A geographically weighted random forest approach for evaluate forest change drivers in the Northern Ecuadorian Amazon.

The Tropical Andes region includes biodiversity hotspots of high conservation priority whose management strategies depend on the analysis of forest dynamics drivers (FDDs). These depend on complex social and ecological interactions that manifest on different space-time scales and are commonly evaluated through regression analysis of multivariate datasets. However, processing such datasets is challenging, especially when time series are used and inconsistencies in data collection complicate their integration.

Drought hazard in Kazakhstan in 2000-2016: a remote sensing perspective.

Droughts have significant negative impacts on livelihoods and economy of Kazakhstan. In this study, we assessed and characterized drought hazard events in Kazakhstan using satellite Remote Sensing time series for the period between 2000 and 2016. First, we calculated Vegetation Condition Index (VCI) and Standardized Enhanced Vegetation Index anomalies (Z) based on 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series.