Significant Findings on the Spatio-Temporal Dynamics of the Satellite-based Aridity Index (SbAI) in Argentina

The increasing impacts of climate variability pose a challenge in understanding the dynamics of arid and semi-arid regions, especially in the context of desertification and land degradation. However, in South America, there is a lack of comprehensive studies on the spatial and temporal shifts in aridity zones, particularly using satellite-based indices. The present paper aimed at assessing the spatio-temporal distribution of the Satellite-based Aridity Index (SbAI) in Argentina to analyze possible shifts in the margins of desert and semi-desert regions during the period 2005–2022. Unsupervised classifications were carried out using K-means clustering algorithm taking into account SbAI, Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), Shuttle Radar Topography Mission (SRTM) digital elevation, Vegetation transpiration (Ec) and wetness tasseled caps classification variables. Five Aridity-related Classes associated with hyper-arid, arid, semi-arid, sub-humid and humid regions were identified. Between the 2005–2013 and 2014–2022 periods, the arid/semi-arid and the semi-arid/sub-humid boundaries shifted to the southwest of the country, i.e., arid and semi-arid areas have undergone a retreat. A discrete wavelet low-pass filtering to identify long-term cyclic dynamics along with a 1D unsupervised signal clustering was applied on the class changing pixels SbAI time series. The shifting aridity frontier seems to be associated with the El Niño Southern Oscillation. Additionally, a simplified model, based on SbAI-NDVI-Altitude thresholds, is proposed to map aridity in the region, improving the SbAI-based models previously developed.