Spatial Pattern of Environmental Vulnerability in Iran

جغرافیا و مخاطرات محیطی

Article 1, Volume 13, Issue 3 - Serial Number 51, November 2024, Pages 1-34   

Document Type: Research Article

DOI: 10.22067/geoeh.2023.84603.1417

Authors

Habib Alla Sadeghi^{* 1}; Afshin Danehkar^{* 2}; Mohammad Jalal Abbasi-Shavazi^{3, 4, 5}

¹PhD scholar in Demography, Department of Demography, Faculty of Social Sciences, University of Tehran, Tehran, Iran .

²Professor in Environmental Science, Natural Resources Faculty, University of Tehran, Karaj, Iran .

³Academy Fellow, Vienna Institute of Demography, Austria.

⁴Professor in Demography, Faculty of Social Sciences, University of Tehran, Tehran, Iran .

⁵Honorary Professor, School of Demography, Australian National University, Canberra, Australia

Abstract

A deeper understanding of environmental vulnerability is essential for crafting effective sustainability strategies. However, data deficiencies and methodological uncertainties often obscure a comprehensive grasp of the underlying issues. This study employs Google Earth Engine (GEE)-coded satellite imagery and the Getis spatial autocorrelation test to examine spatial patterns of environmental vulnerability in 397 Iranian counties from 2011 to 2021, framed within the theoretical lens of vulnerability.
The results of the Getis test reveal heterogeneous distributions and diverse vulnerability patterns across Iranian counties in various dimensions, including air pollution, greenhouse gas emissions, changes in temperature and precipitation, groundwater depletion, biodiversity threats, and soil erosion, particularly in the central, southern, eastern, and northern regions. Emphasizing the role of distinct spatial patterns in terms of "sensitivity" and "exposure," this research suggests that environmental policies in Iran should be tailored to regional spatial disparities and socio-ecological characteristics.
This approach can enhance adaptive capacity and mitigate environmental vulnerability in critical areas. The use of algorithmic techniques for environmental vulnerability indexing, combined with spatial data and population analysis, provides a robust framework for future research. This framework can be applied in national and regional planning to alleviate environmental pressures and improve sustainability.

Keywords

Environmental Vulnerability; Google erarth Engine(GEE); Spatial Autocorrolation; Sustainability Strategies; Regional Disparities; Adaptive Capacity

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