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Information on the crop types is necessary for the studies on global food security and other environmental problems. Fields of crop types are distinguished by images for special periods of planting, growing and harvesting from other LULC types. Series of Landsat satellites can provide high quality images during those special periods. With the local knowledge of crop calendar, we calculated Normalized Difference Vegetation Index during the special periods to identify crop and other LULC types. The resultant TM-derived crop and other LULC type map were evaluated using check points and land registration data from government. The accuracy assessment proved that our area estimates of crop and other LULC types were at high level. The results of this study indicated that our algorithm could be applied at large spatial extents to map crop and other LULC types with limited images.