地球信息科学学报 ›› 2016, Vol. 18 ›› Issue (12): 1653-1659.doi: 10.3724/SP.J.1047.2016.01653

• 地理空间分析综合应用 • 上一篇    下一篇

厦门市林地与建设用地对大气气溶胶空间分布的影响分析

赵颜创1,2(), 赵小锋1,2,*(), 刘乐乐1,2,3, 刘梦悦4   

  1. 1. 中国科学院城市环境与健康重点实验室,中国科学院城市环境研究所,厦门 361021
    2. 厦门市城市代谢重点实验室,厦门 361021
    3. 中国科学院大学,北京 100049
    4. 厦门大学环境与生态学院,厦门 361102
  • 收稿日期:2016-01-04 修回日期:2016-02-17 出版日期:2016-12-27 发布日期:2016-12-20
  • 通讯作者: 赵小锋 E-mail:yczhao@iue.ac.cn;xfzhao@iue.ac.cn
  • 作者简介:

    作者简介:赵颜创(1988-),男,河南郑州人,研究生,研究方向为城市环境遥感。E-mail:yczhao@iue.ac.cn

  • 基金资助:
    厦门市科技计划项目(3502Z20142020);中国科学院重点部署项目(KJZD-EW-TZ-G06-02);国家科技支撑项目(2012BAC21B03)

Impacts of the Forests and Built-up Areas on the Spatial Distribution of Aerosol in Xiamen City

ZHAO Yanchuang1,2(), ZHAO Xiaofeng1,2,*(), LIU Lele1,2,3, LIU Mengyue4   

  1. 1. Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    2. Xiamen Key Lab of Urban Metabolism, Xiamen 361021, China
    3. University of Chinese Academy of Sciences, Beijing 10049, China
    4. College of the Environment and Ecology, Xiamen University, Xiamen 361102, China
  • Received:2016-01-04 Revised:2016-02-17 Online:2016-12-27 Published:2016-12-20
  • Contact: ZHAO Xiaofeng E-mail:yczhao@iue.ac.cn;xfzhao@iue.ac.cn

摘要:

分析大气气溶胶空间分布的影响因素有助于理解其变化机制与规律,从而为大气环境质量的调控提供科学依据。本文以厦门市为例,利用MODIS-Aqua卫星遥感影像,反演了大气气溶胶光学厚度。同时,选取Landsat8 OLI卫星数据,进行土地覆被分类。在此基础上,利用相关分析、一元线性回归模型和方差分解,对比研究了城市林地和建设用地对大气气溶胶空间分布的影响作用,得出以下结论:① 暗像元与插值法的结合适合厦门地区春季气溶胶光学厚度的反演;② 建设用地上空气溶胶光学厚度值明显高于林地;③ 林地对气溶胶空间分布的影响作用强于建设用地。本研究对缓解城市大气污染和改善城市生态环境具有重要参考价值和意义。

关键词: 气溶胶光学厚度, 土地覆被, 空间变化, 遥感, 厦门

Abstract:

Analyzing factors that affecting the spatial distribution of aerosol can help researchers to understand the changing mechanism of aerosol, which provides a scientific reference for regulating the atmospheric quality. In this research, taking Xiamen city as a case study, the MODIS -Aqua and Landsat8 OLI images were used in the aerosol optical depth (AOD) inversion and land cover classification, respectively. Then, the impacts of forests and built-up areas on the spatial distribution of aerosol were compared by employing the correlation analysis, the simple linear regression model and the variation partitioning. It is concluded that: (1) the combination of Dark Dense Vegetation (DDV) algorithm and the interpolation method was appropriate for the computation of AOD inversion during the spring season in Xiamen; (2) the AOD for the built-up areas was significantly higher than that for the forests; and (3) the forests had more impacts on the spatial distribution of aerosol than the built-up areas. Results of this study have significances and referential values for the improvement of urban atmospheric quality and ecological environment.

Key words: aerosol optical depth, land cover, spatial distribution, remote sensing, Xiamen