Back to Search Start Over

Environmental Conditions in Middle Eastern Megacities: A Comparative Spatiotemporal Analysis Using Remote Sensing Time Series.

Authors :
Mohammadi, Shahin
Saber, Mohsen
Amini, Saeid
Mostafavi, Mir Abolfazl
McArdle, Gavin
Rabiei-Dastjerdi, Hamidreza
Source :
Remote Sensing. Nov2022, Vol. 14 Issue 22, p5834. 21p.
Publication Year :
2022

Abstract

Rapid and timely evaluation and monitoring of the urban environment has gained significant importance in understanding the state of urban sustainability in metropolises. Multi-source remote sensing (RS) data are a valuable source for a comprehensive understanding of urban environmental changes in developing countries. However, in the Middle East, a region with several developing countries, limited study has been conducted to understand urban environmental changes. In this study, to evaluate the changes in the urban environment, 32 metropolises in the Middle East were studied between 2000 and 2019. For this purpose, a comprehensive environmental index (CEI) integrated with Google Earth Engine (GEE) platform for processing and analysis is introduced. The results show degraded environmental conditions in 19 metropolises based on a significant increasing trend in the time series of the CEI index. The highest increasing trend in the value of the CEI was observed in the cities of Makkah, Jeddah, Basra, Riyadh, and Sana'a. The results also show that the percentage of urban areas in all 32 cities that falls into the degraded class varies from 5% to 75% between 2005 and 2018. The results of CEI changes in megacities, such as Ajman, Tehran, Jeddah, Makkah, Riyadh, Karaj, and Sana'a show that these cities have increasingly suffered from the degradation of environmental conditions since 2001. According to the results, it is recommended to pay more attention to environmental issues regarding the future of urban development in these cities. The proposed approach in this study can be implemented for environmental assessment in other regions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
14
Issue :
22
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
160465503
Full Text :
https://doi.org/10.3390/rs14225834