Vegetation change detection research of Dunhuang city based on GF-1 data

Abstract

This study selected the Dunhuang city with the unique landscape pattern, its oasis surround by desert, for studying the vegetation change. Based on two period GaoFen-1 images, combined with field survey data, the dimidiate pixel model and fractional vegetation coverage estimation model were applied to detect the changes of local vegetation coverage from July 2013 to July 2015. Analysis showed that during the study years, the Grain for Green project had a remarkable effect on the changes. The vegetation types of intermediate high and very low grades increased by 0.66 and 6.78 km2 respectively. The low vegetation coverage decreased by 23.87 km2. The vegetation coverage types of intermediate grade increased by 88.97 km2 because of the planted forest, which accounted for 10.84% of the study area. The vegetation coverage types of high grade reduced by 72.47 km2. This change effectively prevents the spread of desert and lays a good foundation for the ecological construction of Dunhuang city.