Remote-sensing based monitoring of planting structure and growth condition of major crops in Northeast China

Taking the main crops in Northeast China as an example, large-scale crop planting areas automatic identification methods were researched based on time-series of MODIS NDVI Datasets in this paper. The characteristics of NDVI time series of spring wheat, spring corn, soybeans and rice in Northeast China were firstly analyzed, and then the threshold values of extracting different crops were set and the extraction models of above-mentioned four kinds of crops were established, and finally the spatial distribution of these four crops of 2009 were obtained. MODIS data of Northeast China of 2009 were used to monitor the growth condition of the four kinds of crops, and the growth condition were compared with the average crop growth of last five years. The results showed that the extraction accuracy of crops planting structure was more than 87% compared with what with years of average statistical data, and crops growth condition showed different characteristics both in spatial and temporal. Research shows that it is feasible to extract different crops planting structure and monitor crops growth condition in large scale using MODIS data, which provides effective ways for large scale crops planting structure extraction in China agriculture remote sensing monitoring system.