The Heat Price of Big Data: Leveraging Machine Learning to Analyze the Urban Heat Effects of Data Center Alley in Washington D.C.'S Hinterlands

Since the early 2000s, Ashburn, a satellite city to DC, has urbanized rapidly and has turned into a “Data Center Alley.” Approximately 70 % of internet traffic passes through the region. The data centers have led to an increase in the Urban Heat Island (UHI) effect, which impacts the local environment. This study aims to quantify the extent of the UHI effect and the key causes of the side effects. Satellite data was analyzed through various statistical methods and comparisons and various regions of interest were considered. Additionally, machine learning techniques were applied for downscaling the Land Surface Temperature (LST) data for the purpose of understanding the temperature distribution in a finer detail. The analysis yields that there has been a significant increase in LST, particularly in areas near data centers. This research highlights the urgent need to regulate urbanization and data centers for environmental sustainability. The environmental impact of recent technological innovation and urban development has raised temperatures and destroyed crucial green land that helps combat climate change.

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Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1109/geoinformatics67279.2025.11173558
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
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article

The Heat Price of Big Data: Leveraging Machine Learning to Analyze the Urban Heat Effects of Data Center Alley in Washington D.C.'S Hinterlands

Jason Zhang
Air Quality Monitoring and Forecasting
article

The Heat Price of Big Data: Leveraging Machine Learning to Analyze the Urban Heat Effects of Data Center Alley in Washington D.C.'S Hinterlands

Jason Zhang
article en

Abstract

Since the early 2000s, Ashburn, a satellite city to DC, has urbanized rapidly and has turned into a “Data Center Alley.” Approximately 70 % of internet traffic passes through the region. The data centers have led to an increase in the Urban Heat Island (UHI) effect, which impacts the local environment. This study aims to quantify the extent of the UHI effect and the key causes of the side effects. Satellite data was analyzed through various statistical methods and comparisons and various regions of interest were considered. Additionally, machine learning techniques were applied for downscaling the Land Surface Temperature (LST) data for the purpose of understanding the temperature distribution in a finer detail. The analysis yields that there has been a significant increase in LST, particularly in areas near data centers. This research highlights the urgent need to regulate urbanization and data centers for environmental sustainability. The environmental impact of recent technological innovation and urban development has raised temperatures and destroyed crucial green land that helps combat climate change.

Thomas Jefferson School of Law (US)
Openalex Percentile: Top 76%
Air Quality Monitoring and Forecasting
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The Heat Price of Big Data: Leveraging Machine Learning to Analyze the Urban Heat Effects of Data Center Alley in Washington D.C.'S Hinterlands — Jason Zhang · (2025) | TGRS Research Map | TGRS