雾的遥感监测与物理特性模拟研究
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摘要
雾是一种灾害性天气,具有出现几率高、发生范围广、危害大等特点,经常造成高速公路封闭、航运中断,甚至会造成人员伤亡、财产损失等严重灾情,雾对人体健康、供电线路、农业生产等也有严重影响。雾的监测方法有两种,常规监测方法和利用气象遥感资料(包括卫星和雷达资料)进行监测。常规的监测方法受到观测站点的分布及观测时间的限制,尤其是对大范围雾的监测,不仅浪费大量的人力、物力,而且难以准确获取其强度和范围信息；而气象卫星具有覆盖范围大、观测波段多、观测频次高、信息源可靠、直接投入成本低的优点,利于雾的实时动态监测。随着卫星技术的发展和成熟,卫星资料在大雾监测中的作用已经越来越突出。
本文主要研究了以下内容：
首先,介绍了雾、云、下垫面在卫星遥感图像上的光谱特征,利用不同季节、不同时间的大量数据统计、分析得到它们之间的光谱差异,总结得到了雾的卫星遥感的一般性监测原理。
其次,利用风云二号气象卫星进行了雾的监测,充分利用风云二号气象卫星覆盖范围大、时间分辨率高的优点,进行了雾的连续性动态监测,并针对雾的发生、发展及消亡进行了研究。根据2007年12月18日——21日的风云卫星数据利用该方法对华北、华东地区进行了雾的监测,取得了良好的效果,通过与测站数据进行比对,监测精度达到了76.6%；同时还利用探空资料对此次大雾的生消机理进行分析,通过对天气图上的温、压、湿、风等基本要素的解读,详细阐述了此次大雾的内部发生、发展及消亡机理,对于后面利用探空资料进行雾的预报分析提供了理论基础；
另外,还利用环境减灾小卫星进行了雾的监测,环境星是我国自行研制发射的一颗环境卫星,该卫星主要的功能就是对各种自然灾害进行监测、评估,对环境保护等提供技术支持,其搭载的传感器、空间分辨率等都优于风云二号气象卫星,适合进行雾的监测。本文利用红外相机近红外波段的反射率代替可见光波段的反射率,对2010年1月16日,湖北、河南、安徽、江西等省发生的大雾天气进行了监测,取得了比较理想的结果；
最后,介绍了现在比较常用的MODTRAN辐射传输模型,对模型的一些基本功能及输入输出参数做了简要的概述,根据该模型模拟了雾的一些物理特性,包括能见度、透过率、厚度等,利用得到的模拟数据拟合出它们之间的关系式,为雾的物理特性的遥感反演提供了一种新的方法。
Fog is a disastrous weather, which has occurred with high probability, the occurrence of a wide range, major hazardous and other characteristics, often cause highway closed and the shipping interruption, even casualties, property damage and other serious disaster. The fog also has a significant effect on human health, power lines and agricultural production. There are two ways to monitor the fog, conventional monitoring methods and the use of meteorological remote sensing data (including satellite and radar data) for monitoring. The conventional method of monitoring is restricted to the distribution of observation stations and observation time, especially for the monitoring of large-scale fog. It is not only wasting a lot of manpower and material, difficult to obtain accurate information on the intensity and scope of fog; but meteorological satellites have the larger coverage range, multi-band observations, higher frequency of observations, reliable source of information, lower of directly cost, so they are conducive to real-time dynamic monitoring of the fog. With the development and maturation of satellite technology, the role of satellite data in monitoring of fog will become more and more prominent.
In this paper, it has been done the researches as follows:
First of all, the spectral characteristics of the fog, clouds and land surface in the satellite remote sensing images have been introduced, and the spectral differences between them are summarized by statistical analyzing large amounts of data in different seasons and different times, which will be great useful for determining the fog monitoring threshold in following study. The general principle of fog monitoring using satellite remote sensing is also summed up in this chapter.
Secondly, the monitoring of fog is carried out using the FY-2 geostationary meteorological satellite. In this process, all advantages of FY-2 geostationary meteorological satellite, for example, the larger coverage range, higher time resolution, have been fully utilized to carry out the dynamic fog monitoring. The mechanism study of fog occurrence, development and demise is done at the same time. Using the algorithm of fog monitoring using FY-2 geostationary meteorological satellite and the data of FY-2 geostationary meteorological satellite, fog is monitored by combining spectral analysis method and the texture structure template method. In this process, the FY-2 geostationary meteorological satellite data of northern and eastern china between December 18,2007 and December 21,2007 is used. The monitoring accuracy was 76.6% by comparing with the data from monitoring stations, so the results are satisfactory. In addition, the mechanism of this heavy fog is analyzed using radiosonde data, with interpretation of the temperature, pressure, humidity, wind and other basic elements in weather chart, which provides a theoretical basis for the fog prediction and will be very useful to the fog prediction.
