RELATIONSHIPS BETWEEN VEGETATION INDICES AND RAINFALL AND PET AT DIFFERENT TIME-LAGS: A STUDY AT A MEDITERRANEAN TO ARID GRADIENT

The climatic gradient between the Judean Lowland and the Negev Desert in Central Israel represents a transition zone between dense shrublands in the North, and desert fringe Batha and Irano-Turanian vegetation in the South, characterizing wide Mediterranean Type Climate regions around the world. Understanding the expected response of these water-limited ecosystems to climate change presents a significant challenge due to the high geodiversity of Mediterranean environments. Studying relationships between vegetation patterns and climatic parameters is fundamental for this purpose, and remote sensing provides a valuable tool for investigating these relationships over large regions. This study aims at examining the relationships between NDVI extracted from Sentinel2 and rainfall and PET accumulated over 1 to 6 months. The analysis was first conducted for 38 sites (100x100 meters) across the climatic gradient for three years representing high (2016), low (2017), and average (2018) rainfall. Results indicate that the highest correlation between NDVI and climatic parameters is achieved for accumulation interval of two months. Least-squares analysis was then utilized for calculating the per-pixel regression coefficients between NDVI and corresponding rainfall and PET. Classification of the multi-temporal NDVI (2016-2018) and of the linear regressions' coefficients between NDVI and rainfall and PET at accumulation interval of 2 months yielded both high accuracies. Since these slope and intercept coefficients can be perceived as representing the water-use regime at each pixel, the similarity between the classification results suggests that multi-temporal NDVI typologies correspond water-use regime typologies across desert fringe ecosystems at the margins of Mediterranean regions.

Automated summary

This study examines the relationship between vegetation patterns and climatic parameters using remote sensing in Central Israel. The results indicate that the best correlation between NDVI and climatic parameters is achieved with a two-month accumulation interval. Classification of multi-temporal NDVI and linear regressions between NDVI and rainfall and PET accurately classify water-use regime typologies in desert fringe ecosystems.