Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 122, Issue , 2016, Pages 206-221

  Zhu, Zhe ^a,d   Gallant, Alisa L ^b   Woodcock, Curtis E ^c   Pengra, Bruce ^b   Olofsson, Pontus ^c   Loveland, Thomas R ^b   Jin, Suming ^d   Dahal, Devendra ^b   Yang, Limin ^b   Auch, Roger F ^b  

^a TEXAS TECH UNIVERSITY   (United States)

^b U S GEOLOGICAL SURVEY   (United States)

^c BOSTON UNIVERSITY   (United States)

^d EARTH RESOURCES OBSERVATION AND SCIENCE EROS CENTER   (United States)

Author keywords

Auxiliary data; Continuous Change Detection and Classification (CCDC); Land cover classification; Landsat; Training strategy

Indexed keywords

DATA MINING; DECISION TREES; FORESTRY; GEOLOGICAL SURVEYS; GEOLOGY; IMAGE PROCESSING; PIXELS; PROBABILITY; SALINITY MEASUREMENT; SIGNAL DETECTION;

AUXILIARY DATA; CHANGE DETECTION; LAND COVER CLASSIFICATION; LANDSAT; TRAINING STRATEGY;

CLASSIFICATION (OF INFORMATION);

DATABASE; DETECTION METHOD; DIGITAL ELEVATION MODEL; IMAGE CLASSIFICATION; LAND COVER; LANDSAT; LANDSAT THEMATIC MAPPER; LANDSCAPE CHANGE; MONITORING SYSTEM; OBSERVATIONAL METHOD; OPTIMIZATION; PIXEL; RESOURCE MANAGEMENT; TRAINING;

UNITED STATES;

EID: 84999015235     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2016.11.004     Document Type: Article

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