地球信息科学学报 ›› 2018, Vol. 20 ›› Issue (3): 360-367.doi: 10.12082/dqxxkx.2018.170588

• 遥感科学与应用技术 • 上一篇    下一篇

城市气溶胶光学厚度空间格局特征多指标综合分析

赵小锋1,2(), 刘嘉慧2,3, 赵颜创4, 王菲菲2,3, 李桂林5   

  1. 1. 浙江省地理信息中心,杭州310012
    2. 中国科学院城市环境研究所 城市环境与健康重点实验室,厦门361021
    3. 中国科学院大学,北京 100049
    4. 中国科学院遥感与数字地球研究所,北京 100094
    5. 佛山市国土规划编制研究中心, 佛山 528000
  • 收稿日期:2017-12-04 修回日期:2017-12-26 出版日期:2018-03-20 发布日期:2018-03-20
  • 作者简介:

    作者简介:赵小锋(1981-),男,博士,副研究员,主要从事城市环境遥感与GIS。E-mail: xfzhao@iue.ac.cn

  • 基金资助:
    国家自然科学基金项目(41371392、71573242、71273252)

Multi-index Analysis of Spatial Patterns of Urban Aerosol Optical Depth

ZHAO Xiaofeng1,2,*(), LIU Jiahui2,3, ZHAO Yanchuang4, WANG Feifei2,3, Li Guilin5   

  1. 1. Geomatics Center of Zhejiang, Hangzhou 310012, China
    2. Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    3. University of Chinese Academy of Sciences, Beijing 100049, China
    4. Institute of Remote Sensing and Digital Earth, Beijing 100094, China
    5. Foshan Land Resource and Urban Planning Research Center, Foshan 528000, China
  • Received:2017-12-04 Revised:2017-12-26 Online:2018-03-20 Published:2018-03-20
  • Contact: ZHAO Xiaofeng E-mail:xfzhao@iue.ac.cn
  • Supported by:
    National Natural Science Foundation of China, No. 41371392, 71573242, 71273252.

摘要:

本文以厦门市为例,基于MODIS影像反演的大气气溶胶光学厚度(AOD),利用空间自相关和景观格局指数从数量、形态和结构方面综合分析了2014年各月份(5月和9月除外)AOD时空格局变化。结果表明,研究区AOD具有明显的时空分布差异,林地上空的AOD处于较低等级,建设用地上空AOD大部分处于中高等级;AOD在春夏季较大,在秋冬季较小。AOD分布存在显著正空间自相关性,而且主要存在高高(HH)、低低(LL)、高低(HL)3种聚集模式。低低聚集模式主要分布在厦门市的北部山区;高高(HH)和高低(HL)模式主要分布在本岛东北部新城和本岛外各新城的城区。在景观格局指数方面,从秋冬季节到春夏季节期间,研究区气溶胶光学厚度高等级斑块增加,景观结构趋于复杂,景观异质性增加。对AOD时空格局变化进行多指标综合分析可以更加深入、细致、全面地刻画气溶胶的变化规律,有助于精确评估气溶胶对环境、气候等的影响,为城市可持续发展提供决策支持。

关键词: 气溶胶光学厚度, 空间自相关, 景观指数, 多指标分析, 时空变化

Abstract:

In this study, a time series of MODIS -Aqua images were used to retrieve the atmospheric aerosol optical depth (AOD) of Xiamen City. Then, the spatio-temporal variations of AOD in different months of the year 2014/2015 except May and September were analyzed in respect of quantity, spatial configuration and structure, respectively. The analysis was implemented by integrating multiple indexes related to spatial autocorrelation and landscape metrics. The results showed that distribution of AOD had obvious spatial and temporal variations in the study area. The low-AOD patches were dominant over forests, while middle/high-AOD patches were dominant over built-up areas. The AOD showed significant seasonal variations, which increased in spring and summer and decreased in autumn and winter. The spatial clustering pattern of AOD, characterized by the indexes related to spatial autocorrelation, showed that low-low (LL) clustering pattern was in the northern mountains of the mainland, while high-high (HH) and high-low (HL) clustering patterns were in the newly developed northeast urban area of Xiamen Island and the urban areas of the mainland satellite towns along the coast. In terms of landscape metrics, high-AOD patches increased from autumn and winter to spring and summer, accompanied by an increase of both complexity and heterogeneity of the landscape structure. It is a useful tool to unfold more thorough, detailed and comprehensive description of the characteristics of AOD variation by using the multi-index analysis. Results of this study can help to assess the impact of aerosol on environment and climate, and provide decisions supporting for the sustainable development of cities.

Key words: aerosol optical depth (AOD), spatial autocorrelation, landscape metrics, multi-index analysis, spatio-temporal variation