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the precipitation . The identified relationship with the very best correlation represents the utmost quantity of vegetation variability that can be defined by the precipitation, and corresponding RUE values could be calculated. Using this relationship, the climate component of the NDVI time series could be reconstructed, and the distinction between this and the unique time collection is attributed to anthropogenic and different causes. In Russia, initially of the 2000s, about 7% of the whole space was threatened by desertification Gunin and Pankova ; Kust . Turkey is considered highly susceptible to drought, land degradation and desertification Türkeş , . About 60% of Turkey’s land area is characterised with hydro-climatological conditions favourable for desertification Türkeş . ÇEMGM 390 estimated that about half of Turkey’s land area 48.6% is vulnerable to average-to-excessive desertification. In Central Asia, drying up of the Aral Sea is continuous to have negative impacts on regional microclimate and human well being Issanova and Abuduwaili ; Lioubimtseva ; Micklin ; Xi and Sokolik . Half of the area’s irrigated lands, particularly in the Amudarya and Syrdarya river basins, have been affected by secondary salinisation Qadir . Le 1792 confirmed that about 57% of croplands in Kazakhstan and about 20% of croplands in Kyrgyzstan had reductions in their vegetation productivity between 1982 and 2006. Chen 350 indicated that about fifty eight% of the grasslands in the region had reductions of their vegetation productiveness between 1999 and 2015. Anthropogenic factors had been the primary driver of this loss in Turkmenistan and Uzbekistan, while the function of human drivers was smaller than that of local weather-associated factors in Tajikistan and Kyrgyzstan Chen 2019. The total costs of land degradation in Central Asia were estimated to equal about 6 billion USD annually Mirzabaev . Overall, improved estimation and mapping of areas undergoing desertification are needed. This requires a mixture of rapidly increasing sources of remotely sensed knowledge, ground observations and new modelling approaches. This is a crucial hole, especially in the context of measuring progress in direction of attaining the land degradation-neutrality target by 2030 in the framework of SDGs. Vegetation Optical Depth has been out there since the Nineteen Eighties. VOD is predicated on microwave measurements and is expounded to whole above-floor biomass water content material. Unlike NDVI, which is simply sensitive to green canopy cowl, VOD can also be delicate to water in woody components of the vegetation and therefore supplies a view of vegetation adjustments that can be complementary to NDVI. Liu 278 used VOD tendencies to research biomass adjustments and located that VOD was intently related to precipitation modifications in drylands. To complement their work with NDVI, Andela 279 additionally applied the RESTREND methodology to VOD. By deciphering NDVI and

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