ArticleScientific reports2021
Desertification of Iran in the early twenty-first century: assessment using climate and vegetation indices.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed.
- Mapping spatiotemporal variability of vegetation and climate sensitivity in northern Iran using google earth engine.Scientific reports · 2026Article
- Diversity and composition of vegetation and soil seed banks after sand dune restoration by oil mulching and plantations.Scientific reports · 2025Article
- Decline in Iran's groundwater recharge.Nature communications · 2023Article
- Polyethylene Glycol and Sorbitol-Mediated In Vitro Screening for Drought Stress as an Efficient and Rapid Tool to Reach the TolerantPlants (Basel, Switzerland) · 2023Article
- Interrelations of vegetation growth and water scarcity in Iran revealed by satellite time series.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Remote sensing of specific climatic and biogeographical parameters is an effective means of evaluating the large-scale desertification status of drylands affected by negative human impacts. Here, we identify and analyze desertification trends in Iran for the period 2001-2015 via a combination of three indices for vegetation (NPP-net primary production, NDVI-normalized difference vegetation index, LAI-leaf area index) and two climate indices (LST-land surface temperature, P-precipitation). We combine these indices to identify and map areas of Iran that are susceptible to land degradation. We then apply a simple linear regression method, the Mann-Kendall non-parametric test, and the Theil-Sen estimator to identify long-term temporal and spatial trends within the data. Based on desertification map, we find that 68% of Iran shows a high to very high susceptibility to desertification, representing an area of 1.1 million km
Identifiers
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Registered trials
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