【作者】 宋涛；

【导师】 黄晓军；

【作者基本信息】 西北大学 ， 城市规划硕士（专业学位）， 2022， 硕士

【摘要】 近年来,全球变暖现象日益加剧,极端高温事件不断增多,由于高度城市化导致的蓝绿空间减少、城市下垫面硬质化等原因进一步加剧了城市热环境恶化。极端高温会诱发中暑、热射病及心脑血管疾病等,对人类健康与生产生活造成了极大威胁。因此,采用适应性规划理念,进行城市公共纳凉场所体系规划,提高居民应对极端高温灾害能力具有重要现实意义。本文以西安市为例,在分析西安市高温热浪时空演变特征的基础上,以问卷调查的形式,获取居民在高温热浪期间适应高温的行为选择及纳凉需求,进而对西安市潜在公共纳凉场所数量特征与空间分布进行分析,并以西安市碑林区为例,基于可达性原理,通过位置分配方法进行公共纳凉场所空间布局优化,最后,提出城市公共纳凉场所体系规划对策。主要结论如下:(1)西安市1960—2018年高温热浪灾害呈现波动变化,近年来高温日数、高温强度、热浪频次、热浪持续时间及热浪强度指标呈现上升的趋势。近59年来西安市高温日数呈现波动上升的趋势,59年间共计出现高温日数1402天;高温强度于2017年达到最高值,为38.18℃,1984年达到最低值,为35.49℃;热浪频次呈现波动强烈变化,59年间累计高温热浪频次为206次;59年间高温热浪总持续天数为950天;热浪强度呈现两端高中间低的趋势,于20世纪80年代出现最低值。(2)西安市地表温度较高的地区主要集中在人口密集的居住区及部分工业园区,地表温度较低的区域主要分布在渭河、灞河、公园绿地等蓝绿空间占比较高的区域。研究区内,不同等级地表温度的面积占比依次为中温区(33.84%)>较高温度区(26.25%)>较低温区(24.68%)>低温区(7.67%)>高温区(7.56%)。整体来看,西安市北部、中部地表温度高于南部,高温区主要分布在火车站、工业园区、经开区、商业中心等,低温区则主要分布在高新区、曲江新区及长安区大学城等地,河流和公园绿地也呈现低温特征。(3)西安市大部分区域处于人口高温暴露的低风险区。从空间格局来看,人口高温暴露风险高值呈“点状”分布在中心城区内商业设施聚集和人口密集的地区;人口暴露风险低值主要位于城市边缘地带,区域内绿地、水体相对较多,同时与人口密度低值区高度吻合。各等级人口高温暴露风险区面积占比从大到小依次为低风险区(65.10%)>较低风险区(19.65%)>中等风险区(9.95%)>较高风险区(4.23%)>高风险区(1.08%),各等级老年人口高温暴露风险区面积从大到小占比依次为低风险区(73.59%)>较低风险区(15.79%)>中等风险区(7.29%)>较高风险区(2.79%)>高风险区(0.54%)。从不同市辖区人口高温暴露风险面积占比来看,灞桥区、未央区、雁塔区及长安区均以较低风险区面积占比最大,而碑林区、莲湖区及新城区中等风险区及以上面积占比之和均超过30%,进一步验证了人口高温暴露风险高值位于城市中心区,而城市外围人口高温暴露风险较低。(4)西安市主城区潜在公共纳凉场所空间整体分布呈现中心圈层—外围组团的特征,空间分布不平衡,主要表现为两个方面:一是中心集聚,外围稀疏。由中心向外围,随着空间距离的增加,潜在公共纳凉场所的数量逐渐减少;二是主城区及外围呈现圈层式分布,以碑林区、莲湖区、新城区、雁塔区为核心向外衰减,外围城区出现多个小规模组团,研究区潜在公共纳凉场所空间分布呈现空间集聚特征。(5)西安市碑林区潜在公共纳凉场所可达性分析结果显示,可达性高值位于长安街两侧,碑林区东西部社区公共纳凉场所可达性较低。随着出行时间增加,公共纳凉场所服务覆盖范围增大,居民可选择的场所机会也不断增加,在5min内共有29个社区无法步行抵达公共纳凉场所,而在15min情况下,各社区均能步行抵达。随着时间距离增加,不同时间阈值间可达性值范围不断缩减,社区可达性空间差异有所减少,空间平滑程度提升。(6)根据碑林区公共纳凉场所可达性分析结果,通过位置分配的原理,运用最小化设施点数模型和最大化覆盖范围模型两种方法,提出两种公共纳凉场所空间布局优化方案。最小化设施点数模型结果显示,从候选的134处公共纳凉场所中,选取22个即可满足任意社区15min内步行可抵达公共纳凉场所,其中3处为新增点,平均路程耗时8.25min。最大化覆盖范围模型结果显示,从候选的134处公共纳凉场所中,选取70个点即可满足公共纳凉场所的最大覆盖范围,其中13处为新增点,平均路程耗时4.44min。(7)为提高城市抵御高温灾害风险能力,提出城市公共纳凉场所体系规划对策,包括以人为本的规划原则、分层控制的规划编制、多元参与的运营机构、动态调整的规划流程、智慧系统的信息宣传。更多还原

