Exploring the relationship between leisure walking and the built environment will provide an improvement in human health and well-being. It is, therefore, necessary to explore the most relevant scale for leisure walking and how the association between the built environment and leisure walking varies across scales. Three hundred volunteers were recruited to wear GPS loggers, and a total dataset of 268 tracks from 105 individuals was collected. The shortest possible routes between starting and ending points were generated and compared to the actual routes using the paired T-test. An improved grid-based buffer approach was proposed, and statistics for the grid cells intersecting the paths were calculated. Grid cells were calculated for six scales: 50 m, 100 m, 200 m, 500 m, 800 m, and 1600 m. The results showed that the actual paths were on average 24.97% longer than the shortest path. The mean, standard deviation, and minimum and maximum values of the built environment variables were all significantly associated with leisure walking. The most relevant spatial scale was found to be the 100 m scale. Overall, the smaller the scale, the more significant the association. Participants showed a preference for moderately compact urban forms, diverse options for destinations, and greener landscapes in leisure walking route choice.

Spatial planning, recognized as a systematic policy instrument for regional development and governance, plays a crucial role in achieving carbon peak and carbon neutrality. This study establishes a framework for carbon sources/sinks estimation and carbon compensation optimization and conducts empirical research in a representative coal resource-based city. We analyzed the spatial–temporal distribution characteristics of net carbon emissions in Huaibei from 2006 to 2020 using a spatial correlation model and an improved Carnegie–Ames–Stanford approach (CASA). Then, we applied the normalized revealed comparative advantage (NRCA) index and the SOM-K-means clustering model to categorize the carbon pattern into payment, balance, and compensation areas. These areas were further integrated with the “Three-zones and Three-lines” to reclassify nine spatial partition optimization types. Finally, we proposed a targeted emission reduction and sink enhancement optimization scheme. We found that urban carbon emissions and carbon sinks exhibit a significant mismatch, with the net carbon emission intensity reaching 166.76–383.27 t·hm⁻² from 2006 to 2020, showing a rapid increase followed by stabilization. The high-value area, centered in Xiangshan District, exhibits a circularly decreasing spatial characteristic, gradually extending to the central city of Suixi County. In the optimized payment area, the level of the carbon emission contributive coefficient surpasses the ecological support coefficient (3.92 < ECC < 6.04, 2.09 < ESC < 3.58). The optimized space in the balance area type is primarily situated in mining subsidence areas, leading to a lower overall level (0.42 < ECC < 0.57, 0.49 < ESC < 1.13). The optimized space in the compensation area type (2.24 < ECC < 3.25, 4.59 < ESC < 5.69) requires economic or non-economic compensation from the payment area. The study combines the “Three-zones and Three-lines” with the results of carbon compensation to formulate an urban emission reduction and sink enhancement program, which not only helps to consolidate the theory of low-carbon cities but also effectively promotes the realization of the regional carbon peak goal.