Study on Grain for Green Project implementation effect monitoring based on high resolution image — A case study in Ansai County, Shanxi Province, China

Abstract

China has implemented the Grain for Green Project (GGP) since 1999 and up until today. It is emergent to search for smart methods utilizing remote sensing to learn the states of GGP. This research studied a method for land cover information extraction based on automatic interpretations of high resolution satellite images, which could obtain local GGP information efficiently and timely. The method was used in the land cover change monitoring in Ansai County, where is the priority area for GGP implementation. Land cover change information from 2004 to 2010 was revealed based on SPOT5 and Rapideye high resolution images. The results showed that the farmland reduced overall with a decrease in percentage from 18.12% in 2004 to 13.58% in 2010, an area of 133.91km2 was lost. The proportion of forest increased from 14.60% to 37.95% with area raised by 688.18km2. As with the forest, the grassland showed a trend of growing, its ratio increased to 28.83% from 19.16%, the area raised by 564.47km2. The classification accuracy of SPOT5 is 90.73%, and the Rapideye is 92.19%, the corresponding Kappa coefficients are 0.87 and 0.89, respectively. This study can provide date support and technical reference for GGP implementation's remote sensing monitoring in the study area and other related areas in China.