MSPA-based green space morphological pattern and its spatiotemporal influence on land surface temperature

Area of Science:

• Urban Climatology
• Environmental Science
• Geographic Information Science

Background:

• Extreme heat events pose significant risks to human well-being and urban environments.
• Green spaces are recognized for their cooling potential, but their specific effects on land surface temperature (LST) require detailed investigation.
• The spatiotemporal dynamics of how different green space configurations influence LST remain largely unexplored.

Purpose of the Study:

• To investigate the spatiotemporal effects of various green space patterns on land surface temperature (LST).
• To identify which green space patterns (e.g., core, edge, islet) are most effective in mitigating urban heat.
• To provide insights for optimizing urban green space planning and design for thermal regulation.

Main Methods:

• Morphological Spatial Pattern Analysis (MSPA) was employed to classify green space patterns.
• Geographically and Temporally Weighted Regression (GTWR) and two other models were used to analyze the relationship between green space patterns and LST across different time periods.
• The study analyzed the spatial heterogeneity of these effects within the study area.

Main Results:

• The Geographically and Temporally Weighted Regression (GTWR) model demonstrated superior performance in capturing the complex relationships.
• Core, edge, bridge, and branch green space patterns generally contributed to cooling, while islets exacerbated heat.
• Perforation and loop patterns exhibited dual effects, indicating complex impact mechanisms, and the intensity of cooling varied spatially, with the core pattern having the most substantial effect.

Conclusions:

• Green space morphology significantly influences urban land surface temperature, with distinct patterns having varied cooling or heating effects.
• A neighborhood scale of 960m is suggested as a fundamental unit for green space management in urban areas.
• Accounting for the spatiotemporal non-stationarity of green space pattern effects is vital for effective urban thermal environment management and planning.