摘要
典型极端天气现象遥感监测方法的研究为准确监测典型极端天气现象提供技术支持,可防止和减少因极端天气造成的事故和损失,对我国生态环境建设和可持续发展有着重要的现实意义。本课题来源于“耦合BRDF模型的城市地区气溶胶遥感反演模型与方法研究”(40701112),“华北区域气溶胶光学厚度卫星遥感反演研究”(200906),“北京生态环境多源卫星遥感监测研究”(200730)。本文以MODIS和CBERS数据为主要数据源,针对雾、霾、沙尘这三种典型极端天气现象的特征,使用单通道法及通道组合方法构建了监测模型,实现了典型极端天气现象的遥感监测。
本文主要进行了以下方面的研究:
1.为了说明典型极端天气现象遥感监测的可行性,使用6S模型模拟了不同能见度及水汽含量条件下,土壤、植被、水体等典型下垫面背景卫星反射率的变化;并通过查阅大量文献资料,归纳总结了雾、霾、沙尘粒子的物理特性以及物理特性对其光谱特性的影响。
2.通过分析云与雾、霾、沙尘的反射率与亮度温度的差异,提出了新的用于极端天气条件下的云识别方法,并与MOD35云掩膜产品进行了对比,结果表明,本文提出的云识别方法在识别云与雾、霾、沙尘等象元方面具有更高的准确性。
3.综合利用地基监测数据与MODIS数据,基于极端天气对应象元、地表象元、云象元反射率及亮度温度的差异,使用单通道法及通道组合方法构建了沙尘、雾、霾的遥感监测模型,以2008,2009年发生在我国内蒙古及中东部城市的雾、霾、沙尘天气为例,实现了云识别及雾、霾、沙尘监测。
4.综合利用地基监测数据与CBERS数据,基于沙尘象元、地表象元、云象元反射率及亮度温度的差异,使用单通道法及通道组合方法构建了沙尘监测模型,以2006,2007年发生在我国内蒙古境内的两次沙尘天气为例,实现了云识别及沙尘监测。
5.使用MICAPS资料验证了卫星遥感监测的雾、霾、沙尘结果。
实验结果表明本文提出的监测方法能较精确地提取雾、霾、沙尘信息,实现了雾、霾、沙尘与云、下垫面背景的分离以及雾、霾、沙尘之间的分离。
The study on the method for monitoring the typical extreme weather phenomenon by remote sensing provides a technical support to monitor them exactly, so it can prevent and reduce the accident and loss caused by the typical extreme weather phenomenon, having practical significance to ecological environment construction and sustainable development. This paper originates from "The study on aerosols inversion model and method by remote sensing in the city based on coupling BRDF model" (40701112), "The study on inversing aerosols optical depth by remote sensing in the north China regional" (200906), "The study on monitoring ecological environment of Beijing by multisource satellite remote sensing" (200730).The MODIS and CBERS data are main data sources in this paper. The monitoring models have been constructed based on the characteristics of fog, haze and dust storm to extract the areas of fog, haze and dust storm.
In this paper, study has been made as following:
1. In order to show the feasibility of monitoring the typical extreme weather phenomenon by remote sensing,6S model has been used to simulate the change of soil、vegetation and water satellite reflectance in different visibility and water vapor content. A lot of literatures have been read to inductive and summarize the physical characteristics of fog, haze and dust storm and analyze the influence to spectral properties.
2. From the reflectance and brightness temperature difference among cloud, fog, haze and dust storm, a new cloud recognition method used under the typical extreme weather phenomenon has been proposed. It has been compared with the cloud mask product MOD35.The result shows the cloud recognition method in this paper can recognize cloud more accurately when the typical extreme weather phenomenon happen.
3. The foundation monitoring data and MODIS data have been used to find the reflectance and brightness temperature difference among cloud, fog, haze, dust storm and land. The single channel method and channel combination method have been used to construct models for monitoring fog, haze and dust storm. Examples have been given, which happened at Inner Mongolia and the middle-east cities of China in 2008, 2009 year. The model has been used to recognize cloud and monitor fog, haze and dust storm.
4. The foundation monitoring data and CBERS data have been used to find the reflectance and brightness temperature difference among cloud, dust storm and land. The single channel method and channel combination method have been used to construct models for monitoring dust storm. Two examples have been given, which happened at Inner Mongolia in 2006, 2007 year. The model has been used to separate dust storm from cloud and land.
5. The software of MICAPS has been used to verify the result of monitoring fog, haze and dust storm by remote sensing.
The result shows that the monitoring method proposed in this paper can be used to extract the areas of fog, haze and dust storm more accurately, making it become true to separate fog, haze and dust storm from cloud, land and make the three typical extreme weather separated from each other.
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