Urban Heat in the Lower Mekong Delta

Urban Heat in the Lower Mekong Delta

Map of LST trends in Bangkok. Grey represents no significant change, green represents significantly increasing trend, and orange represents a significantly decreasing trend.
Map of 30-year LST (Land Surface Temperature) trend in Bangkok. Grey represents no significant change, green represents significantly increasing trend, and orange represents a significantly decreasing trend. Image courtesy of Shams Razzak Rothee and Nishan Kumar Biswas.

By Madeleine Gregory


The Lower Mekong Delta sits in a tropical climate, meaning that its residents are no stranger to heat. This is especially true in four of its major cities—Bangkok, Ho Chi Minh City, Vientiane, and Phnom Penh—where the urban heat island effect raises the temperature even more. As the climate warms, these cities will face greater heat extremes. Researchers Shams Razzak Rothee of the University of Nevada, Las Vegas, and Nishan Kumar Biswas of the University of Maryland Baltimore County (affiliated with NASA Goddard Space Flight Center through GESTAR II) set out to investigate the link between vegetation and land surface temperature in these cities. They used 30 years of Landsat data to analyze how changes in vegetation health (measured by the Enhanced Vegetation Index) impacted land surface temperature. They found that as cities lost vegetation, the land surface temperature increased. 

What is one major takeaway from your research? 

 

Rapid urbanization in the lower Mekong delta’s major cities has fundamentally altered the region’s landscape over the past three decades. As cities expanded, vegetation and water bodies declined substantially, leading to marked increases in land surface temperatures. The research reveals a strong inverse correlation between vegetation health and land surface temperature with a detailed spatiotemporal focus. We found that areas that lost vegetation consistently experienced higher surface temperatures, highlighting the direct environmental impact of urban development in the region.

 

Why did you use Landsat in this work? Did it give you any insight that would have been difficult to get otherwise? 

 

Landsat satellites proved ideal for our research due to their extensive temporal coverage and easy access to analysis-ready products through open-source cloud computing platforms like Google Earth Engine. The dataset allows us to analyze three decades of changes in vegetation cover and land surface temperature. The platform’s high-resolution imagery, multispectral bands, and global coverage provided comprehensive data for our analysis.

 

What are the implications of this work for urban planners in the Lower Mekong Delta?

 

Our research identifies specific areas in major Mekong delta cities that demonstrate the clear inverse relationship between vegetation cover and land surface temperatures. The study also reveals the significant cooling effect of the Mekong River on adjacent areas, suggesting that incorporating green spaces and water bodies into urban planning could effectively mitigate urban heat island effects. These findings have practical implications for local stakeholders and policymakers, offering evidence-based guidance for urban development decisions and environmental policy formulation.

 

Are there any research questions you’re interested in that build off of this work?

 

This research establishes a crucial groundwork for developing comprehensive policy frameworks addressing environmental and urban dynamics. The analytical methodology we’ve developed offers scalability, with potential applications ranging from regional assessments to continent-wide analyses.

 

To advance our understanding, future research initiatives should focus on two primary domains. First, researchers can work on refining the accuracy of satellite data estimation techniques and developing more sophisticated methods for integrating diverse satellite products with ground-based measurements. Second, emerging technologies such as advanced machine learning, artificial intelligence, and causal inference models present promising opportunities to uncover nuanced and precise cause-and-effect relationships between urbanization processes and environmental transformations.

 

By systematically addressing these research directions, we can create more robust, data-driven insights that support informed policy-making and sustainable development strategies in the urban areas.

Map of EVI trends in Bangkok. Grey represents no significant change, green represents significantly increasing trend, and orange represents a significantly decreasing trend.
Map of 30-year EVI (Enhanced Vegetation Index) trend in Bangkok. Grey represents no significant change, green represents a significantly increasing trend, and orange represents a significantly decreasing trend. EVI was found to be inversely correlated to LST in this study. Image courtesy of Shams Razzak Rothee and Nishan Kumar Biswas.

Co-authors: 

 

Shams Razzak Rothee

Ph.D. Candidate, University of Nevada, Las Vegas

 

Nishan Kumar Biswas

Adjunct Faculty, University of Maryland, Baltimore County

Researcher, Goddard Earth Sciences Technology and Research II and Hydrological Sciences Laboratory, NASA Goddard Space Flight Center

 

Rothee, S.R., Biswas, N.K., Sharma, S., Le, M.H. (2025). Analysis of Land Surface Temperature and Vegetation Trends Across Major Lowe Mekong Urban Centers. Geomatica (submitted).
Post Last Updated on January 24, 2025
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