Mapping major land cover dynamics in Beijing using all Landsat images in Google Earth Engine

Abstract

© 2017 Elsevier Inc. Land cover in Beijing experienced a dramatic change due to intensive human activities, such as urbanization and afforestation. However, the spatial patterns of the dynamics are still unknown. The archived Landsat images provide an unprecedented opportunity to detect land cover changes over the past three decades. In this study, we used the Normalized Difference Vegetation Index (NDVI) trajectory to detect major land cover dynamics in Beijing. Then, we classified the land cover types in 2015 with the Google Earth Engine (GEE) cloud calculation. By overlaying the latest land cover types and the spatial distribution of land cover dynamics, we determined the main types where a land cover change occurred. The overall change detection accuracy for three types (vegetation loss associated with negative change in NDVI, vegetation gain associated with positive change in NDVI, and no changes) is 86.13%. We found that the GEE is a fast and powerful tool for land cover mapping, and we obtained a classification map with an overall accuracy of 86.61%. Over the past 30 years, 1402.28 km2 of land was with vegetation loss and 1090.38 km2 of land was revegetated in Beijing. The spatial pattern of vegetation loss and vegetation gain shows significant differences in different zones from the center of the city. We also found that 1162.71 km2 of land was converted to urban and built-up, whereas 918.36 km2 of land was revegetated to cropland, shrub land, forest, and grassland. Moreover, 202.67 km2 and 156.75 km2 of the land was transformed to forest and shrub land in the plain of Beijing that were traditionally used for cropland and housing.