北京市细颗粒污染物与土地覆被景观格局关联分析
收稿日期: 2021-06-29
修回日期: 2021-07-07
网络出版日期: 2021-09-26
基金资助
国家重点研发计划(2017YFD0600903-03);内蒙古自治区科技计划项目(2020GG0067);内蒙古农业大学高层次人才引进项目(170014);双一流建设项目(DC2000001008)
Correlation Analysis of Fine Particulate Pollutants and Land Cover Landscape Pattern in Beijing
Received date: 2021-06-29
Revised date: 2021-07-07
Online published: 2021-09-26
空气污染是当今重点环境问题,了解不同土地覆被景观格局与空气细颗粒污染物的相互影响,对改善城市生态环境具有重要意义。气溶胶光学厚度(Aerosol Optical Depth,AOD)是空气细颗粒污染物生成的前提,研究通过引入AERONET北京地面检测点所测AOD数据和地面细颗粒污染物数据进行拟合分析,随后运用MODIS数据反演北京地区四季AOD,处理Landsat 8影像得到2018年北京市景观类型指数,并与四季AOD数据进行关联分析。结果表明:1)细颗粒污染物与LPI(最大斑块指数)、ED(边界密度)、COHESION(斑块连接度)、AI(斑块聚集度)4个指数均为显著负相关,但与PD(斑块破碎度)、LSI(景观形状指数)两个指数则存在极显著正相关;2)全年森林与草地是与细颗粒污染物呈显著负相关的核心类型,农田与水体的相关性则与季节变化有显著关系;3)利用多元线性回归分析得出森林、草地、农田、水体与四季细颗粒污染物的规律模型,进一步证明可用景观指数对区域细颗粒污染物质量浓度值进行估算。
马博伦 , 王雷 , 滑永春 . 北京市细颗粒污染物与土地覆被景观格局关联分析[J]. 林草资源研究, 2021 , 0(4) : 94 -103 . DOI: 10.13466/j.cnki.lyzygl.2021.04.013
Air pollution is a key environmental issue nowadays.It is of great significance to understand the interaction between different land cover landscape patterns and air fine particulate pollutants for improving urban ecological environment.Aerosol optical depth(AOD) is the premise of the generation of fine particulate pollutants in the air.The AOD data measured by the AERONET ground monitoring points in Beijing and the surface fine particulate pollutants data were used for fitting analysis,and then the AOD of four seasons in Beijing was retrieved by using MODIS data.The Landsat8 image was processed to obtain the landscape type index of Beijing in 2018,and the correlation analysis was conducted with four seasons AOD data.The results showed that:1) fine particulate pollutants were negatively correlated with LPI(maximum patch index),ED(boundary density),COHESION(patch connectivity) and AI(patch aggregation),but positively correlated with PD(patch fragmentation) and LSI(landscape shape index);2) The annual forest and grassland were the core types with significant negative correlation with fine particulate pollutants,while the correlation between farmland and water body was significantly related to seasonal changes;3) Multiple linear regression analysis was used to get the regular model of forest,grassland,farmland,water and fine particulate pollutants in four seasons,which further proved that landscape index could be used to estimate the mass concentration of regional fine particulate pollutants.
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