Crop type classification by simultaneous use of satellite images of different resolutions

IEEE Transactions on Geoscience and Remote Sensing

Volumn 52, Issue 6, 2014, Pages 3637-3649

  Liu, Mark W ^a,b   Ozdogan, Mutlu ^a   Zhu, Xiaojin ^c  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b 8 to 18 Media ^*  (United States)

^c University of Wisconsin Madison   (United States)

Author keywords

Agriculture; classification algorithms; cost function; crops; geospatial analysis; image processing; pattern recognition; probability; remote sensing; Vegetation mapping

Indexed keywords

AGRICULTURE; ALGORITHMS; COST FUNCTIONS; IMAGE PROCESSING; IMAGE RESOLUTION; PATTERN RECOGNITION; PROBABILITY; REMOTE SENSING; SATELLITE IMAGERY;

CLASSIFICATION ALGORITHM; COMPUTATIONAL PERFORMANCE; CROP TYPE CLASSIFICATION; ENVIRONMENTAL APPLICATIONS; GEO-SPATIAL ANALYSIS; HIGH TEMPORAL FREQUENCY; REFLECTANCE CHARACTERISTICS; VEGETATION MAPPING;

CROPS;

ACCURACY ASSESSMENT; ALGORITHM; CROP; FREQUENCY ANALYSIS; IMAGE CLASSIFICATION; IMAGE RESOLUTION; MAPPING; REMOTE SENSING; SATELLITE IMAGERY;

EID: 84896403906     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2013.2274431     Document Type: Article

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