Detecting Crop Rotations in China Using Avhrr Imagery and Ancillary Data

The situation of cropland use in China is very complicated. In many areas, the cropland is used in multi-cropped ways. There is a need for better information on the area and distribution of cropland using in different cropping rotation systems, but it is not easy to get it in traditional census ways. This paper focuses on the methodology of crop rotations detection in China using multitemporal satellites images. Two agricultural regions located in the middle of China were chosen as the study areas. The dataset used here includes 10 days composites NDVI (36 periods) obtained from the NASA Pathfinder AVHRR Land dataset, land-cover dataset derived from TM images, and the ground based agricultural monitoring data. The discrete Fourier transform was applied to the NDVI data set on a per pixel basis for the whole cropland of the study areas and then the additive and the first four harmonics (amplitude and phase) were classified using ISOLATE unsupervised classification algorithm for both regions respectively. Crop information derived from local stations and the Chinese cultivated system regionalization map were used to assess the accuracy of the result. The result of this study showed that the methodology used in this study is, in general, feasible for detecting crop rotations in China.