Zoning Optimization Method of a Riverfront Greenspace Service Function Oriented to the Cooling Effect: A Case Study in Shanghai

Blue-green space commonly provides multiple ecological service functions, especially thermal environment comfort for citizens. The greenspace of the riparian buffers along 22 river channels in Shanghai was selected as the study object, and remote sensing and GIS technologies were used to obtain the quantitative composition and morphological indices of riverfront greenspace and the spatial distribution data of the land surface temperature in the study area. Through BRT modelling and statistical analyses, the interactive correlations among the three aspects, namely, the spatial patterns of riverfront greenspace, their specific functional zoning, and cooling island differentiation characteristics, were explored. The results showed that different river types served for different functional zones of the city, namely, high-density built-up zoning, new urban-growth zoning in built-up areas, suburban areas, and rural areas, and had specific regular patterns of morphosis and service function of riverfront greenspace. These also led to a significant spatial differentiation pattern of cooling intensity levels, which generally appeared in the approximate circle differentiation structure of the cooling island in the city riverfront area. The study further proposed the key factors and corresponding strategies for optimizing the greenspace pattern to strengthen the cooling intensity levels of different river types. This study summarizes the landscape composition paradigm of riverfront greenspaces at the urban mesoscale and provides adaptive planning methods for better local microclimate conditions.

Cooling Island Effect of Blue-Green Corridors: Quantitative Comparison of Morphological Impacts

The patterns of green corridors in urban riverfront districts provide different synergistic cooling effects of blue-green space in urban areas. The purpose of this study is to quantify the spatial morphological impact of green corridors in riverfront block-scale area on the cooling effect. Three representative patterns (radiate, grid and dendritic) were selected in the study. The comprehensive influences analysis between multi-dimensional factors of spatial structure and morphology of green corridors and Ta (air temperature) distribution are processed by Envi-met4.4.5 simulation data and statistical analysis methods, such as regression tree model (BRT), were combined. The results showed that the D (distance from riverbank) has the greatest impact on the cooling effect of each belt green space. The D in the range of 600–750 m was affected by the cooling effect of blue-green space; The orientation with parallel to (southeast–northwest) or roughly the same as the prevailing wind direction (north–south) green corridors had relatively better cooling effect. When the width of green corridor was 20–25 m, the ME (marginal effect) of cooling was the largest; at 30–35 m (corridor width), the overall ME of cooling was the best; When the dPC (decreased probability connectivity, here the index was adapted to describe the connectivity degree) of green corridors was in the range of 0.5–1.5, the cooling effect of green corridor could be significantly improved. When dPC is 1.5, its marginal effect on temperature reached the maximum. The study provided a quantitative correlation technology for the morphological influence of blue-green space on the distribution of UCI (urban cooling island), which can guide the spatial layout control of green corridors in the planning and design of urban riverfront district.

Interaction of Urban Rivers and Green Space Morphology to Mitigate the Urban Heat Island Effect: Case-Based Comparative Analysis

The spatial morphology of waterfront green spaces helps generate cooling effects to mitigate the urban heat island effect (UHI) in metropolis cities. To explore the contribution and influence of multi-dimensional spatial indices on the mitigation of UHIs, the green space of the riparian buffer along 18 river channels in Shanghai was considered as a case study. The spatial distribution data of the land surface temperature (LST) in the study area were obtained by using remote sensing images. By selecting the related spatial structure morphological factors of the waterfront green space as the quantitative description index, the growth regression tree model (BRT) was adapted to analyze the contribution of various indexes of the waterfront green space on the distribution of the LST and the marginal effect of blue–green synergistic cooling. In addition, mathematical statistical analysis and spatial analysis methods were used to study the influence of the morphological group (MG) types of riparian green spaces with different morphological characteristics on the LST. The results showed that in terms of the spatial structure variables between blue and green spaces, the contribution of river widths larger than 30 m was more notable in decreasing the LST. In the case of a larger river width, the marginal effect of synergistic cooling could be observed in farther regions. The green space that had the highest connectivity degree and was located in the leeward direction of the river exhibited the lowest LST. In terms of the spatial morphology, the fractional cover values of the vegetation (Fv) and area (A) of the green space were the main factors affecting the cooling effect of the green space. For all MG types, a large green patch that had a high green coverage and connectivity degree, as well as was distributed in the leeward direction of the river, corresponded to the lowest LST. The research presented herein can provide methods and development suggestions for optimizing spatial thermal comfort in climate adaptive cities.

Comparative Study on the Cooling Effects of Green Space Patterns in Waterfront Build-Up Blocks: An Experience from Shanghai

Different structural patterns of waterfront green space networks in built-up areas have different synergistic cooling characteristics in cities. This study’s aim is to determine what kinds of spatial structures and morphologies of waterfront green spaces offer a good cooling effect, combined with three different typical patterns in Shanghai. A multidimensional spatial influence variable system based on the cooling effect was constructed to describe the spatial structural and morphological factors of the green space network. The ENVI-met 4.3 software, developed by Michael Bruse at Bochum, German, was used to simulate the microclimate distribution data, combined with the boosted regression tree (BRT) model and the correlation analysis method. The results showed that at the network level, the distance from the water body and the connectivity of green space had a stronger cooling correlation. The orientation of green corridors consistent with a summer monsoon had larger cooling effect ranges. In terms of spatial morphology, the vegetation sky view factor (SVF) and Vegetation Surface Albedo (VS_Albedo) had an important correlation with air temperature (T), and the green corridor with a 20–25 m width had the largest marginal effect on cooling. These results will provide useful guidance for urban climate adaptive planning and design.