A geospatial and statistical assessment of surface temperature response to land cover change and spatial drivers in Sekondi-Takoradi, Ghana

Rapid urbanization is profoundly transforming land use and surface thermal environments in West African cities, with implications for urban heat island (UHI) intensification and climate resilience. Unfortunately, the influence of urban growth and spatial determinants on surface temperature variability remains underexplored in Sekondi–Takoradi and across Ghana. This research addresses this gap by employing geospatial techniques and statistical models to assess the influence of land cover change and spatial drivers on temperature distribution in the Sekondi-Takoradi Metropolis. Landsat images were classified using the random forest algorithm to map LULC transitions, while spectral indices, land surface temperature (LST), elevation, and proximity variables were employed to assess the spatial thermal dynamics. Statistical modeling combined Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) to evaluate the relationships between LST and explanatory variables, and urban archetype analysis was applied to examine the role of spatial drivers on temperature variability. The findings revealed a 32.91% expansion of built-up, a 1.09% decline in water, and a 32.82% decline in vegetation cover, leading to a 3.1 °C rise in mean LST. Regression results showed that GWR consistently outperformed OLS, highlighting the importance of spatial heterogeneity in explaining urban thermal dynamics. The distinct spatial factors defining each class revealed that archetype 6 recorded the lowest mean temperature, whereas archetype 1 exhibited the highest. These results highlight the dominant role of urban growth and spatial drivers in shaping UHI intensification. The study provides critical insights for sustainable land use planning, urban greening, and climate-sensitive infrastructure development, offering policy-relevant evidence to support Sustainable Development Goal 11 on sustainable cities and communities.快速城市化正深刻改变西非城市的土地利用格局与地表热环境，进而加剧城市热岛（UHI）效应并对气候韧性造成影响。遗憾的是，针对塞康第-塔科拉迪地区乃至整个加纳，城市扩张及其空间决定因子对地表温度变异性的影响仍未得到充分探索。本研究针对这一研究空白，采用地理空间技术与统计模型，评估塞康第-塔科拉迪都会区的土地覆盖变化与空间驱动因子对温度分布的影响。本研究通过随机森林算法对Landsat影像进行分类，以绘制土地利用/土地覆盖（LULC）变化图谱；同时借助光谱指数、地表温度（LST）、海拔与邻近性变量，解析空间热动态特征。统计建模环节结合普通最小二乘法（OLS）与地理加权回归（GWR），探究地表温度与各解释变量间的关联；同时采用城市原型分析方法，检验空间驱动因子对温度变异性的作用机制。研究结果显示，建成区面积扩张32.91%，水域面积缩减1.09%，植被覆盖减少32.82%，由此导致平均地表温度上升3.1℃。回归分析结果表明，地理加权回归（GWR）的表现始终优于普通最小二乘法（OLS），凸显了空间异质性在解析城市热动态过程中的重要性。不同城市原型类别的关键空间因子存在显著差异，其中原型6的平均温度最低，而原型1的平均温度最高。上述结果凸显了城市扩张与空间驱动因子在加剧城市热岛（UHI）效应过程中的主导作用。本研究可为可持续土地利用规划、城市绿化与气候适应性基础设施建设提供关键见解，可为落实可持续发展目标11（可持续城市和社区）提供政策相关的实证依据。