首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于高光谱的环首都地区数字高程模型与可吸入颗粒物的空间相关性研究
引用本文:毛海颖.基于高光谱的环首都地区数字高程模型与可吸入颗粒物的空间相关性研究[J].光谱学与光谱分析,2016,36(9):2946-2950.
作者姓名:毛海颖
作者单位:中国人民武装警察部队警种学院,北京 102202
基金项目:国家科技支撑计划项目(2012BAH34B01),单兵便携应急侦测评估无人机系统研究项目(WK2016-Y7)
摘    要:空气中可吸入颗粒物浓度的增加与众多综合因素相关,其空间分散程度与高程DEM间也有一定的相关性。为了研究雾霾的污染与高度的空间相关关系,以环首都地区100 km范围内为研究对象,利用矩形格网尺度法对所研究区域进行不同边长及不同尺度的格网划分,通过无人机获取可见光影像数据和高光谱POS信息数据,对所研究区内的空气污染因子和高程因子进行提取和整合。同时利用地统计学GS+软件的克里格插值法对所提取的变量数据进行空间相关性研究,并利用MODIS遥感影像数据和无人机获取的POS数据与实地调查相结合的方法对地形和环境数据进行非线性回归拟合分析。计算在不同格网尺度下环首都地区空气中的可吸入颗粒物及高程因子的空间相关效应的影响变程,建立二者间的空间相关性优化模型,从而确定可吸入颗粒物浓度随着高程变化的整体趋势。结果表明:高程DEM与空气污染指数API的最大相关影响距离为14.74 km,且随着样本点间的距离增大,DEM的空间自相关性呈现逐渐减弱的规律,即可吸入颗粒物浓度随着高程的增加而减小的整体趋势。同时,建立了高程DEM与环境间的空间相关性模型,该模型符合地统计学的高斯球状模型,相关系数r均高于90%,模型拟合度较高。试验为日后相关部门控制空气污染指数随着高度的变化选择不同树种进行绿化提供了一定的理论和实践指导依据。

关 键 词:高光谱  环首都地区  数字高程模型  可吸入颗粒物  空间相关性    
收稿时间:2016-01-06

Researches on the Spatial Distribution of Digital Elevation Model and Particulate Matter Around the Central Metropolitan Correlation Based on Hyperspectral Ring
MAO Hai-ying.Researches on the Spatial Distribution of Digital Elevation Model and Particulate Matter Around the Central Metropolitan Correlation Based on Hyperspectral Ring[J].Spectroscopy and Spectral Analysis,2016,36(9):2946-2950.
Authors:MAO Hai-ying
Institution:Specialized Forces College of the Chinese Armed Police Force, Beijing 102202, China
Abstract:Increased concentration of air respirable particulate matter associated with a number of combination factors.Spatial dispersion is also correlated with elevation DEM.In order to study the fog haze pollution associated with digital elevation model of spatial relations,this paper used the capital area ring within 100 km as the research scope,partitioning different length scale grid according to the rectangular grid method in the study area,obtaining visible light image data and hyperspectral image data by using unmanned aerial vehicle (UAV)for the extraction and integration air pollution factor and elevation factor within the scope of this study.GS+ software of kriging interpolation method was used to research the spatial correlation of variable data extrac-tion;the MODIS remote sensing image data combined with field survey were used to analyze nonlinear regression of the terrain and environmental data.With the Calculation of variation effects of the particulate matter in the air and the spatial of the elevation factor under different grid scale ring of capital region,an optimization model of spatial correlation between them was established. Then the relation between the concentration of PM10 and height was determined.The biggest influence distance of elevation DEM associated with particulate matter API is 14.74 km.DEM space since the correlation of waning with the increase of the distance between sample points,which is also an important innovation of this paper.This result shows that the spatial correlation be-tween the elevation DEM and environment conforms to the statistical spherical Gaussian model,correlation coefficient R2 were over 90%,which model fittings good.This study provides a certain theoretical and practical guidance for the control of air pollu-tion index in the future as the change of height to select different tree species for afforestation.
Keywords:Hyperspectral ring  Central metropolitan correlation  Digital elevation model  Particulate matter  Spatial correlation function mutation
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《光谱学与光谱分析》浏览原始摘要信息
点击此处可从《光谱学与光谱分析》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号