https://www.wikidata.org/wiki/Q52139","display_name":"Climatology","level":1,"score":0.42526814341545105},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.39909854531288147},{"id":"https://openalex.org/C107054158","wikidata":"https://www.wikidata.org/wiki/Q25257","display_name":"Precipitation","level":2,"score":0.3644196391105652},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.3137609660625458},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3066134452819824},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.302557110786438},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18439733982086182},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1839858889579773},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.14006423950195312},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13904526829719543},{"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/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs10010031","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10010031","pdf_url":"https://www.mdpi.com/2072-4292/10/1/31/pdf?version=1514204044","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:04b728e8e47747c98b7a0df43d30919c","is_oa":true,"landing_page_url":"https://doaj.org/article/04b728e8e47747c98b7a0df43d30919c","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 10, Iss 1, p 31 (2017)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/10/1/31/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs10010031","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing; Volume 10; Issue 1; Pages: 31","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs10010031","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs10010031","pdf_url":"https://www.mdpi.com/2072-4292/10/1/31/pdf?version=1514204044","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.5}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2777003700.pdf","grobid_xml":"https://content.openalex.org/works/W2777003700.grobid-xml"},"referenced_works_count":82,"referenced_works":["https://openalex.org/W30651129","https://openalex.org/W273955616","https://openalex.org/W1588622902","https://openalex.org/W1786856418","https://openalex.org/W1926971900","https://openalex.org/W1963516471","https://openalex.org/W1964217023","https://openalex.org/W1965524806","https://openalex.org/W1975288608","https://openalex.org/W1977473269","https://openalex.org/W1978835122","https://openalex.org/W1982118872","https://openalex.org/W1988195734","https://openalex.org/W1989736185","https://openalex.org/W1990590197","https://openalex.org/W1991626956","https://openalex.org/W1996746229","https://openalex.org/W2001351094","https://openalex.org/W2002116577","https://openalex.org/W2002646960","https://openalex.org/W2003567919","https://openalex.org/W2005130804","https://openalex.org/W2015155441","https://openalex.org/W2020004539","https://openalex.org/W2020799038","https://openalex.org/W2024689500","https://openalex.org/W2024759588","https://openalex.org/W2024903254","https://openalex.org/W2025515353","https://openalex.org/W2027554150","https://openalex.org/W2028979033","https://openalex.org/W2030103530","https://openalex.org/W2031292142","https://openalex.org/W2039348932","https://openalex.org/W2040678502","https://openalex.org/W2045176421","https://openalex.org/W2048086440","https://openalex.org/W2051378084","https://openalex.org/W2053669534","https://openalex.org/W2055976274","https://openalex.org/W2056218351","https://openalex.org/W2058232479","https://openalex.org/W2059266940","https://openalex.org/W2067967609","https://openalex.org/W2068371905","https://openalex.org/W2069414124","https://openalex.org/W2094351185","https://openalex.org/W2097498299","https://openalex.org/W2101234009","https://openalex.org/W2103421500","https://openalex.org/W2110835349","https://openalex.org/W2119513445","https://openalex.org/W2123281900","https://openalex.org/W2123744475","https://openalex.org/W2132549823","https://openalex.org/W2139582652","https://openalex.org/W2146104749","https://openalex.org/W2147241431","https://openalex.org/W2148557261","https://openalex.org/W2151591509","https://openalex.org/W2151593676","https://openalex.org/W2154272608","https://openalex.org/W2155632266","https://openalex.org/W2161071