摘要
PM10质量浓度是表征城市空气质量最为重要的污染指标之一.快速了解其浓度和大范围的分布状况,有利于控制PM10质量浓度,并最终提高空气质量.卫星遥感可在瞬间获取大区域的地表和大气信息,在污染监测上具有广泛的应用前景.本文在对覆盖杭州市2004年至2007年的MODIS数据进行了小波分析的基础上,建立了小波系数与同期PM10质量浓度实测数据的回归模型,并进一步比较了不同空气质量条件下的相应图像特征.初步实验表明,MODIS遥感影像特征与PM10浓度存在相关关系.
PM10 concentration is one of the most important quantitative indicators to indicate air quality in urban areas. Efficient collection of concentration and distribution information of PM10 at a large scale benefits control of PM10 and ultimately will help improve air quality. Satellite remote sensing, which provides a means to obtain atmosphere and surface conditions in a large scale, is a good prospect for pollution monitoring. In this paper, a satellite remote sensing product, namely MODIS images captured from 2004 to 2007 over Hangzhou, were decomposed by wavelet transformation. The resultant wavelet coefficients were analyzed with the in situ PM10 concentration to establish a regression model. Further comparisons of image features in different air quality conditions were conducted. The initial experimental result shows that image features of MODIS are correlated with PM10 concentration.
出处
《环境科学学报》
CAS
CSCD
北大核心
2010年第3期565-571,共7页
Acta Scientiae Circumstantiae
基金
浙江省科技厅平台项目(No10127003)~~
关键词
遥感
PM10
小波分析
城市大气污染
remote sensing
PM10 concentration
wavelet analyze
urban air pollution