In addition, the monitoring of the fog using HJ-1B satellite, which is first environmental satellite independently developed by china. The main function of this satellite is to monitor and evaluate a variety of natural disasters, providing technical support for environmental protection. Its onboard sensors, spatial resolution are superior to FY-2 meteorological satellite, suitable for the fog monitoring. However, because the spatial resolution and detection range of the CCD camera and infrared camera equipped on satellites are inconsistent, it is difficult to use two cameras at the same time in the fog monitoring process. In this article, the reflected radiation in near infrared band is used for fog monitoring instead of the reflectivity in visible band. The heavy fog in Hubei, Henan, Anhui, Jiangxi province on January 16,2010, was monitored utilizing this method, and the satisfactory results are achieved.
Finally, the MODTRAN radiative transfer model and its basic features, input and output parameters are introduced. Some physical characteristics, including visibility, transmittance, thickness, etc, are simulated according to the model. The relationships between them are obtained by fitting the simulated data, which provides a new approach to the retrieval of physical properties using remote sensing.
本文主要研究了以下内容：
首先,介绍了雾、云、下垫面在卫星遥感图像上的光谱特征,利用不同季节、不同时间的大量数据统计、分析得到它们之间的光谱差异,总结得到了雾的卫星遥感的一般性监测原理。
其次,利用风云二号气象卫星进行了雾的监测,充分利用风云二号气象卫星覆盖范围大、时间分辨率高的优点,进行了雾的连续性动态监测,并针对雾的发生、发展及消亡进行了研究。根据2007年12月18日——21日的风云卫星数据利用该方法对华北、华东地区进行了雾的监测,取得了良好的效果,通过与测站数据进行比对,监测精度达到了76.6%；同时还利用探空资料对此次大雾的生消机理进行分析,通过对天气图上的温、压、湿、风等基本要素的解读,详细阐述了此次大雾的内部发生、发展及消亡机理,对于后面利用探空资料进行雾的预报分析提供了理论基础；
另外,还利用环境减灾小卫星进行了雾的监测,环境星是我国自行研制发射的一颗环境卫星,该卫星主要的功能就是对各种自然灾害进行监测、评估,对环境保护等提供技术支持,其搭载的传感器、空间分辨率等都优于风云二号气象卫星,适合进行雾的监测。本文利用红外相机近红外波段的反射率代替可见光波段的反射率,对2010年1月16日,湖北、河南、安徽、江西等省发生的大雾天气进行了监测,取得了比较理想的结果；
最后,介绍了现在比较常用的MODTRAN辐射传输模型,对模型的一些基本功能及输入输出参数做了简要的概述,根据该模型模拟了雾的一些物理特性,包括能见度、透过率、厚度等,利用得到的模拟数据拟合出它们之间的关系式,为雾的物理特性的遥感反演提供了一种新的方法。
Fog is a disastrous weather, which has occurred with high probability, the occurrence of a wide range, major hazardous and other characteristics, often cause highway closed and the shipping interruption, even casualties, property damage and other serious disaster. The fog also has a significant effect on human health, power lines and agricultural production. There are two ways to monitor the fog, conventional monitoring methods and the use of meteorological remote sensing data (including satellite and radar data) for monitoring. The conventional method of monitoring is restricted to the distribution of observation stations and observation time, especially for the monitoring of large-scale fog. It is not only wasting a lot of manpower and material, difficult to obtain accurate information on the intensity and scope of fog; but meteorological satellites have the larger coverage range, multi-band observations, higher frequency of observations, reliable source of information, lower of directly cost, so they are conducive to real-time dynamic monitoring of the fog. With the development and maturation of satellite technology, the role of satellite data in monitoring of fog will become more and more prominent.
In this paper, it has been done the researches as follows:
First of all, the spectral characteristics of the fog, clouds and land surface in the satellite remote sensing images have been introduced, and the spectral differences between them are summarized by statistical analyzing large amounts of data in different seasons and different times, which will be great useful for determining the fog monitoring threshold in following study. The general principle of fog monitoring using satellite remote sensing is also summed up in this chapter.
Secondly, the monitoring of fog is carried out using the FY-2 geostationary meteorological satellite. In this process, all advantages of FY-2 geostationary meteorological satellite, for example, the larger coverage range, higher time resolution, have been fully utilized to carry out the dynamic fog monitoring. The mechanism study of fog occurrence, development and demise is done at the same time. Using the algorithm of fog monitoring using FY-2 geostationary meteorological satellite and the data of FY-2 geostationary meteorological satellite, fog is monitored by combining spectral analysis method and the texture structure template method. In this process, the FY-2 geostationary meteorological satellite data of northern and eastern china between December 18,2007 and December 21,2007 is used. The monitoring accuracy was 76.6% by comparing with the data from monitoring stations, so the results are satisfactory. In addition, the mechanism of this heavy fog is analyzed using radiosonde data, with interpretation of the temperature, pressure, humidity, wind and other basic elements in weather chart, which provides a theoretical basis for the fog prediction and will be very useful to the fog prediction.
