Abstract
Explicitly identifying the desertification changes and causes has been a hot issue of eco-environment sustainable development in the China–Mongolia–Russia Economic Corridor (CMREC) area. In this paper, the desertification change patterns between 2000 and 2015 were identified by operating the classification and regression tree (CART) method with multisource remote sensing datasets on Google Earth Engine (GEE), which has the higher overall accuracy (85%) than three other methods, namely support vector machine (SVM), random forest (RF) and Albedo-normalized difference vegetation index (NDVI) models. A contribution index of climate change and human activities on desertification was introduced to quantitatively explicate the driving mechanisms of desertification change based on the temporal datasets and net primary productivity (NPP). The results show that the area of slight desertification land had increased from 719,700 km2 to 948,000 km2 between 2000 and 2015. The area of severe desertification land decreased from 82,400 km2 to 71,200 km2. The area of desertification increased by 9.68%, in which 69.68% was mainly caused by human activities. Climate change and human activities accounted for 68.8% and 27.36%, respectively, in the area of desertification restoration. In general, the degree of desertification showed a decreasing trend, and climate change was the major driving factor in the CMREC area between 2000 and 2015.
Highlights
Desertification, as a major type of land degradation around the world, has been a hot topic in the field of global change and sustainable development, especially in arid areas [1,2,3,4]
Based on the Landsat 8 data, and the products obtained by classification and regression tree (CART), random forest (RF), support vector machine (SVM), and Albedo-normalized difference vegetation index (NDVI) methods in this study, we selected severe desertification, high desertification, moderate desertification, slight desertification, and non-desertification to conduct an intuitive comparison (Figure 3)
The classification accuracy (Table 6) of desertification in the China–Mongolia–Russia Economic Corridor (CMREC) area by operating the four methods of CART, RF, SVM, and Albedo-NDVI shows that the accuracy of the CART model (OA = 85%, Kappa = 0.754) is higher than other methods
Summary
Desertification, as a major type of land degradation around the world, has been a hot topic in the field of global change and sustainable development, especially in arid areas [1,2,3,4]. Desertification directly affects the subsistence of about three billion people living in desertified areas, which would put at risk the livelihoods of about 135 million people around the world by 2045 [5,6]. The CMREC area is a typical arid zone with a poor environment that is sensitive to climate change and human activities, on the China–Mongolia border and in the Gobi Desert area [3,10]. How to effectively monitor the desertification trend and understand the driving factors have become the two significant issues in the sustainable development of the CMREC area, especially on the China–Mongolia border
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