ORIGINAL RESEARCH article
Front. Environ. Sci.
Sec. Environmental Informatics and Remote Sensing
Volume 13 - 2025 | doi: 10.3389/fenvs.2025.1634243
GEE-Based Analysis of Spatiotemporal Patterns of Land Cover and LST in an Arid Urban Environment A Case Study of Abu Dhabi
Provisionally accepted
- 1Geography and Urban Sustainability Department, College of Humanities & Social Sciences, UAE University, Al Ain, United Arab Emirates
- 2Mississippi State University Department of Wildlife Fisheries and Aquaculture, Mississippi State University, United States
- 3University of Tartous, Tartus, Syria
- 4United Arab Emirates University Department of Geography and Urban Sustainability, Al Ain, United Arab Emirates
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Urban expansion and land cover changes significantly influence land surface temperature (LST), especially in arid environments. This study investigates spatial and temporal patterns of land cover and LST across Abu Dhabi, UAE, for the benchmark years 2017, 2020, and 2024, using Sentinel-2 imagery and MODIS thermal data via Google Earth Engine (GEE). Four dominant land cover classes were mapped: bare desert, urban areas, vegetation, and water bodies. Between 2017 and 2024, bare desert coverage declined from 92.8% to 90.9%, while urban land grew from 3.0% to 4.5%, vegetation increased from 3.3% to 4.1%, and water decreased from 0.9% to 0.5%. Thermal analysis based on MODIS summer composites revealed that 2020 was the hottest year, with an average LST of 53.14 °C, higher than 2017 (52.40 °C) despite COVID-19 mobility restrictions, likely due to extreme heat and atmospheric conditions. These values reflect emirate-wide averages, aggregated across all land cover types. By 2024, average LST declined to 48.76 °C, coinciding with expanded vegetation and milder summer temperatures. The observed 3.6 °C reduction may reflect both climatic moderation and land cover transformations. LST comparisons across land cover types showed a consistent thermal hierarchy: bare desert exhibited the highest surface temperatures, followed by urban areas, vegetation, and water bodies. These results highlight the cooling role of green infrastructure in hyper-arid cities. The findings contribute to Sustainable Development Goals (SDGs) 11, 13, and 15 by providing geospatial insights for sustainable land management and urban climate resilience.
Keywords: land cover, land surface temperature (LST), Google Earth Engine (GEE), Urbanheat island (UHI), remote sensing, Arid environments, Abu Dhabi, Sustainable UrbanDevelopment
Received: 23 May 2025; Accepted: 29 Sep 2025.
Copyright: © 2025 S. Ramadan, Tariq, Abdo and Al Hosani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Mona S. Ramadan, mona.s.ramadan@uaeu.ac.ae
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.