Monitoring to variations of vegetation cover using long-term time series remote sensing data on the Google Earth Engine cloud platform

In this paper, we take the Nandong underground river watershed as an example, to quantitatively estimate annual maximum Fractional Vegetation Cover(FVC) using time series Landsat-NDVI data from 1988 to 2016. There were in total 1952 scenes extracted and analyzed using Dimidiate Pixel Model through Google Earth Engine which is the most advanced cloud computing platform for remotely sensed big data. Spatio-temporal change characteristics during the past 29 years were also analyzed on both the entire groundwater water catchment and a pixel scales, respectively. Results show that，(1) Most parts of the Nandong underground river watershed have the middle or middle-high coverage; FVC increases with the growing elevation and slope; the area of the region in Nandong which has the annual maximum FVC higher than 60% accounts for 45.75% of the total watershed. (2) During the past 29 years, the annual maximum FVC exhibits a growing trend in Nandong, with the average annual increase rate of 0.56%. The area of the region which experienced slight improvement or obvious improvement in FVC accounts for 38.84% of the total area. (3) Compared with 1988, the area of high coverage and middle-high coverage regions in 2016 increased by 50.51% and 18.40%, respectively. While the area of the middle coverage region, middle-low coverage and low coverage regions decreased by 24.05%, 47.95% and 37.72%, respectively. Comprehensive control on karst rocky desertification, e.g. natural forest conservation and climate change, have important effects on vegetation recovery and eco-environment reconstruction in Nandong. Results of this study can provide basic data for monitoring to subsequent karst rocky desertification.