Understanding trends and dynamics over the last four decades of vegetation greenness in Chile

Chile extends between latitudes 17° and 56°S, and longitudes 66° and 75°W., has at least 25 climatic zones by Koppen-Geiger, going from arid to glacial climates, and 20 general vegetation formations according to Luebert and Pliscoff. Recent changes in climate can alter the distribution of that climatic variables, which in turn will have impact on the biosphere.  This study is a data driven research looking to understand dynamics of vegetation in relation to other physical variables such as precipitation, temperature, soil moisture and evapotranspiration over the last 37 years in Chile. This is relevant giving the lack of studies that make a relation between vegetation state and different processes that might affect its present and future distribution and coverage.
To quantify the changes in Vegetation cover over time and their drivers, a regression-based mapping using satellite images and reanalysis data of physical variables such as: Precipitation (ECMWF), Vegetation (AVHRR-NDVI), Temperature (ECMWF), Soil moisture and Evapotranspiration (TerraClimate) was undertaken, covering the last four decades. The respective trends of the previous mentioned physical variables will be evaluated on a yearly basis and in the respective wet season (May to October). This evaluation will look to establish differences across the continental area of Chile in terms of z-score, slope, and significance values for each variable.
Initial results suggest that changes in vegetation greenness is mainly controlled by changes in precipitation. Precipitation, as a variable and possible driver, presents a significant negative trend in the central/south area of Chile, affecting mainly temperate to evergreen forest and shrublands. Temperature displays a negative trend all along the country, which can be translated to an increment on temperature on a range between 0.4 to 0.8 °C, with the exception of coastal areas. 
Among other results, there is an area of Chile which extends from Coquimbo to Los Lagos, with at least 3 to 6 general vegetation formations, that indicates a “greening” process. This diverse area and its vegetation coverage are not being affected by the negative trends in precipitation and temperature, and its respective NDVI trend values displays a positive trend over the last four decades.
Further spatial analysis will be undertaken to identify geographic distribution of key drivers of vegetation changes in the past and possible future projection. In addition, this dynamics, depending on its location, will be evaluated to decipher the role of different phenomena that can affect vegetation cover and its distribution, such as land degradation, desertification or changes related to human and urban densification.
Finally, machine learning algorithms such as linear regression, support vector regression, and random forest will be explored to model the patterns of present and future vegetation covers considering all possible drivers of vegetation change. This would be a useful tool to identify key areas of changes in vegetation cover under future climate change and development scenarios and can feed into development of a management strategy.