Bayesian Markov Chain Random Field Cosimulation for Improving Land Cover Classification Accuracy

Mathematical Geosciences

Volumn 47, Issue 2, 2015, Pages 123-148

  Li, Weidong ^a   Zhang, Chuanrong ^a   Willig, Michael R ^a   Dey, Dipak K ^a   Wang, Guiling ^a   You, Liangzhi ^b  

^a UNIVERSITY OF CONNECTICUT   (United States)

^b INTERNATIONAL FOOD POLICY RESEARCH INSTITUTE   (United States)

Author keywords

Bayesian inference; Cosimulation; Expert interpretation; Geostatistics; Land cover classification; Markov chain; Remotely sensed image

Indexed keywords

BAYESIAN NETWORKS; IMAGE CLASSIFICATION; IMAGE ENHANCEMENT; INFERENCE ENGINES; LAND USE; MARKOV CHAINS; MAXIMUM LIKELIHOOD; PIXELS; REMOTE SENSING;

BAYESIAN INFERENCE; COSIMULATION; EXPERT INTERPRETATION; GEO-STATISTICS; LAND COVER CLASSIFICATION; REMOTELY SENSED IMAGES;

CLASSIFICATION (OF INFORMATION);

ACCURACY ASSESSMENT; ALGORITHM; BAYESIAN ANALYSIS; GEOSTATISTICS; IMAGE CLASSIFICATION; LAND COVER; LAND USE; MARKOV CHAIN; MAXIMUM LIKELIHOOD ANALYSIS; REMOTE SENSING;

EID: 85027917195     PISSN: 18748961     EISSN: 18748953     Source Type: Journal    
DOI: 10.1007/s11004-014-9553-y     Document Type: Article

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