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基于多源遥感数据并考虑景观源汇尺度效应的大气雾霾影响

[Effect of Atmospheric Haze Based on Multi-source Remote Sensing Data Considering the Size Effect of Landscape Sources and Sinks].

作者信息

Xu Kai, Yu Tian-Tian, Sun Jiao-Jiao, Yuan Zhao-Xiang, Qin Kun

机构信息

Faculty of Information Engineering, China University of Geosciences(Wuhan), Wuhan 430070, China.

Faculty of Earth Science, Chengdu University of Technology, Chengdu 610059, China.

出版信息

Huan Jing Ke Xue. 2017 Dec 8;38(12):4905-4912. doi: 10.13227/j.hjkx.201702032.

Abstract

Based on a geo-weighted regression model, this study analyzes the relationship between the landscape patterns of sources and sinks in urban areas and atmospheric haze pollution. First, the classification result of the study area is divided into a number of square grids with side lengths of 2-9 km. Heterogeneity indices at different scales are calculated and compared to select an optimal scale for the following analysis. Then, the category level landscape indices, such as PLAND, PD, COHEDION, LPI, and FRAC_MN, are calculated in each grid. The aerosol optical thickness (AOD) of Wuhan is used to represent the degree of atmospheric haze pollution. Furthermore, the mean value of the pixels in each grid is regarded as the value of the grid's center. Next, the landscape sources and sinks of atmospheric haze pollution are selected based on the analysis of the correlation between landscape indices and AOD. To make the following analysis more efficient, the indices selected previously are determined using their correlation coefficients. Finally, the geo-weighted regression analysis model is used to analyze the relationship between the landscape indices of the category level and AOD. In addition, the influences of industrial, commercial, and residential areas on haze pollution are analyzed based on the result of the classification of urban functional areas. The results show that the heterogeneity of the whole landscape is most obvious at a 6 km scale, so 6 km is the optimal scale for the analysis. The landscape sources of atmospheric haze pollution are the buildings, and the landscape sinks are shrubs and woodland. Reducing the proportion of landscape source area and increasing the degree of fragmentation can cut down aerosol optical thickness. Distributing the landscape sources and sinks evenly and interspersedly could effectively reduce aerosol optical thickness, which represents atmospheric haze pollution. For Wuhan City, the main sources of haze pollution are commercial and residential areas in the city center, representing public sources. Since it is not easy to adjust existing facilities and infrastructure, adjusting built-up areas slightly and planning reasonably for those areas that are not yet built up can reduce atmospheric haze pollution.

摘要

基于地理加权回归模型,本研究分析了城市地区源汇景观格局与大气雾霾污染之间的关系。首先,将研究区域分类结果被划分为若干边长为2 - 9千米的正方形网格。计算并比较不同尺度下的异质性指数,以选择最优尺度用于后续分析。然后,在每个网格中计算类别水平的景观指数,如斑块面积百分比(PLAND)、斑块密度(PD)、凝聚度(COHEDION)、最大斑块指数(LPI)和平均斑块分维数(FRAC_MN)。利用武汉的气溶胶光学厚度(AOD)来表征大气雾霾污染程度。此外,将每个网格中像素的平均值视为该网格中心的值。接下来,基于景观指数与AOD之间的相关性分析,选取大气雾霾污染的景观源和汇。为了使后续分析更高效,利用之前选取指数的相关系数来确定这些指数。最后,使用地理加权回归分析模型来分析类别水平的景观指数与AOD之间的关系。此外,根据城市功能区分类结果分析工业、商业和居民区对雾霾污染的影响。结果表明,整个景观的异质性在6千米尺度下最为明显,因此6千米是分析的最优尺度。大气雾霾污染的景观源是建筑物,景观汇是灌木和林地。减少景观源面积比例并增加破碎化程度可以降低气溶胶光学厚度。均匀且分散地分布景观源和汇能够有效降低代表大气雾霾污染的气溶胶光学厚度。对于武汉市而言,雾霾污染的主要来源是市中心的商业和居民区,属于公共源。由于调整现有设施和基础设施并不容易,对建成区进行微调并对未建成区进行合理规划可以减少大气雾霾污染。

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