New method for extracting multiple cropping index of North China Plain based on wavelet transform

This study chose the North China Plain as study area and proposed a new method of multiple cropping extraction from remote sensing data based on wavelet transform. Firstly, using wavelet transform to de-noise time-series SPOT VGT/NDVI（SPOT VEGETATION/normalized difference vegetation index） remote sensing data and reconstructing NDVI curve of main crops in North China Plain. Then, combining with ground samples data, farming season data and agricultural statistics data, this study extracted the multiple cropping index and spatial distribution of the North China Plain based on the double difference method. The results show that the multiple cropping index in Henan province is the largest, up to 179.4%, followed by Shandong province, which in Beijing is the smallest among the five provinces in the area, and the spatial distribution of the multiple cropping index has obvious geographical characteristics. Comparing with statistical data and other results based on remote sensing technologies, the results have the better consistency and the spatial distribution has convergence.