城市下垫粗糙特性面时空演变规律遥感监测及其对风场的影响

发布时间：2018-05-06 02:20

本文选题：雷达遥感 + 城市　；参考：《中国科学院大学(中国科学院遥感与数字地球研究所)》2017年硕士论文

【摘要】：城镇是人类对气候变化影响最深刻、最集中的区域。随着城镇化的快速发展,出现了气候变暖、气象灾害频发、生态失衡、空气污染等一系列气象灾害和生态环境问题。综合利用多种遥感数据可以监测快速城镇化过程中下垫面演变的时空特征及其对气候环境要素的影响,因此,本文综合利用夜晚灯光数据、散射计数据和合成孔径雷达数据,以两个尺度对城市下垫面在水平和垂直两个方向上的扩展程度进行监测;并结合气象站点数据与WRF气象预报模型分析城市下垫面扩张与风场变化间的关系,进而明确城镇化对区域气候环境变迁的影响及其空间分异规律。本文研究对于城市科学发展与规划、大气环境质量改善,减缓城市气象灾害等具有重要意义。本文主要在以下三个方面进行研究:(1)利用QuikSCAT散射计数据与OLS/DMSP夜晚灯光数据提取了中国2000-2009年10年间的城市下垫面范围及后向散射系数,分析了城市下垫面的变化,讨论了不同区域的城市扩张特点,并进行了系统的比较。总体来说,2000-2009年我国城市扩张范围显著,城市面积增加了约5倍。然而,城市扩张在不同的区域表现出显著的差异,东部地区扩张范围较大,中部次之,西部扩张范围最小,扩张面积与区域的经济水平呈现较强的正相关关系;此外不同城市群的扩张模式也极为不同,主要表现在水平(城市下垫面面积)和垂直(建筑物高度)两个方面的差异。(2)由于灯光溢出效应,夜晚灯光数据提取城市下垫面存在提取范围过大,提取结果不准确的问题。而基于ALOS PALSAR提取城市下垫面存在虚警范围的现象。因此本文利用ALOS PALSAR数据与夜晚灯光数据相结合,提出了一种综合利用多源遥感数据提取城市下垫面的方法,有效的去除了SAR数据在建成区提取中存在虚警范围的问题,并用这一方法对京津冀地区的城市下垫面的范围及其变化进行了详细的分析。并结合同时期气象站点数据讨论了城市下垫面扩张对风场的影响。结果表明建成区面积与高度的增加改变了建成区下垫面粗糙度,对风速的拖拽效应不能忽视。对于北京区域而言,城市扩展造成的下垫面变化对于西北风的阻挡效应尤其显著。(3)为了验证城镇化过程造成风速减小这一现象,文章引入WRF气象预报模式。针对WRF模型设计了两组对比实验,从模型的角度分析验证了下垫面变化对于风场的具体影响。试验控制下垫面类型作为输入变量,通过比较两组实验结果可以发现:以遥感数据作为辅助信息获取真实的地表覆盖信息作为WRF下垫面的更新输入有助于提高模型对气象要素的模拟精度;风场对于下垫面类型变化敏感,城市下垫面的扩张区域的风速有明显的减小。
[Abstract]:Cities and towns are the most profound and concentrated area of human influence on climate change. With the rapid development of urbanization, there are a series of meteorological disasters and ecological environment problems, such as climate warming, frequent meteorological disasters, ecological imbalance, air pollution and so on. Multiple remote sensing data can be used to monitor the spatial and temporal characteristics of the underlying surface evolution and its influence on climate and environment elements in the rapid urbanization process. Therefore, the night light data, scatterometer data and synthetic aperture radar data are used in this paper. The expansion degree of urban underlying surface in horizontal and vertical directions is monitored by two scales, and the relationship between the expansion of urban underlying surface and the variation of wind field is analyzed by combining the meteorological station data and the WRF meteorological forecast model. Furthermore, the influence of urbanization on regional climate and environment change and the law of spatial differentiation are clarified. This paper is of great significance for the development and planning of urban science, the improvement of atmospheric environment quality and the mitigation of urban meteorological disasters. In this paper, the following three aspects are studied: (1) using QuikSCAT scatterometer data and OLS/DMSP night light data, the range and backscatter coefficient of urban underlay in China from 2000 to 2009 are extracted, and the change of urban underlying surface is analyzed. The characteristics of urban expansion in different regions are discussed and compared systematically. In general, China's urban expansion range was significant from 2000 to 2009, with a five-fold increase in urban area. However, urban expansion shows significant differences in different regions. The eastern region has a larger expansion range, the central region is the second, and the western region has the smallest expansion scope. The expansion area has a strong positive correlation with the economic level of the region. In addition, the expansion patterns of different urban agglomerations are also very different, mainly manifested in the differences between horizontal (area of the underlying surface of the city) and vertical (height of buildings) due to the effect of light spillover. Night lighting data extraction of urban underlying surface exists the problem that the extraction range is too large and the result is inaccurate. Based on ALOS PALSAR, there is a false alarm range on the underlying surface of the city. So this paper combines the ALOS PALSAR data with the night light data, and puts forward a comprehensive method of extracting the underlying surface of the city using multi-source remote sensing data, which effectively removes the problem of false alarm range in the extraction of the SAR data in the built area. With this method, the range and variation of the underlying surface of the city in Beijing, Tianjin and Hebei are analyzed in detail. The influence of the urban underlying surface expansion on the wind field is discussed based on the meteorological station data of the same period. The results show that the roughness of the underlying surface is changed with the increase of the area and height of the built area, and the drag effect of wind speed cannot be ignored. For the Beijing area, the barrier effect of the change of the underlying surface caused by urban expansion to the northwest wind is especially significant. In order to verify the phenomenon that the wind speed decreases due to the urbanization process, the WRF weather forecast model is introduced in this paper. Two sets of comparative experiments are designed for WRF model. The influence of the change of underlying surface on the wind field is verified from the point of view of the model. The test controls the underlying surface type as an input variable, By comparing two groups of experimental results, it can be found that using remote sensing data as auxiliary information to obtain real ground cover information as the updated input of WRF underlying surface is helpful to improve the simulation accuracy of meteorological elements in the model; The wind field is sensitive to the change of the underlying surface type, and the wind velocity in the expansion area of the urban underlying surface is obviously reduced.
【学位授予单位】：中国科学院大学(中国科学院遥感与数字地球研究所)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：P407;P461

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