{"id":"https://openalex.org/W2182293987","doi":null,"title":"Application of Bayesian Methods for Assessing Detection Accuracy in Remote Sensing","display_name":"Application of Bayesian Methods for Assessing Detection Accuracy in Remote Sensing","publication_year":2001,"publication_date":"2001-01-01","ids":{"openalex":"https://openalex.org/W2182293987","mag":"2182293987"},"language":"en","primary_location":{"id":"mag:2182293987","doi":null,"is_oa":false,"landing_page_url":"https://www.amstat.org/sections/SRMS/Proceedings/y2001/Proceed/00030.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5062340553","display_name":"Bahman Shafii","orcid":"https://orcid.org/0000-0001-5962-1651","observed_orcids":["https://orcid.org/0000-0001-5962-1651"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bahman Shafii","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0001-5962-1651","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5074090137","display_name":"William J. Price","orcid":"https://orcid.org/0000-0002-4989-6333","observed_orcids":["https://orcid.org/0000-0002-4989-6333"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"William J. Price","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-4989-6333","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3732,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67626707,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.004699999932199717,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13309","display_name":"Reliability and Agreement in Measurement","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bayesian-estimation","display_name":"Bayesian estimation","score":0.7319999933242798},{"id":"https://openalex.org/keywords/classification-accuracy","display_name":"classification accuracy","score":0.6869999766349792},{"id":"https://openalex.org/keywords/cohen-s-kappa","display_name":"Cohen's kappa","score":0.8799999952316284},{"id":"https://openalex.org/keywords/omission-errors","display_name":"omission errors","score":0.7590000033378601},{"id":"https://openalex.org/keywords/errors-of-commission","display_name":"commission errors","score":0.996999979019165},{"id":"https://openalex.org/keywords/confusion-matrix","display_name":"confusion matrix","score":0.7910000085830688},{"id":"https://openalex.org/keywords/remote-sensing-image-classification","display_name":"remote sensing image classification","score":0.6110000014305115}],"concepts":[{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6649615168571472},{"id":"https://openalex.org/C163864269","wikidata":"https://www.wikidata.org/wiki/Q1107106","display_name":"Cohen's kappa","level":2,"score":0.6294770240783691},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5922654867172241},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5032748579978943},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.49015769362449646},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4901162087917328},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.45914387702941895},{"id":"https://openalex.org/C41054675","wikidata":"https://www.wikidata.org/wiki/Q185547","display_name":"Binomial distribution","level":2,"score":0.43939611315727234},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4204738736152649},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41811975836753845},{"id":"https://openalex.org/C2778724333","wikidata":"https://www.wikidata.org/wiki/Q14401","display_name":"Kappa","level":2,"score":0.4118501543998718},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3564501702785492},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34243518114089966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28310155868530273},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:2182293987","doi":null,"is_oa":false,"landing_page_url":"https://www.amstat.org/sections/SRMS/Proceedings/y2001/Proceed/00030.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W88102679","https://openalex.org/W1503422628","https://openalex.org/W1523879065","https://openalex.org/W1964924117","https://openalex.org/W1989492805","https://openalex.org/W2138973222","https://openalex.org/W2279077827","https://openalex.org/W2404198674","https://openalex.org/W2504969653"],"related_works":["https://openalex.org/W2586689912","https://openalex.org/W2580783796","https://openalex.org/W2109975565","https://openalex.org/W2046963292","https://openalex.org/W3174833194","https://openalex.org/W2039547568","https://openalex.org/W2398311942","https://openalex.org/W2999585470","https://openalex.org/W2136163895","https://openalex.org/W1992203211"],"abstract_inverted_index":{"Digital":[0],"imagery":[1],"and":[2,8,25,35,64,78,92,95,102],"remote":[3],"sensing":[4],"have":[5],"become":[6],"popular":[7],"accessible":[9],"tools":[10],"in":[11,99,130],"many":[12],"scientific":[13],"research":[14],"fields.":[15],"Accuracy":[16],"of":[17,21,55],"classification,":[18],"the":[19,56,118],"degree":[20],"agreement":[22,38,73],"between":[23],"classification":[24],"ground":[26],"truth,":[27],"is":[28],"traditionally":[29],"quantified":[30],"by":[31],"an":[32],"error":[33,66],"matrix":[34],"summarized":[36],"using":[37],"measures":[39,74],"such":[40],"as":[41,62],"Cohen\u2019s":[42],"kappa.":[43],"The":[44],"kappa":[45],"statistic,":[46],"however,":[47],"can":[48],"be":[49,52,114],"shown":[50],"to":[51,61,116,126],"a":[53,86],"transformation":[54],"marginal":[57],"proportions":[58],"commonly":[59],"referred":[60],"omissional":[63,91],"commissional":[65,93],"rates.":[67],"Alternative":[68],"estimation":[69,88,119],"methods":[70],"for":[71,90],"these":[72],"include":[75],"binomial,":[76],"bootstrap":[77],"Bayesian":[79,87],"techniques.":[80],"In":[81],"this":[82,131],"study,":[83],"we":[84],"develop":[85],"method":[89],"errors":[94],"discuss":[96],"its":[97],"utilization":[98],"variability":[100],"assessment":[101],"inference.":[103],"We":[104],"will":[105],"also":[106],"show":[107],"how":[108],"additional":[109],"or":[110],"sequential":[111],"information":[112],"may":[113],"incorporated":[115],"improve":[117],"situation.":[120],"Results":[121],"are":[122],"demonstrated":[123],"with":[124],"reference":[125],"our":[127],"previous":[128],"work":[129],"area.":[132]},"counts_by_year":[],"updated_date":"2025-11-06T04:12:42.849631","created_date":"2016-06-24T00:00:00"}