Farmland and urban area dynamics monitoring in China using remote sensing and spatial statistics methodology

Abstract

With the need in the global change research project for the land -use/land-cover change information, most international and regional research organization or groups have put amounts of efforts to improve of the dynamics monitoring and database updating techniques. With the pressure on nature environment from increasing population and decreasing farmland becoming significant more and more in China, the farmland urban dynamics in historical and current times, even the change trends in the future, should be monitored and analyzed serving for regional and national social, economic and environmental sustainable development in the long future. Based on spatial and temporal series of land-use/land-cover database resources, Chinese Academy of Sciences designed a sampling framework for monitoring farmland and urban area dynamics in regional and national level. In order to test the accuracy of the sampling schema for national and regional level, we took two provinces area into overall covered change detecting process with TM images data through being interpreted by digitalization on the screen. The result shows that our stratified random sampling schema is suitable for monitoring land -use/land-cover change at national and regional level with quick response, high accuracy and low expenses. The land-use/land-cover change (LUCC) information can update the LUTEA database for global change research during certain period so that the forecasting process and evaluating analysis on land resources and environment under human and natural driving force will get essential data and produce valuable conclusions.