{"id":"https://openalex.org/W2161911139","doi":"https://doi.org/10.1109/igarss.2009.5417811","title":"Markov random field model-based soil moisture content segmentation from MODIS satellite data","display_name":"Markov random field model-based soil moisture content segmentation from MODIS satellite data","publication_year":2009,"publication_date":"2009-01-01","ids":{"openalex":"https://openalex.org/W2161911139","doi":"https://doi.org/10.1109/igarss.2009.5417811","mag":"2161911139"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2009.5417811","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2009.5417811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 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/A5088101246","display_name":"Ken-Chung Ho","orcid":null},"institutions":[{"id":"https://openalex.org/I125934054","display_name":"National United University","ror":"https://ror.org/04twccc71","country_code":"TW","type":"education","lineage":["https://openalex.org/I125934054"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ken-Chung Ho","raw_affiliation_strings":["Department of Electronic Engineering, National United University, Miaoli, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, National United University, Miaoli, Taiwan","institution_ids":["https://openalex.org/I125934054"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110347385","display_name":"Y.C. Tzeng","orcid":null},"institutions":[{"id":"https://openalex.org/I125934054","display_name":"National United University","ror":"https://ror.org/04twccc71","country_code":"TW","type":"education","lineage":["https://openalex.org/I125934054"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Chang Tzeng","raw_affiliation_strings":["Department of Electronic Engineering, National United University, Miaoli, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, National United University, Miaoli, Taiwan","institution_ids":["https://openalex.org/I125934054"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051119879","display_name":"Chun-Long Woo","orcid":null},"institutions":[{"id":"https://openalex.org/I125934054","display_name":"National United University","ror":"https://ror.org/04twccc71","country_code":"TW","type":"education","lineage":["https://openalex.org/I125934054"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chun-Long Woo","raw_affiliation_strings":["Department of Electronic Engineering, National United University, Miaoli, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, National United University, Miaoli, Taiwan","institution_ids":["https://openalex.org/I125934054"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17324561,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"48","issue":null,"first_page":"III","last_page":"538"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.9998000264167786,"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":0.9998000264167786,"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/T10535","display_name":"Landslides and related hazards","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"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":0.9952999949455261,"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/water-content","display_name":"Water content","score":0.6920804977416992},{"id":"https://openalex.org/keywords/normalized-difference-vegetation-index","display_name":"Normalized Difference Vegetation Index","score":0.6248921155929565},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.6035028696060181},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5336728096008301},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.4821128845214844},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.46291854977607727},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.4464353322982788},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.41064363718032837},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.38284987211227417},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21381357312202454},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.19814810156822205},{"id":"https://openalex.org/keywords/leaf-area-index","display_name":"Leaf area index","score":0.17345917224884033},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.16711416840553284},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14775994420051575},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12626922130584717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.10202562808990479}],"concepts":[{"id":"https://openalex.org/C24939127","wikidata":"https://www.wikidata.org/wiki/Q373499","display_name":"Water content","level":2,"score":0.6920804977416992},{"id":"https://openalex.org/C1549246","wikidata":"https://www.wikidata.org/wiki/Q718775","display_name":"Normalized Difference Vegetation Index","level":3,"score":0.6248921155929565},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.6035028696060181},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5336728096008301},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.4821128845214844},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.46291854977607727},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.4464353322982788},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.41064363718032837},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.38284987211227417},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21381357312202454},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.19814810156822205},{"id":"https://openalex.org/C25989453","wikidata":"https://www.wikidata.org/wiki/Q446746","display_name":"Leaf area index","level":2,"score":0.17345917224884033},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.16711416840553284},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14775994420051575},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12626922130584717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.10202562808990479},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","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/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.0},{"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/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2009.5417811","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2009.5417811","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5299999713897705,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1554544485","https://openalex.org/W1978835122","https://openalex.org/W1988810672","https://openalex.org/W1989222601","https://openalex.org/W2118099382","https://openalex.org/W2130736855","https://openalex.org/W2148459381","https://openalex.org/W2157245283","https://openalex.org/W2159997012","https://openalex.org/W2168959566","https://openalex.org/W2171253919","https://openalex.org/W6633362792"],"related_works":["https://openalex.org/W3207046288","https://openalex.org/W3023446922","https://openalex.org/W4324030030","https://openalex.org/W4233585817","https://openalex.org/W2016045932","https://openalex.org/W1675950995","https://openalex.org/W2188882668","https://openalex.org/W2004379491","https://openalex.org/W2088323302","https://openalex.org/W2083140487"],"abstract_inverted_index":{"The":[0],"soil":[1,21],"moisture":[2,22],"(SM)":[3],"content":[4],"plays":[5],"an":[6],"important":[7],"role":[8],"in":[9,133],"hydrology,":[10],"agronomy,":[11],"and":[12,39,80,104],"meteorology.":[13],"We":[14],"propose":[15],"to":[16],"estimate":[17],"the":[18,51,59,86,96,114],"type":[19,125],"of":[20,37,53,65,77],"content.":[23],"This":[24,107,124],"estimation":[25,52],"is":[26,43,56,120],"modeled":[27],"as":[28],"a":[29,35,61],"Markov":[30],"random":[31],"field":[32],"over":[33],"which":[34,119],"regression":[36,76],"NDVI":[38,79],"LST":[40,81],"MODIS":[41,66,78],"data":[42,82],"constructed":[44],"into":[45],"Gaussian":[46],"distributions.":[47],"Under":[48],"this":[49],"model,":[50],"SM":[54],"types":[55],"achieved":[57,112],"by":[58,113],"maximum":[60],"posteriori":[62],"(MAP)":[63],"segmentation":[64],"data.":[67],"Experimental":[68],"results":[69],"show":[70],"that":[71,98],"our":[72],"ICM":[73],"based":[74],"on":[75],"can":[83,100,109,127],"successfully":[84,101],"segment":[85],"wooded":[87],"grassland":[88],"region":[89],"under":[90],"studying":[91],"Our":[92],"method":[93],"also":[94],"has":[95],"advantage":[97],"it":[99],"distinguish":[102],"\"dryness\"":[103],"\"wetness.":[105],"\"":[106],"distinguishing":[108],"not":[110],"be":[111,128],"linear":[115],"two-source":[116],"model":[117],"[3],":[118],"much":[121],"more":[122],"complex.":[123],"information":[126],"used":[129],"for":[130],"further":[131],"applications":[132],"hydrology":[134],"or":[135],"drought":[136],"management.":[137]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}