Long-Term Monitoring of Cropland Change near Dongting Lake, China, Using the LandTrendr Algorithm with Landsat Imagery

Abstract

Tracking cropland change and its spatiotemporal characteristics can provide a scientific basis for assessments of ecological restoration in reclamation areas. In 1998, an ecological restoration project (Converting Farmland to Lake) was launched in Dongting Lake, China, in which original lake areas reclaimed for cropland were converted back to lake or to poplar cultivation areas. This study characterized the resulting long-term (1998–2018) change patterns using the LandTrendr algorithm with Landsat time-series data derived from the Google Earth Engine (GEE). Of the total cropland affected, ~447.48 km2 was converted to lake and 499.9 km2 was converted to poplar cultivation, with overall accuracies of 87.0% and 83.8%, respectively. The former covered a wider range, mainly distributed in the area surrounding Datong Lake, while the latter was more clustered in North and West Dongting Lake. Our methods based on GEE captured cropland change information efficiently, providing data (raster maps, yearly data, and change attributes) that can assist researchers and managers in gaining a better understanding of environmental influences related to the ongoing conversion efforts in this region.