【作者】 董良鹏；

【导师】 江志红； 沈素红；

【作者基本信息】 南京信息工程大学 ， 气象学， 2012， 硕士

【摘要】 随着城市化的快速发展,研究城市化的热岛效应变得日益重要。本文利用MODIS地表温度、地表覆盖类型产品和台站气温观测资料,建立了中国东部城市群地区区域尺度的气温估计模型,得到了高分辨率的长江三角洲地区和京津唐地区的最高气温场,并分析了长江三角洲地区和京津唐地区近十年城市热岛变化及其与城市群发展的关系研究,主要工作如下：1.利用MODIS地表覆盖类型资料和站点气温资料,建立了区域气温估计模型,并对模型做了独立样本检验,结果表明：不同地表覆盖类型下MODIS白天地表温度和站点最高气温间相关性较好,可以利用该关系来估计近地面气温,并得到了高分辨率(1km)的城市群最高气温场；最高气温估计值平均绝对误差在2℃-3℃之间,长江三角洲地区的气温估计模型精度略高于京津唐地区；对上述气温估计模型进行了误差分析,发现地表温度数据精度是气温估计误差的来源之一,经提高后,气温估计值精度有了一定程度的提高,提升幅度在0.5℃以内。2.对2009年长江三角洲地区和2001年京津唐地区基于地表温度和最高气温估计值的热岛的季节变化的研究结果表明,无论是在城市热岛强度还是城市带对区域增温的贡献上看,城市热岛效应都以春夏两季最强,秋季次之,冬季最弱。3.利用长江三角洲地区和京津唐地区2001-2010夏季平均的MODIS地表温度及最高气温估计值,对研究区近十年热状况的变化特征进行了研究,结果表明,自2001年以来,长江三角洲地区夏季白天热岛区的面积不断增长,导致该区域热状况过渡区面积大幅减小。其中强热岛区的范围呈现出快速增长的趋势,各城市群又以苏锡常城市群的增速为最大,该城市群热岛与上海热岛已连成一体成为了大城市群热岛区,并沿海岸线有向杭州湾发展连成更大城市群热岛区的趋势。同时,京津唐地区夏季热岛区的面积也在不断增长,使得城市群内部各城市间热岛连成了一体,并有向其他城市发展的趋势,其中以北京-廊坊-天津城市带最为明显。4.对近十年城市、城郊和乡村地区温度的变化与城市群城市化进程之间的关系的研究表明,长江三角洲地区的温度变化与夜间灯光灰度值的变化的关系密切,城郊地区的温度增温幅度最大,夜间灯光灰度值的加强趋势也最高,乡村次之,城市地区则几乎没有增温,夜间灯光加强趋势也最小,表明温度的精细变化与城市化进程有着相当密切的联系。将近十年京津唐地区温度的变化分布图与夜间灯光灰度值变化的分布图结合起来看,发现城市化变化最大的城郊地区,温度处于明显的上升趋势；乡村和城市中心区城市化基本无变化,而温度也无变化或有微弱的降温趋势,表明了温度变化与城市化进程之间密切的联系。更多还原

【Abstract】 With the rapid urbanization around the globe, the urban heat island (UHI) effects have received considerable attention by scientists. In this paper, high resolution MODIS daytime land surface temperature (LST), MODIS land cover types, DMSP/OLS nighttime light imagery and meteorological stations data were used to estimate the regional surface air temperature. Spatial patterns and variability of UHI over Yangtze River Delta area and Beijing-Tianjin-Tangshan metropolitan area were analized.(1) Based on the remote sensing data from MODIS and ground stations data, a simple statistical model was developed. The accuracy of the model was analyzed. Results show that the linear relationships between MODIS land surface temperature and stations daily maximum air temperature are significant. The2008-2009data was used for the training, and2001-2003data was used for accuracy assessment of the model. It is found that the error (mean absolute error) of the estimated surface air temperature is2℃-3℃. The estimated value has slightly lower error over Yangtze River Delta area than that over Beijing-Tianjin-Tangshan Metropolitan Area. For error analysis, we improve the MODIS land surface temperature data accuracy by using best quality values only, results show that it is successeful to increase the accuracy of the model to about2℃. However, this study has used LST data at all quality levels in develping the statistical model as using best quality data will reduce dramatically the valid data points.(2) By analyzing the seasonal variation of UHI in2009over Yangtze River Delta area and in2001over Beijing-Tianjin-Tangshan Metropolitan Area, results show that the UHI effect observed from the daytime Ts is most significant in the spring and summer; weaker in the autumn, and is not significant in the winter.(3) Analyzing the2001-2010summer MODIS LST and estimaed surface air temperature over Yangtze River Delta area and Beijing-Tianjin-Tangshan Metropolitan Area, we found that during last decade, the heat island areas over the Yangtze River Delta region are increased rapidly, leading to significant decreases in the size of temperature transition region. The strong heat island areas increase fastest, especially in the Suzhou-Wuxi-Changzhou city cluster. The number and size of UHI over the Yangtze River Delta region are grown very fast, connecting each other gradually and forming a giant heat island. At the same time, the heat island areas over Beijing-Tianjin-Tangshan Metropolitan Area region are also increased rapidly, especially in the Beijing-Langfang-Tianjin city cluster.(4) By analyzing the relationship between the change of temperature and the different urbanization area over the study areas, the change of mean temperature is highly correlated to the change of the nighttime lights, the spatial correlation coefficient between mean temperature and nightlight values was high, indicating that the human activity (urbanization) is highly responsible for the local temperature change.更多还原