907","https://openalex.org/W2286406264","https://openalex.org/W2362351596","https://openalex.org/W2443939784","https://openalex.org/W2529998007","https://openalex.org/W2550894800","https://openalex.org/W2615057855","https://openalex.org/W2911964244","https://openalex.org/W3101477643","https://openalex.org/W3214323364","https://openalex.org/W4233341945","https://openalex.org/W6610017368","https://openalex.org/W6633912359","https://openalex.org/W6634857426","https://openalex.org/W6651749711","https://openalex.org/W6654407675","https://openalex.org/W6675354045","https://openalex.org/W6696365603","https://openalex.org/W6804231292"],"related_works":["https://openalex.org/W2394436593","https://openalex.org/W3013458534","https://openalex.org/W3010558748","https://openalex.org/W2526815458","https://openalex.org/W4220911053","https://openalex.org/W2048488252","https://openalex.org/W2940614149","https://openalex.org/W4288365262","https://openalex.org/W2787485953","https://openalex.org/W3217432596"],"abstract_inverted_index":{"Although":[0],"numerous":[1],"satellite-based":[2],"soil":[3],"moisture":[4],"(SM)":[5],"products":[6],"can":[7,14,187],"provide":[8],"spatiotemporally":[9],"continuous":[10],"worldwide":[11],"datasets,":[12],"they":[13],"hardly":[15],"be":[16],"employed":[17],"in":[18,155],"characterizing":[19],"fine-grained":[20],"regional":[21],"land":[22,96],"surface":[23,97,112],"processes,":[24],"owing":[25],"to":[26,39,72,88,132,153,178,190,212],"their":[27],"coarse":[28],"spatial":[29,42,90,135],"resolution.":[30,91],"In":[31],"this":[32],"study,":[33],"we":[34],"proposed":[35],"a":[36,216],"machine-learning-based":[37],"method":[38],"enhance":[40],"SM":[41,49,84,149,160,182],"accuracy":[43],"and":[44,57,66,104,120,123,146,183,186,207],"improve":[45],"the":[46,74,93,95,143,171,194,221],"availability":[47],"of":[48],"data.":[50],"Four":[51],"machine":[52],"learning":[53],"algorithms,":[54],"including":[55],"classification":[56],"regression":[58,236],"trees":[59],"(CART),":[60],"K-nearest":[61],"neighbors":[62],"(KNN),":[63],"Bayesian":[64],"(BAYE),":[65],"random":[67],"forests":[68],"(RF),":[69],"were":[70,127,162],"implemented":[71],"downscale":[73],"monthly":[75],"European":[76],"Space":[77],"Agency":[78],"Climate":[79],"Change":[80],"Initiative":[81],"(ESA":[82],"CCI)":[83],"product":[85],"from":[86,151],"25-km":[87],"1-km":[89],"During":[92],"regression,":[94],"temperature":[98],"(including":[99],"daytime":[100],"temperature,":[101,103],"nighttime":[102],"diurnal":[105],"fluctuation":[106],"temperature),":[107],"normalized":[108],"difference":[109],"vegetation":[110],"index,":[111],"reflections":[113],"(red":[114],"band,":[115,117],"blue":[116],"NIR":[118],"band":[119],"MIR":[121],"band),":[122],"digital":[124],"elevation":[125],"model":[126],"taken":[128],"as":[129,142],"explanatory":[130],"variables":[131],"produce":[133],"fine":[134],"resolution":[136],"SM.":[137],"We":[138],"chose":[139],"Northeast":[140],"China":[141],"study":[144],"area":[145],"acquired":[147],"corresponding":[148],"data":[150],"2003":[152],"2012":[154],"unfrozen":[156],"seasons.":[157],"The":[158,167],"reconstructed":[159],"datasets":[161],"validated":[163],"against":[164],"in-situ":[165,184],"measurements.":[166],"results":[168,173],"showed":[169,226],"that":[170],"RF-downscaled":[172],"had":[174,215],"superior":[175],"matching":[176],"performance":[177],"both":[179],"ESA":[180],"CCI":[181],"measurements,":[185],"positively":[188],"respond":[189],"precipitation":[191],"variation.":[192],"Additionally,":[193],"RF":[195],"was":[196],"less":[197],"affected":[198],"by":[199],"parameters,":[200],"which":[201],"revealed":[202],"its":[203],"robustness.":[204],"Both":[205],"CART":[206,214],"KNN":[208,225],"ranked":[209,231],"second.":[210],"Compared":[211],"KNN,":[213],"relatively":[217],"close":[218],"correlation":[219],"with":[220,233],"validation":[222],"data,":[223],"but":[224],"preferable":[227],"precision.":[228],"Moreover,":[229],"BAYE":[230],"last":[232],"significantly":[234],"abnormal":[235],"values.":[237]},"counts_by_year":[{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":22},{"year":2022,"cited_by_count":18},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2018-01-05T00:00:00"}