Vegetation trends and dynamics in Shada Mountain, Saudi Arabia, (1984–2023): insights from Google Earth Engine and R analysis
This research analyses the long-term vegetation trends in Shada Mountain across
six elevation zones, utilizing Landsat 5, 7, 8, and 9 imageries processed via Google
Earth Engine and R. The study managed differences in images resolution through
meticulous calibration and image processing techniques. The study is structured
around two objectives: examining the relationship between vegetation and its
proximity to streams and land surface temperature and analyzing trends in the
Normalized Difference Vegetation Index (NDVI). Regression analysis revealed a
negative correlation between vegetation and proximity to streams in lower zones
(1–3), with no significant effect in higher zones (4–6). NDVI trend analysis
indicated an overall increase in vegetation across most zones, with the
exception of zone 5, which displayed a negative trend (slope −0.0025). The
findings reveal that the decline is particularly pronounced among key tree species
such as Ficus cordata subsp. salicifolia and Acacia asak, suggesting potential
impacts from climate change and land use alterations. These zone-specific
insights deepen our understanding of the dynamic ecological processes in
semi-arid environments and guide targeted environmental management and
conservation efforts.
Mangrove ecosystems are vital to arid environments like Saudi Arabia, offering crucial ecological services and enhancing biodiversity. This study investigates the spatial distribution and temporal…
This research analyses the long-term vegetation trends in Shada Mountain across
six elevation zones, utilizing Landsat 5, 7, 8, and 9 imageries processed via Google
Earth Engine and R…
Abstract: Environmental, soil, and groundwater pollution
from toxic heavy metals, as well as food safety are all
global concerns nowadays. The effect of various processes
viz.…