Desertification of Iran in the early 21th century assessed via climate
and vegetation indices
Abstract
Remote sensing of specific climatic and biogeographical factors is an
effective means of evaluating the desertification status of dryland
regions affected by negative human impacts. Here, we identify and
analyse land desertification trends in Iran via a combination of three
indices of vegetation (NPP—net primary production, NDVI—normalized
difference vegetation index, and LAI—leaf area index); and two climate
indices (LST—land surface temperature, and P—precipitation) during
the period 2001–2015. The Mann-Kendall non-parametric test, the
Theil–Sen estimator, and a simple linear regression method were then
applied to identify trends and to map regions of Iran that are
susceptible to desertification. Our results show that an area of 680,000
km2 (~ 56 %) of Iran is classified with a very high
level, indicating that a large fraction of Iran is susceptible to land
desertification. We suggest that spatial and temporal trends in the
three vegetation indices (NPP, NDVI, and LAI) and the two climate
indices (LST and P) are a cost-effective choice for the prediction and
management of future environmental trends in the world’s developing
regions, and are a step towards achieving land-use sustainability by
helping to locate the most degraded areas.