Precipitation, temperature, and vegetation indices analysis for Saudi Arabia region: Feasibility of Google Earth Engine

Abstract

Climatic disaster is continuously triggering environmental degradation and thermal diversification over the earth's surface. Global warming and anthropogenic activities are the triggering factors for thermal variation and ecological diversification. Saudi Arabia has also recorded precipitation, temperature, and vegetation dynamics over the past decades. Therefore, monitoring past precipitation, temperature, and vegetation condition information can help to prepare future disaster management plans and awareness strategies. The Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN-CDR) from the Center for Hydrometeorology and Remote Sensing (CHRS) data portal and Moderate Resolution Imaging Spectroradiometer (MODIS) are applied for precipitation, Land Surface Temperature (LST), Enhance Vegetation Index (EVI), and Normalized Difference Vegetation Index (NDVI) from 2003 to 2021 respectively. Yearly mean LST, EVI, NDVI, and precipitation values are calculated through the Google Earth Engine (GEE) cloud computing platform. MODIS-based LST datasets recorded the highest temperatures is 43.02 °C (2003), 45.56 °C (2009), 47.83 °C (2015), and 49.24 °C (2021) respectively. In between nineteen years, the average mean LST increased by 6.22 °C and the most affected areas are Riyadh, Jeddah, Abha, Dammam, and Al Bahah. The mean Precipitation is recorded around 776 mm, 842 mm, 1239 mm, and 1555 mm for the four study periods, while the high precipitation area is Jazan, Asir, Baha, and Makkah provinces. In between nineteen years, 779 mm of precipitation is increasing in Saudi Arabia.  Similarly, the NDVI vegetation indices observed 0.885 (2003), 0.871 (2009), 0.891 (2015), and 0.943 (2021), while EVI observed 0.775 (2003), 0.776 (2009), 0.744 (2015), and 0.847 (2021). The R2 values of the LST and EVI correlation is 0.0239 (2003), 0.0336 (2009), 0.0136 (2015) and 0.0175 (2021) similarly correlation between LST and NDVI is 0.0352 (2003), 0.0265 (2009), 0.0183 (2015) and 0.0161 (2021) respectively. The vegetation indices indicate that the green space is gradually increasing in Saudi Arabia and the highly vegetated lands are Meegowa, An Nibaj, Tabuk, Wadi Al Dawasir, Al Hofuf, and part of Qaryat Al Ulya. This analysis indicates that the temperature is increasing but precipitation and green spaces are increasing because of the groundwater recharge through dam construction, precision agriculture, and planned build-up is helps to prepare Saudi Arabia as a green country. Therefore, more attention to preparing the strategic agricultural plants as well as other vegetation and artificial groundwater recharge can improve the country as a green nation. This analysis might help to prepare future planning, awareness, and disaster management teams to prepare for future disasters and strategic steps for sustainable development.