| 摘要: |
| 极端高温事件的频发使得优化城市热环境迫
在眉睫。滨水住区作为常见住区类型，其室外热环境
影响因素和改善措施值得关注。既往研究缺乏对地表
要素影响室外热环境的空间异质性考量，难以指导滨
水住区内部具体规划实践。以银川市4 个典型滨水住
区为例，利用无人机采集地表空间数据，并分析其热
环境特征；进而采用线性回归和地理加权回归分析地
表要素与室外热环境的相关性和空间分异特征。研究
表明：地表要素对室外热环境的影响取决于其自身温
度与住区建筑环境条件；产生空间异质性的主要原因
为水体影响、植被遮荫以及车行道路邻接裸露地表。
最后，从住区建筑的退台式形态控制、植被配置中提
升绿化质量与构建隔离带以及开放空间中增加遮荫和
滨水区绿化改造的3 方面提出了滨水住区的室外热环
境优化策略，以期对气候适应性的住区规划设计提供
参考。 |
| 关键词: 滨水住区 低空红外遥感 室外热环境 地
理加权回归 空间分异 |
| DOI：10.13791/j.cnki.hsfwest.20240109003 |
| 分类号: |
| 基金项目:国家自然科学基金项目面上项目（52378066）；宁夏自然科学基金项目（2024AAC03071、2020AAC03046） |
|
| The influence of ground surface factors on the outdoor thermal environment of waterfrontresidential areas and its spatial differentiation characteristics: An empirical study based onfour typical waterfront residential areas in Yinchuan |
|
CHEN Tian,ZUO Minghao,LI Muhan,GU Haozhuo,LIU Jia
|
| Abstract: |
| The intensification of global climate change has resulted in the frequent
occurrence of extreme heat disasters, which seriously affects the production and life of
urban residents, and the optimisation of the urban thermal environment is urgent.
Waterfront settlements, as a common type of settlement, deserve attention for their outdoor
thermal environment influencing factors and improvement measures. Previous studies
lacked the spatial heterogeneity of surface elements affecting the outdoor thermal
environment, which makes it difficult to guide the specific planning practices within
waterfront settlements. In this study, we take four typical waterfront settlements in
Yinchuan City as examples, and collect the impacts of surface space and thermal
environment data using both visible light and infrared remote sensing thermal imaging tools
from unmanned aerial vehicles (UAVs), to study the global correlation between surface
elements and outdoor thermal environment and their spatial heterogeneity in urban
waterfront settlements. In order to explore the spatial differentiation within the settlements
based on the differences between the settlements, and to better compare the results of
different methods and draw more accurate conclusions, the study adopts the Ordinary Least
Squares (OLS) linear regression model, which is widely used in the field of thermal
environment research, and the Geographically Weighted Regression (GWR) model, which
is widely used in the field of thermal environment research. Weighted Regression (GWR)
model, the study firstly determines the optimal statistical grid scale by the significance of
the coefficient of determination of the OLS model and the correlation between each
element and the land surface temperature (LST). Afterwards, the OLS and GWR regression
models were constructed with the area share of each element as the independent variable
and the average LST within the grid as the dependent variable, respectively, to explore the
global impacts of different surface elements on the thermal environment and analyse their
spatial differentiation characteristics in depth, so as to put forward the theoretical support
for the design strategy of waterfront settlements as well as the updating scheme, with a
view to providing scientific guidance for the design of climate-adapted settlements. The
study has the following conclusions: 1) the temperature of trees, shrubs and grassland
elements are low, while the elements of the carriageway are concentrated in high
temperature distribution. 2) the effect of temperature rise and fall of surface elementsdepends on their own temperature and the conditions of the built environment of the settlement. In low-density high-rise settlements, trees, shrubs and grass
elements all have a cooling effect; in terms of warming effect, the element with the strongest effect varies in different settlements, but grass elements all have
the weakest warming effect. 3) The main reasons for the spatial heterogeneity of the influence of surface elements on the outdoor thermal environment of
waterfront settlements are the influence of water bodies, vegetation shading, and the bare surface adjacent to the carriageway. The closer to the water body, the
worse the cooling effect of trees and shrubs and the warming effect of buildings, the shading effect of trees and shrubs can alleviate the warming effect of grass,
pavements and other hard paving elements while cooling, and the direct connection between carriageway and bare surface will enhance the warming effect.
Finally, this study proposes strategies for optimising the outdoor thermal environment of waterfront settlements from three aspects, with a view to informing the
planning and design of climate-resilient settlements. The recommendations are as follows: 1) for the architecture of the settlement, to construct a spatial
environment of high-rise buildings combined with high green coverage, and to form an overall architectural layout of the settlement with a water-facing setback
through the combination of high-rise and low-rise buildings; 2) for the vegetation configuration, to construct a rich combination of trees, shrubs, and grasses
while avoiding the appearance of bare land, and to form a separation zone between the settlement and the surrounding roads through the rich green
configuration; and 3) to provide a green environment of the settlement with a high level of green coverage. In terms of open space, for the large area of hard
pavement in the settlement, the first consideration is to use buildings, greenery, structures and so on to increase the shade to alleviate the high temperature
situation, while for the large area of hard pavement along the waterfront, the cooling effect provided by the shade is limited, and priority can be given to the
pavement greening modification method. |
| Key words: waterfront residential area low-altitude infrared remote sensing outdoor thermal environment geographic weighted regression spatial
differentiation |
