Spatial dynamics modelling of crops pattern with remote sensing classification data

The objective of this paper is to describe the method of crops pattern change allocation, and to simulate the crops pattern in Heilongjiang province utilizing crop pattern simulator (CROPS) model. In this study, based on interpreted remote sensing data and crops pattern statistical data, CROPS model simulates long time series crop spatial pattern. Firstly, crops pattern and driving factor analysis using the method of logistic regression were described in detail in this article, to identify the probability of spatio-temporal distribution of various crops. Then, the method of spatial distribution of iteration combined with the space distribution probability was applied to allocate statistical data in the study area. Finally, we collect 14 driving factors and other input data to simulate the crop pattern in Heilongjiang Province during 2005-2010. The validation was performed using remote sensing image interpretation result in 2007 to test simulation accuracy. Results showed that it can finely allocate the crops patterns in a region, and provide a basis for analysis of crops spatial dynamics change. This method can produce a series of crop patterns of data and effectively improve the remote sensing interpretation work efficiency.