5 research outputs found
Vegetation cover change detection and assessment in arid environment using multi-temporal remote sensing images and ecosystem management approach
Vegetation cover (VC) change detection is essential for a better
understanding of the interactions and interrelationships between humans and
their ecosystem. Remote sensing (RS) technology is one of the most beneficial
tools to study spatial and temporal changes of VC. A case study has been
conducted in the agro-ecosystem (AE) of Al-Kharj, in the center of Saudi
Arabia. Characteristics and dynamics of total VC changes during a period of
26 years (1987–2013) were investigated. A multi-temporal set of images was
processed using Landsat images from Landsat4 TM 1987, Landsat7 ETM+2000, and
Landsat8 to investigate the drivers responsible for the total VC pattern and
changes, which are linked to both natural and social processes. The analyses
of the three satellite images concluded that the surface area of the total VC
increased by 107.4 % between 1987 and 2000 and decreased by
27.5 % between years 2000 and 2013. The field study, review of secondary
data, and community problem diagnosis using the participatory rural appraisal
(PRA) method suggested that the drivers for this change are the deterioration
and salinization of both soil and water resources. Ground truth data
indicated that the deteriorated soils in the eastern part of the Al-Kharj AE
are frequently subjected to sand dune encroachment, while the southwestern
part is frequently subjected to soil and groundwater salinization. The
groundwater in the western part of the ecosystem is highly saline, with a
salinity  ≥ 6 dS m<sup>−1</sup>. The ecosystem management approach applied in
this study can be used to alike AE worldwide