Assessment of the Effectiveness of Sand-Control and Desertification in the Mu Us Desert, China

Abstract

The first successful sand-control was achieved in the Mu Us Desert by local people in the 1950–1960s, and their experience and approach have been extended to the whole Ordos and Northern China since then. The objective of this paper is to assess comprehensively the effectiveness of sand-control in 15 counties in and around Mu Us using multitemporal satellite images and socioeconomic data. After atmospheric correction, Landsat TM and OLI images were harnessed for land cover classification based on the ground-truth data and for derivation of the GDVI (generalized difference vegetation index) to extract the biophysical changes of the managed desert and desertification. Climatic, socioeconomic, environmental and spatial factors were selected for coupling analysis by multiple linear and logistic regression models to reveal the driving forces of desertification and their spatial determinants. The results show that from 1991 to 2020, 8712 km2 or 63% of the desert has been converted into pastures and shrublands with a greenness increase of 0.3509 in GDVI; the effectiveness of sand-control is favored by the rational agropastoral activities and policies; though desertification occurs locally, it is associated with both climatic and socioeconomic factors, such as wind speed, precipitation, water availability, distance to roads and animal husbandry.

Remote sensing-based multi-scenario land use change simulation in Hefei, China

“…In this study, the COST model was used to correct the atmospheric effects of Landsat images [9][10][11][12] , and six spectral bands together with the normalized difference vegetation index (NDVI), the generalized difference vegetation index (GDVI), enhanced vegetation index (EVI), land surface temperature (LST) and elevation, slope, aspect derived from DEM, were recombined to form a new dataset through the Layer Stacking function [12] . According to the Standard of the Third National Land Survey of China, land use/cover was divided into water-bodies, built-up areas, croplands, forests, grasslands and bare lands.…”

“…Moreover, the socioeconomic development has maintained a rapid growth rate in Hefei thanks to the Reform and Openingup Policy since 1987 [9,10]. The rapid development has caused certain problems, e.g., unbalanced land use, unreasonable land exploitation, and contradiction between human demand and land provision.…”

A new radar vegetation index for research in the dry areas

“…As sandy land (or desert), desertification used to be an important phenomenon in the past but it has been reduced thanks to the sand-control activities by the governments and household companies since recent decades [10] . These sand-control enterprises cultivated gradually grasses, shrubs and then trees inside the "straw checkerboard barriers" so that the desert area has been revived in Mu Us.…”

Land Use/Cover Change Prediction Based on a New Hybrid Logistic-Multicriteria Evaluation-Cellular Automata-Markov Model Taking Hefei, China as an Example

“…Chavez (1996) called this COST (COSine Theta) model [58]. This study employed the COST model for atmospheric correction of Landsat images, in which the band minimum was used to eliminate the haze effect, and the at-satellite radiance of each band was transformed into surface reflectance [59,60]. LST (land surface temperature) was also calculated from the thermal infrared band of Landsat TM and OLI images [61][62][63][64].…”