Assessing land-cover change and degradation in the Central Asian deserts using satellite image processing and geostatistical methods

Soil and vegetation degradation around watering points has been observed in many drylands around the world. It can be recognized in spaceborne imagery as radial brightness belts fading as a function of distance from the water wells. The primary goal of the study was to characterize spatial and temporal land degradation/rehabilitation in the Central Asian drylands. Tasseled Capʹs brightness index was found to be the best spectral transformation for enhancing the contrast between the bright-degraded areas close to the wells and the darker surrounding areas far from and in-between these wells. Semi-variograms were derived to understand the spatial structure present in the spaceborne imagery of two desert sites and in three key time periods (mid-late 1970s, around 1990, and 2000). A geostatistical model, namely the kriging interpolation technique, was applied for smoothing brightness index values extracted from 30 to 80 m spatial resolution images in order to assess spatial and temporal land-cover patterns. Change detection analysis, based on the kriging prediction maps, was performed to assess the direction and intensity of changes between the study periods. These findings were linked to the socio-economic situation before and after the collapse of the Soviet Union that influenced the grazing pressure and hence the land-use/land-cover state of the study sites. The study found that degradation occurred in some areas due to recent exploration and exploitation of the gas and oil reserves in the region. Another area was subject to rehabilitation of the rangeland due to a dramatic decrease in the number of livestock due to socio-economical changes after the independence of Kazakhstan in 1991.