Evaluating high resolution SPOT 5 satellite imagery for crop identification

Computers and Electronics in Agriculture

Volumn 75, Issue 2, 2011, Pages 347-354

  Yang, Chenghai ^a   Everitt, James H ^a   Murden, Dale ^b  

^a KIKA DE LA GARZA SUBTROPICAL AGRICULTURAL RESEARCH CENTER   (United States)

^b Rio Farms Inc   (United States)

Author keywords

Crop identification; High resolution satellite imagery; Maximum likelihood classification; SPOT 5; Support vector machine

Indexed keywords

A-SPOTS; ACCURACY ASSESSMENT; CLASSIFICATION ACCURACY; CLASSIFICATION RESULTS; COARSER RESOLUTION; CROP IDENTIFICATION; CROP MONITORING; GROWTH STAGES; HIGH RESOLUTION; HIGH RESOLUTION SATELLITE IMAGERY; MAHALANOBIS DISTANCES; MAXIMUM LIKELIHOOD CLASSIFICATION; MINIMUM DISTANCE; MULTI-SPECTRAL IMAGERY; NEAR INFRARED; NEW OPPORTUNITIES; ORIGINAL IMAGES; PIXEL SIZE; SATELLITE IMAGES; SHORT WAVE INFRARED; SPECTRAL ANGLE MAPPERS; SPECTRAL BAND; SPOT 5; STATISTICAL DIFFERENCES; SUPERVISED CLASSIFICATION; SVM CLASSIFICATION;

CLASSIFIERS; CROPS; IMAGE PROCESSING; INFRARED RADIATION; MAXIMUM LIKELIHOOD ESTIMATION; PIXELS; QUADRATURE PHASE SHIFT KEYING; RATING; REMOTE SENSING; SUPPORT VECTOR MACHINES;

SATELLITE IMAGERY;

ACCURACY ASSESSMENT; GROWTH RATE; MAXIMUM LIKELIHOOD ANALYSIS; MULTISPECTRAL IMAGE; PIXEL; SATELLITE IMAGERY; SHORTWAVE RADIATION; SPECTRAL RESOLUTION; SPOT; VECTOR;

TEXAS; UNITED STATES;

EID: 79551684301     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2010.12.012     Document Type: Article

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