【作者】 李国梁；

【导师】 王伟武；

【作者基本信息】 浙江大学 ， 城市规划与设计， 2010， 硕士

【摘要】 城市热岛效应作为一种城市灾害成为城市热环境恶化的突出表征,给城市大气环境、社会经济发展、人们身心健康所带来的危害不容低估,同时由于城市热岛引起的能源消耗也相当可观。因此,对城市热岛效应进行定性、定量分析研究,有助于改善城市热环境、降低能源消耗、实现城市人居环境的可持续发展。本论文应用遥感和GIS以及数值模拟技术,选取杭州为研究实例,着重分析城市尺度下城市热岛产生与影响机制,以探索城市热岛缓减技术与系统开发作为主要研究内容。选择从城市规划角度去研究城市热岛,将城市规划与城市环境问题结合起来,作为最基本的创新点,为协调城市内部人地系统的均衡发展、最大限度地减少人类活动对城市热环境的影响与破坏提供基本思路,具有理论和实践的双重意义。第一章主要对研究背景和意义进行阐述,分别对对国内外城市热岛相关研究进展综述。发现以往研究城市热岛缓减研究缺乏系统性和综合性,没有明确识别出城市热岛在不同空间尺度下的影响因素,更没有系统提出不同空间尺度下城市热岛的研究方法与缓减策略,研究大都是基于一定的现实基础,就某一方面或领域的深入展开,往往忽视了城市热岛研究的综合性。最后针对本文的研究目的,建立本文研究的技术路线,为后面的研究提供立论基础和思路框架。第二章重点分析多源遥感影像数据Landsat TM/ ETM+、EOS /MODIS、ASTER、NOAA/AVHRR等数据特征,系统归纳每种遥感影像不同波段的光谱特征与分辨率,并阐述了其优缺点,并根据不同遥感数据特点,分别建立一套地表温度、植被指数、土地覆盖分类以及地表反照率等遥感计算方法,为后期数据的选用、遥感影像因子的计算和城市热岛缓减模拟系统因子提取模块提供依据和模型库。第三章应用遥感和GIS技术,揭示了杭州城市热岛的时空变化以及空间分布规律与差异,结果显示：①自1991年以来杭州市区与郊区的年均温呈现上升趋势,城市热岛强度呈显著增大趋势。②建设用地的扩张速率与热岛高温区的增加速率成明显的正相关关系。③城市热岛中心主要分布在工业用地、商业用地以及居住用地密集区域。在前面定量分析研究基础上,深入探讨了城市尺度下城市热岛产生与影响机制,归纳为：①城郊用地向城市建设用地的快速转变是产生城市热岛的本源。②人为热的排放以及空气污染是产生热岛的重要影响因素。③城市空间格局的改变以及自然生态格局的破坏加剧了城市热岛效应。④城市用地性质的差异对城市热岛也有不同程度的影响。针对城市尺度下热岛产生机制,从城市规划角度提出了合理控制城市用地扩展规模与速度、构建开敞的城市生态空间、优化用地功能布局和交通体系、适当降低城市建筑密度等一系列城市热岛效应缓减策略。第四章重点分析中尺度MM5数值模拟模式和城市冠层模式,并以杭州为研究案例,运用数值模式模拟技术,通过改变杭州城市下垫面地面特征参数对气温变化做了模拟研究,结果显示：①水体被替换成城市下垫面后,模拟区域内整体平均气温升高了1.75℃。②植被替换成城市下垫面后,模拟区域内整体平均气温升高了4.26℃。③水体与植被共同被替换成城市下垫面后,模拟区域内整体平均气温升高了6.32℃。④部分城市下垫面被替换成植被后,模拟区域内整体平均温度降低了2.36℃。第五章第一节重点对不同规划地块的地表反照率、NDVI、建筑密度、容积率以及平均高度与地表温度之间的关系进行了深入分析,揭示了：①地表温度与NDVI、地表反照率、平均高度呈负相关关系,而建筑密度、容积率则对地表温度的作用是呈正比。②地表反照率、NDVI和建筑密度对规划地块地表温度的影响与容积率和平均高度两个因子相比更剧烈。③地表温度与NDVI和地表反照率的相关关系最为密切,相关系数分别为0.843和0.829,其次为建筑密度,相关系数分别为0.662,再次为容积率和平均高度,相关系数分别为0.429和0.416。第二节利用移动观测数据,建立一种气温精细化插值方法。利用三角网线性插值、薄条样板插值、最小曲率插值三种方法对移动观测气温数据进行插值研究,插值出精度较高的气温栅格数据,为研究城市热岛分布状况提供了最有价值的气温资料,对提高气温空间化精度更具有现实意义。第六章基于前五章的理论与实例研究,应用IDL语言并借助ENVI二次开发函数库的开发平台,开发出“城区热岛缓减分析与优化系统”,系统主要有四个功能模块组成：数据管理模块,遥感因子提取模块,数据统计与查询模块、分析模拟优化模块。其功能特点包括：①支持多种数据文件格式。②栅格矢量数据叠加功能。③从NOAA、MODIS、Landsat TM/ETM+、ASTER等多源遥感影像数据提取地表温度、NDVI、地表反照率等影响因子信息功能。④实现不同建设用地类型地温查询,包括规划地块地温的最值标定、平均值计算、不同时段地块地温曲线生成、不同地块地温剖面曲线生成。⑤够进行单因子线性拟合分析和多元同归分析等,用户可采用在同一地块同一地段随机采集点数据,采用曲线拟合方式获取地表温度与影响因子关系数据库。⑥气温观测数据精细化插值功能。更多还原