In addition, the monitoring of the fog using HJ-1B satellite, which is first environmental satellite independently developed by china. The main function of this satellite is to monitor and evaluate a variety of natural disasters, providing technical support for environmental protection. Its onboard sensors, spatial resolution are superior to FY-2 meteorological satellite, suitable for the fog monitoring. However, because the spatial resolution and detection range of the CCD camera and infrared camera equipped on satellites are inconsistent, it is difficult to use two cameras at the same time in the fog monitoring process. In this article, the reflected radiation in near infrared band is used for fog monitoring instead of the reflectivity in visible band. The heavy fog in Hubei, Henan, Anhui, Jiangxi province on January 16,2010, was monitored utilizing this method, and the satisfactory results are achieved.
Finally, the MODTRAN radiative transfer model and its basic features, input and output parameters are introduced. Some physical characteristics, including visibility, transmittance, thickness, etc, are simulated according to the model. The relationships between them are obtained by fitting the simulated data, which provides a new approach to the retrieval of physical properties using remote sensing.
引文
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[2]Hunt, Radiative properties of terrestrial clouds at visible and infrared thermal window wavelength [J]. Quarterly Journal of the Royal Meteorological Society,1973,99:346-369
[3]Eyre J R, Brownscombe J I, Allm R J. Detection of fog at night using advanced very high resolution radiometer (AVHRR) imagery [J]. Meteorological Magazine,1984, 113(1346):266-271
[4]Ellrod G P. Advances in the detection and analysis of fog at night using GOES multispectral infrared imagery. Weather Forecasting[J],1995,10(3):606-619
[5]Thomas F L, Furk F J, and Richardson K. Stratus and fog products using GOES 8.9-3.9μm data[J], Weather and Forecasting,1997,12(3):664-677
[6]Bendix, A case study on the determination of fog optical depth and liquid water path using AVHRR data and relations to fog liquid water content and horizontal visibility[J]. International Journal of Remote Sensing,1995,16(3):515-530
[7]Jorg Bendix, Jan Cermak, Thies B New perspectives in remote sensing of fog and low stratus-Terra/Aqua-MODIS and MSG[R]. Cape Town ZA:Proceeding 3 International Conference on Fog, Fog Collection and Dew,2004:11-15
[8]Jorg Bendix, Boris Thies, et, Ground Fog Detection from Space Based on MODIS Daytime Data-A Feasibility Study [J]. Weather and Forecasting.2005 12,989-1005
[9]Jan Cermak, Jorg Bendix. Dynamical Nighttime Fog/Low Stratus Detection Based on Meteosat SEVIRI Data:A Feasibility Study[J]. Pure appl. geophys,2007,164:1179-1192
[10]Jan Cermak, Jorg Bendix. A novel approach to fog/low stratus detection using Meteosat 8 data [J], Atmospheric Research,2008,87,279-292
[11]居为民,孙涵,张忠义,等.卫星遥感资料在沪宁高速公路大雾监测中的初步应用[J],遥感信息,1997(3)：25-27
[12]刘健,许健民,方宗义.利用NOAA卫星的AVHRR资料试分析云和雾顶部粒子的尺度特征[J],应用气象学报,1999,10(1)：28-33
[13]李亚春,孙涵,李湘阁,等.用GMS-5气象卫星资料遥感监测白天雾的研究[J],南京气象学院学报,2001,24(3)：121-129
[14]周红妹,谈建国,葛伟强,等.NOAA卫星云雾自动检测和修复方法[J],自然灾害学报, 2003,12(3)：41-47
[15]纪瑞鹏,代付,班显秀.NOAA/AVHRR图像资料在大雾灾害监测中的应用[J],防灾减灾工程学报,2004,24(2)：149-152
[16]张树誉EOS-MODIS资料在陕西大雾监测中的应用[J],灾害学,2003,17(2)：65-68
[17]孙涵,孙照渤,李亚春.雾的气象卫星遥感光谱特征[J],南京气象学院学报,2004,27(3)：289-301
[18]陈伟,袁志康,周红妹,等GMS-5红外图像上夜间雾的分离实验[J],气象科学,2004,24(2)：193-198
[19]陈林,牛生杰,仲凌志.MODIS监测雾的方法及分析[J],南京气象学院学报,2006,29(4),448-454
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