Modeling and Estimating the Land Surface Temperature (LST) Using Remote Sensing and Machine Learning (Case Study: Yazd, Iran)

Modeling and Estimating the Land Surface Temperature (LST) Using Remote Sensing and Machine Learning (Case Study: Yazd, Iran)

The pressing issue of global warming is particularly evident in urban areas, where urban thermal islands amplify the warming effect. Understanding land surface temperature (LST) changes is crucial in mitigating and adapting to the effect of urban heat islands, and ultimately addressing the broader c...

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Bibliographic Details
Main Authors:	Mohammad Mansourmoghaddam, Iman Rousta, Hamidreza Ghafarian Malamiri, Mostafa Sadeghnejad, Jaromir Krzyszczak, Carla Sofia Santos Ferreira
Format:	Article
Language:	English
Published:	MDPI AG 2024-01-01
Series:	Remote Sensing
Subjects:	land surface temperature modeling land surface parameters machine learning gradient boosting method
Online Access:	https://www.mdpi.com/2072-4292/16/3/454

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