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Chinthu Naresh on Muck Rack

Chinthu Naresh

As seen in: Taylor & Francis Online
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Articles

Deep learning-driven forecasting of nighttime urban heat patterns in Kolkata: a spatiotemporal approach for climate-resilient city planning

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By Harsh Yadav, Aneesh Mathew, Chinthu Naresh
| Taylor & Francis Online
ABSTRACT Urbanization has intensified land surface temperature (LST) patterns, exacerbated urban heat island (UHI) effects, and posed significant challenges for sustainable city planning. This study investigates long-term LST dynamics (2000–2022) and develops deep learning models to forecast future night-time LST over Kolkata, India. Analysis of the 23-year record reveals a consistent warming trend, with annual mean LST ranging from 18.58°C to 20.32°C and an overall average of 19.48°C.
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