Detecting Spatiotemporal Differences in Cropland Abandonment and Reforestation Across the Three-North Region of China Based on Landsat Time Series

Abstract

The Three-North region of China is an important ecological protection area. While the depopulation of rural areas and policy intervention have allowed cropland abandonment and reforestation (CAR), the spatial distribution and temporal differences underlying this landscape pattern have not been analyzed. CAR results in the gradual disappearance of the soil signal representing tilled or harvested crops, followed by a gradual increase in the interannual vegetation signal. This long-term gradual greening can be exploited to map the spatiotemporal distribution of CAR. In this study, Landsat-based detection of trends in disturbance and recovery (LandTrendr) was applied to the 1990–2020 Landsat-derived normalized difference vegetation index (NDVI) time series. The data were combined with a differential analysis of the phenological characteristics of the surveyed area to detect land surface greening trends. The relationship with actual information on CAR was then determined. The results showed widespread long-term greening in the Three-North region, covering up to 80% of the region) during the annual growth (May–June) and harvest (September–October) periods. Together, these two periods indicated 7.5% overall greening. The highest greening intensity was in areas where cropland undergone conversion to forest, which strongly suggested CAR as the succession type. The average accuracy of CAR mapping was ~80% (mapping accuracy of a greening intensity > 0.4 was as high as 87%). This study demonstrates the utility of our method in studies of driving factors of CAR and ecological benefits of secondary forest restoration.