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 t...
Geo-parcel based crop identification plays an important role in precision agriculture. It meets the ...
The combination of high spatial resolution and multi-date satellite imagery offers new opportunities...
Crop area and its spatial distribution are generally considered to be essential data inputs for crop...
In this landscape-scale study we explored the potential for multitemporal 10-day composite data from...
Abstract. In this landscape-scale study we explored the potential for multi-temporal 10-day composit...
In this landscape-scale study we explored the potential for multitemporal 10-day composite data from...
Crop type classification with satellite imageries is widely applied in support of crop production ma...
Mapping and monitoring the distribution of croplands and crop types support policymakers and interna...
The spatial distribution of fine crop types at regional scale is required by numerous research commu...
When using microwave remote sensing for land use/land cover (LULC) classifications, there are a wide...
Most methods used for crop classification rely on the ground-reference data of the same year, which ...
Mapping the spatial and temporal dynamics of cropland is an important prerequisite for regular crop ...
LiDAR data are becoming increasingly available, which has opened up many new applications. One such ...
The derivation of leaf area index (LAI) from satellite optical data has been the subject of a large ...
Maps of different kinds of crops offer information about both crop distribution and crop mix, which ...
Geo-parcel based crop identification plays an important role in precision agriculture. It meets the ...
The combination of high spatial resolution and multi-date satellite imagery offers new opportunities...
Crop area and its spatial distribution are generally considered to be essential data inputs for crop...
In this landscape-scale study we explored the potential for multitemporal 10-day composite data from...
Abstract. In this landscape-scale study we explored the potential for multi-temporal 10-day composit...
In this landscape-scale study we explored the potential for multitemporal 10-day composite data from...
Crop type classification with satellite imageries is widely applied in support of crop production ma...
Mapping and monitoring the distribution of croplands and crop types support policymakers and interna...
The spatial distribution of fine crop types at regional scale is required by numerous research commu...
When using microwave remote sensing for land use/land cover (LULC) classifications, there are a wide...
Most methods used for crop classification rely on the ground-reference data of the same year, which ...
Mapping the spatial and temporal dynamics of cropland is an important prerequisite for regular crop ...
LiDAR data are becoming increasingly available, which has opened up many new applications. One such ...
The derivation of leaf area index (LAI) from satellite optical data has been the subject of a large ...
Maps of different kinds of crops offer information about both crop distribution and crop mix, which ...
Geo-parcel based crop identification plays an important role in precision agriculture. It meets the ...
The combination of high spatial resolution and multi-date satellite imagery offers new opportunities...
Crop area and its spatial distribution are generally considered to be essential data inputs for crop...