【Abstract】 In recent years,the phenomenon of global warming has intensified,and extreme high temperature events have continued to increase.Due to the reduction of blue and green spaces caused by high urbanization,the hardening of urban underlying surfaces has further aggravated the deterioration of urban thermal environment.Extremely high temperature can induce heat stroke,heat stroke and cardiovascular and cerebrovascular diseases,posing a great threat to human production and life.Therefore,it is of great practical significance to adopt the concept of adaptive planning,carry out the system planning of urban cooling center,and improve the ability of residents to cope with extreme high temperature disasters.Taking Xi’an as an example,based on the analysis of the temporal and spatial evolution characteristics of high temperature and heat waves in Xi’an,this paper uses a questionnaire survey to obtain the behavior choices and cooling needs of residents adapting to high temperature during high temperature and heat waves,and then to determine the number of potential public cooling centers in Xi’an.This paper analyzes the characteristics and spatial distribution,and takes Beilin District of Xi’an as an example to optimize the spatial layout of public cooling centers based on location allocation based on the community life circle.Through the above research,the main conclusions are as follows:(1)The high temperature and heat wave disasters in Xi’an from 1960 to 2018 showed fluctuations.In recent years,the number of high temperature days,high temperature intensity,heat wave frequency,heat wave duration and heat wave intensity indicators showed an upward trend.In the past 59 years,the number of high-temperature days in Xi’an has shown a fluctuating upward trend.In the past 59 years,there have been 1402 high-temperature days.The high-temperature intensity reached the highest value of 38.18°C in 2017 and the lowest value of 35.49°C in 1984.The frequency of heat waves fluctuated strongly.The cumulative frequency of high temperature and heat waves in 1959 was 206;the total duration of high temperature and heat waves in 1959 was 950 days;the intensity of heat waves showed a trend of high at both ends and low in the middle,with the lowest value in the 1980 s.(2)The areas with high surface temperature in Xi’an are mainly concentrated in densely populated residential areas and some industrial parks,and the areas with low surface temperature are mainly distributed in areas with a high proportion of blue-green space such as Weihe River,Bahe River,and park green space.In the study area,the area proportions of different levels of surface temperature are in the order of medium temperature area(33.84%)>higher temperature area(26.25%)> lower temperature area(24.68%)> low temperature area(7.67%)> high temperature area(7.56%).On the whole,the surface temperature in the northern and central parts of Xi’an is higher than that in the southern part.The hightemperature areas are mainly distributed in railway stations,industrial parks,economic development zones,and commercial centers,while the low-temperature areas are mainly distributed in the High-tech Zone,Qujiang New District and Chang’an University In cities and other places,rivers and parks also exhibit low temperature characteristics.(3)Most of Xi’an is in a low-risk area where the population is exposed to high temperature.From the perspective of the spatial pattern,the high risk of population exposure to high temperature is distributed in “point-like” areas in the central urban area where commercial facilities are concentrated and densely populated;the low risk of population exposure is mainly located in the urban fringe,where there are relatively more green spaces and water bodies,and is highly consistent with the low-value area of population density.The proportion of high-temperature exposure risk areas of all levels of population in descending order is low-risk area(65.10%)> lower-risk area(19.65%)> medium-risk area(9.95%)> higherrisk area(4.23%)> High-risk areas(1.08%),and the proportion of high-temperature exposure risk areas for the elderly at all levels in descending order is low-risk areas(73.59%)>lower-risk areas(15.79%)> medium-risk areas(7.29%)> Higher risk area(2.79%)> high risk area(0.54%).From the perspective of the proportion of high temperature exposure risk areas in different municipal districts,Baqiao District,Weiyang District,Yanta District and Chang’an District all have the largest proportion of low-risk areas,while Beilin District,Lianhu District and Xincheng District are medium-risk areas.The sum of the proportions of the areas above and above is more than 30%,which further verifies that the high risk of high temperature exposure of the population is located in the central area of the city,while the risk of high temperature exposure of the population outside the city is lower.(4)The overall spatial distribution of potential public cooling centers in the main urban area of Xi’an presents the characteristics of central circles and peripheral clusters,and the spatial distribution is unbalanced,which is mainly manifested in two aspects: first,the center is concentrated and the periphery is sparse.From the center to the periphery,with the increase of spatial distance,the number of potential public cooling centers gradually decreases;second,the main urban area and its periphery are distributed in a circle,with Beilin District,Lianhu District,Xincheng District and Yanta District as the core and outwards.Attenuation,there are many small-scale groups in the outer urban area,and the spatial distribution of potential public cooling centers in the study area presents the characteristics of spatial aggregation.(5)The accessibility analysis results of potential public cooling centers in Beilin District of Xi’an show that the high accessibility values are located on both sides of Chang’an Avenue,and the accessibility of public cooling centers in the eastern and western communities of Beilin District is low.With the increase of travel time,the coverage of public cooling centers increases,and the opportunities for residents to choose places are also increasing.A total of29 communities cannot walk to public cooling centers within 5 minutes,but within 15 minutes,all communities can walk arrival.As the time distance increases,the range of accessibility values between different time thresholds continues to shrink,the spatial difference in community accessibility decreases,and the spatial smoothness improves.(6)According to the analysis results of the accessibility of public cooling centers in Beilin District,through the principle of location allocation,two methods of minimizing the number of facility points and maximizing the coverage model are used to propose two optimization schemes for the spatial layout of public cooling centers.The results of the minimization facility point model show that from the 134 candidate public cooling centers,22 points can be selected to satisfy any community within 15 minutes of walking to reach the public cooling centers,of which 3 are new points,and the average journey time is 8.25 minute.The results of the maximizing coverage model show that from the 134 candidate public cooling centers,70 points can be selected to meet the maximum coverage of public cooling centers,of which 13 are new points,and the average travel time is 4.44 minutes.(7)In order to improve the city’s ability to resist high temperature disaster risks,this paper proposes urban public cool place system planning strategies,including people-oriented planning principles,hierarchical control planning,multi-participation operating agencies,dynamic adjustment planning process,and intelligent system information publicity.更多还原