Using remote sensing to assess vegetation dynamics in a hyper-arid region: The Arava valley as a case study

Hyper-arid areas are characterized by high evaporation rates, low levels of precipitation, and significant intra-annual variation in both the quantity and timing of rainfall. While harsh desert conditions pose considerable challenges, the resilience of local vegetation indicates remarkable adaptation strategies. This study aimed to evaluate the response of vegetation cover to fluctuating rainfall amounts typical to the hyper-arid environment, using the Arava Valley (Israel/Jordan) as a case study. We analyzed a long-term time series (1984–2022) of monthly rainfall records to examine overall trends and identify distinct dry (drought) and wet periods, using the Standardized Precipitation Index (SPI). We used the Normalized Difference Vegetation Index (NDVI) derived from Landsat satellite imagery to quantify and monitor vegetation cover and its annual dynamics, and constructed proxies for perennial and annual vegetation based on their yearly phenological cycles. Our results revealed no clear statistical long-term trend in rainfall amounts; however, we identified transitions between wet and dry sub-periods occurring in clusters spanning several years. Vegetation cover aligned with rainfall patterns; no distinct long-term trend was seen but clear declines in vegetation cover and subsequent recoveries corresponded to rainfall amounts. When assessing vegetation responsiveness to the fluctuating conditions, we identified a time lag of two to four years between the response of annual and perennial vegetation during transitions between contrasting sub-periods. The year-to-year correlation between rainfall and yearly vegetation cover was strongest when averaging rainfall over two consecutive years for annual vegetation cover (∼0.45–0.65), and three to four consecutive years for perennial vegetation cover (∼0.52–0.79), highlighting the significant influence of past years' conditions on yearly vegetation cover. By integrating long-term remote sensing satellite imagery and climatic records, we were able to uncover the complexity of rainfall-vegetation dynamics and the remarkable resilience of natural desert vegetation in the extreme conditions of hyper-arid environments.