Nonlinear Effects of Human Settlements on Seasonal Land Surface Temperature Variations at the Block Scale: A Case Study of the Central Urban Area of Chengdu DOI Creative Commons

Muze Zhang,

Tong Hou, Yuping Ma

et al.

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 693 - 693

Published: March 25, 2025

The land surface temperature (LST) in the central urban area has shown a consistent upward trend over years, exacerbating heat island (SUHI) effect. Therefore, this study focuses on of Chengdu, using blocks as research scale. Gradient Boosting Decision Tree (GBDT) model and SHAP values are employed to explore nonlinear effects human settlements (HS) LST across different seasons. results show that (1) At block scale, overall impact HS all four seasons tracks following order: built environment (BE) > landscape pattern (LP) socio-economic development (SED). (2) LP is most important factor affecting summer, while BE greatest influence during spring, autumn, winter. (3) Most indicators exhibit seasonal variations their LST. impervious (ISA) exhibits significant positive autumn. In contrast, nighttime light index (NTL) functional mix degree (FMD) exert negative Additionally, normalized difference vegetation (NDVI) negatively affects both spring summer. Moreover, connectivity (CNT) density (FPD) demonstrate notable threshold (4) Certain interaction effects, some combinations these can effectively reduce This reveals HS–LST interactions through multidimensional analysis, offering block-scale planning strategies for sustainable thermal optimization.

Language: Английский

Nonlinear Effects of Human Settlements on Seasonal Land Surface Temperature Variations at the Block Scale: A Case Study of the Central Urban Area of Chengdu DOI Creative Commons

Muze Zhang,

Tong Hou, Yuping Ma

et al.

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 693 - 693

Published: March 25, 2025

The land surface temperature (LST) in the central urban area has shown a consistent upward trend over years, exacerbating heat island (SUHI) effect. Therefore, this study focuses on of Chengdu, using blocks as research scale. Gradient Boosting Decision Tree (GBDT) model and SHAP values are employed to explore nonlinear effects human settlements (HS) LST across different seasons. results show that (1) At block scale, overall impact HS all four seasons tracks following order: built environment (BE) > landscape pattern (LP) socio-economic development (SED). (2) LP is most important factor affecting summer, while BE greatest influence during spring, autumn, winter. (3) Most indicators exhibit seasonal variations their LST. impervious (ISA) exhibits significant positive autumn. In contrast, nighttime light index (NTL) functional mix degree (FMD) exert negative Additionally, normalized difference vegetation (NDVI) negatively affects both spring summer. Moreover, connectivity (CNT) density (FPD) demonstrate notable threshold (4) Certain interaction effects, some combinations these can effectively reduce This reveals HS–LST interactions through multidimensional analysis, offering block-scale planning strategies for sustainable thermal optimization.

Language: Английский

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