Relationship between urban form and surface temperature based on XGBoost SHAP interpretable machine learning model

With the increase of high-rise buildings in major cities worldwide, exploring the effects of urban two-dimensional (2D) and three-dimensional (3D) morphology on land surface temperature (LST) has become the key to mitigating the urban thermal environment and optimizing urban planning. Using the area...

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Vydané v:	Ying yong sheng tai xue bao Ročník 36; číslo 3; s. 659
Hlavní autori:	Tan, Jie, Wei, Qian-Jun, Liao, Zhao-Yang, Kuang, Wen-Jun, Deng, Hui-Ting, Yu, De
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	China 18.03.2025
Predmet:	Boosting Machine Learning Algorithms China Cities City Planning Environmental Monitoring - methods Machine Learning Models, Theoretical Remote Sensing Technology Temperature Urbanization China XGBoost-SHAP model urban 2D/3D form urban heat island effect explainable machine learning
ISSN:	1001-9332
On-line prístup:	Zistit podrobnosti o prístupe
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