CROP DISCRIMINATION IN SHANDONG PROVINCE BASED ON PHENOLOGY ANALYSIS OF MULTI-YEAR TIME SERIES

Crop type identification plays an important role in extracting crop acreage, assessing crop growth and arable land productivity. In this study, the main crops (winter wheat, summer maize and cotton) of Shandong Province as research objects, and the SPOT_VGT normalized difference vegetation index (NDVI) remote sensing datasets from 1999 to 2011 covering Shandong Province were acquired. The NDVI characteristic curves of typical features were extracted by combining the SPOT_VGT NDVI time series datasets, the HJ-1B image and the phenological information. Moreover, the reasonable dynamic thresholds were settled, the non-cultivated land areas were removed and the crop patterns and the crop types were identified based on the annual NDVI variation and the phenological information of the typical features. The accuracy assessment was performed through the spatial contrast and quantitative description. The overall accuracy is 77.10% in the spatial accuracy assessment compared with standard land cover classification map, and the overall relative errors of winter wheat, summer maize and cotton are 25.52%, 25.97% and 7.11% in the quantitative accuracy assessment compared with the statistical datasets. The results of research show that it is feasible to identify the crop planting patterns and crop types using the proposed classification method by combining the SPOT_VGT NDVI time series datasets with the phenological information.