Land Use Change Detection Based on GF-1 Satellite Remote Sensing Images

Land use change detection is crucial in land resource management and monitoring. Herein, GF-1 multispectral remote sensing images, which were captured in Nanchang city of Jiangxi province in 2013-2017, are classified using the image classification method based on support vector machine. Moreover, land use change maps of the study area in those five years are generated, and land use change characteristics are analyzed. Results show that the types of land in the study area are mainly forest land, grassland, water, and building land. In the five years, the vegetation changed the most with a decrease of 54.74 km(2), followed by the water area with an increase of 22.12 km(2), then land building area with an increase of 19. 45 km(2), and bare land area with an increase of 5.17 km(2).