【Abstract】 As an urban disaster, urban heat island effect (UHI) has been highlighted as a symbol of urban thermal environment deterioration, the adverse impacts of UHI on urban atmospheric environment, socio-economic development, people’s physical and mental health cannot be underestimated. It also consumes considerable amount of energy. Therefore, it is helpful to improve the thermal environment, reduce energy consumption, and make urban human settlements development sustainable by analyzing UHI qualitatively and quantitatively. In this thesis, we employ remote sensing, GIS and numerical simulation technology to analyze the generation and impact mechanism of UHI on an urban scale in Hangzhou, and explore the UHI mitigation technology and system development. Therefore, researching UHI from the perspective of urban planning and combining the city planning and urban environmental issues can provide basic ideas for coordinating the relationship between human and land and minimizing impacts from human activities on the urban thermal environment, and thus has important significance both in theory and practice.The first chapter mainly elaborates on the background and significance of the research, and reviews related domestic and foreign literature on urban heat island. We "find that previous studies of urban heat island mitigation lacks systematic and integrated analyses, it does not distinguish the influencing factors of UHI as well as mitigation strategies on different spatial scales The majority of the studies are based on a specific aspect and ignores the comprehensive characteristic of UHI research. Finally, we establish a research framework, aiming to provide theoretical basis for following research.The second chapter focuses on analyzing the characteristics of multi-source remote sensing data such as Landsat TM/ETM+, EOS/MODIS, ASTER, NOAA/AVHRR, categorizing the spectral characteristics and resolution of different band for each remote sensing images, and presenting their advantages and disadvantages. Then, according to different characteristics of remote sensing data, the calculation methods for surface temperature, vegetation index, land cover classification and surface albedo are established respectively,, which provides the basis and model libraries for factor extraction module of UHI mitigation simulation system.Chapter 3, based on RS and GIS technologies, the reveals the spatial and temporal variation of UHI in Hangzhou as well as the differences of spatial distribution. The research results show:①The average annual temperature of urban and suburban areas and UHI intensity have been increased significantly since 1991.②The expansion rate of built-up land is positively correlated with the increase rate of high temperature area.③The center of UHI is mainly distributed in the industrial land, commercial land and residential land-intensive areas. Based on the previous quantitative study, we discussed the mechanism of generation and impact on urban scale. Several conclusions have been drawn as follows:①The source of UHI generation is the rapid conversion of suburban land to urban land.②Anthropogenic heat emissions and air pollution are an important factors for the UHI.③The changes of urban spatial pattern and the destruction of ecological environment aggravate the UHI.④The differences of urban land also have effects on the UHI. Corresponding to these investigated UHI generation mechanisms on urban scale, many mitigation strategis from urban planning point,such as controlling the expansion scale and speed of urban land, constructing urban ecological open space, optimizing land use and transportation system, and appropriately reducing building density of urban are put forward.In chapter 4, the paper mainly analyzes mesoscale numerical model MM5 and the urban canopy model, and simulates the variations of temperature by changing the characteristics of urban land surface parameters in Hangzhou city using numerical model simulation technology. The results show:①The average temperature of the whole simulation region increases by 1.75℃when water is replaced with urban land.②The average temperature of the whole simulation region increases by 4.26℃when vegetation is replaced with urban land.③The average temperature of the whole simulation region increases by 6.32℃when the water and vegetation are all replaced with urban land.④The average temperature of the whole simulation region falls 2.36℃when part of the urban land is replaced by vegetation.In chapter 5, section I analyzes the relationship between surface temperature and land surface albedo, NDVI, building density, floor area ratio and average height of the different planning plots. The results show:①The surface temperature is negatively correlated with NDVI, surface albedo, and the average height, while positively correlated with building density and plot ratio.②Surface albedo, NDVI and the building density have more effects on land surface temperature than plot ratio and average height.③Surface temperature is most closely related with NDVI and surface albedo. The correlation coefficients are 0.843 and 0.829, followed by building density, whose correlation coefficient is 0.662. The last are the plot ratio and average height, whose correlation coefficients are 0.429 and 0.416 respectively. In section II, the paper establishes a fine interpolation of the temperature using mobile observation data, which generates accurate grid temperature data using mobile observe temperature data by the methods of triangulation linear interpolation, thin section sample interpolation and minimum curvature interpolation. This method provides the most valuable temperature data for the study of the distribution of UHI status. And it has more practical significance to improve the spacial accuracy of the temperature.Based on the theories and case studies of the previous five chapters, chapter 6 developes the "Urban Heat Island Mitigation Analysis and Optimization System" by employing IDL language and secondary development of library development platform of ENVI. The system has four main functional modules:data management module, remote sensing factor extraction module, data statistics query module, and analysis of simulation and optimization module. Its features include:①Supporting multiple data file formats.②overlaying raster and vector data.③Extracting information such as surface temperature, NDVI, and surface albedo from remote sensing data:NOAA、MODIS、Landsat TM/ETM+、ASTER, and so on.④Allowing inquiries into surface temperatures of different types of construction land, including demarcating the extreme on plan land, calculating the average temperature, producing the average land temperature curve at different times, producing different temperature profiles curve on different lands.⑤Allowing the single factor analysis and multiple linear regression analysis. Users can use the same block in the same location to collect point data randomly, and use curve fitting method to obtain surface temperature and the impact factor relational database.⑥Fine interpolation function using temperature observation data.更多还原