静止卫星数据准实时处理与亮温场远程计算服务综合技术研究与应用
|
摘要
卫星热红外遥感以其大视野、高精度和短周期等诸多优势以及对某些强震红外异常的良好反映,成为监测断裂活动性及地震短临前兆的很有前途的观测技术。然而由于地表热红外辐射受云层、地形地貌、地物类型和气象等诸多外部非震因素的影响,仅靠震前震后一定时段的卫星资料不足以排除所有非震因素的影响,至少需利用两年以上的卫星历史数据从不同的时间、空间尺度进行综合统计分析和相关性研究,才能提取出普遍性的规律。就地震热红外遥感来说,静止卫星相对于极轨卫星来说时间分辨率高(非汛期每小时,汛期每半小时可以获取约覆盖三分之一地球的一幅地球全景图像),有利于生成时效快、高质量的全国地表亮温数据,有利于地震前兆信息的捕获。但是,由于缺乏面向地震行业的、大规模的静止卫星数据处理系统以及相应的海量数据仓库,这方面的研究工作受到了严重制约。目前,卫星热红外遥感观测与应用技术已经列入《国家中长期科技和技术发展规划纲要》,《国家防震减灾规划》中,以及5部委发布的《国家地震科学技术发展纲要》业已把卫星热红外等多源遥感卫星及地面应用系统,天地一体化观测数据处理技术和地震信息识别与提取方法列入重点发展领域与优先研究主题。
我们于2007年8月份架设了风云静止卫星接收系统,每天接收到的卫星数据量多达3G,每年将接收到1000G的原始数据,加上追加的从2006年1月到2007年8月的原始数据3TB,数据量庞大。如果这些数据仅仅依靠人工值守进行接收、校正、备份、专题图生成等预处理,工作量巨大,很难保证卫星数据获取的及时性和可靠性。针对静止卫星数据的特点,本文通过静止卫星数据处理的方法研究、改进和应用,提出了静止卫星地表亮温时区差校正模型,静止卫星短周期去云算法,实现了静止卫星图像精确定位算法,解决了全自动去噪、去云、数据订正、合成、编码、时间解码和地理信息处理等一系列技术问题;在此基础上,从底层开始自主开发了卫星数据准实时自动处理系统,避免了大量的人工操作,获得了大量的、时间上不间断的、空间上覆盖全国的卫星热红外无云遥感影像库,以及相应的、经过适当设计的卫星影像信息库,组成了包含大量历史数据并且具有自动动态更新能力的数据仓库,积累了从2006年至今的数据。
热红外地表亮温数据的质量问题一直是利用热红外遥感数据进行地震活动性热红外异常研究的瓶颈。首先要解决的就是自动化处理应用中遇到的原始数据的噪声和干扰线问题,针对此本文研究和发展噪声、干扰线的自动识别算法并予以消除。其次是云层干扰问题,如果地表上空被云层覆盖,卫星探测到的则是云顶的热红外辐射信息。目前云层消除的主要手段是利用一个时期内(例如十天)同一地区的多景影像进行对比分析。假设在这一时期内任一地段出现过无云天气,则可利用该时段的影像生成合成影像的局部。对于目前地震热红外监测所利用的极轨卫星来说,由于其重访周期长(单颗星,24h),在中国区域内每天夜间对同一地点重复观测的数据两幅(极少时间为3幅),若要获得大面积如全国范围内的无云合成地表亮温大概需要10天左右的数据(对于同一接收点)才能完成,且西部地区很难完全覆盖(卫星接收天线仰角小),局部地区可进行像素比对的图幅数据少,因此利用极轨气象卫星很难得到高质量、短周期的连续的全国合成地表亮温数据。本文根据静止卫星时间分辨率高、覆盖范围大的特点,通过对每3-5天夜间0点-3点的数据(这样无论太阳高度角、相对方位角还是日照、降温时间的影响都是大体相同的)利用热红外通道2辐射值进行比对以NE值大的像素替代NE值小的像素来消除云层实验,得出每5天一个周期进行像素对比合成消除云层能够达到较好的效果,并进行了具体算法实现。对于热红外通道来说虽然处在大气窗区,但仍存在大气影响(主要表现为水汽吸收),使得到达星载传感器的下垫面热红外辐射能量受到了大气削弱。本文利用分裂窗方法,通过对9个监测区样本从2007年9月18日至2008年8月15日夜间4点的共211幅影像数据进行了地表亮温反演,反演结果表明大气对地表亮温会造成-12~8K的影响,本文通过此方法有效地实现了对影像的大气校正,生成了中国区域及邻区的无云地表亮温影像库。
结合亮温场远程计算与数据共享系统的需求,构建了基于Netfilter/Iptables技术的双出口透明网关,提高了地震地质与地震动力学数据共享分中心的访问速度,减少网络拥塞;提出了利用ArcIMS Servlet Connector连接器,把ArcIMS与.NET平台集成开发方案的新思路,这样的优点有:1、保留了利用ArcIMS Servlet Connector的开发方式;2、把Asp.net服务器端的强大功能融合进去,以便用户实现更高级的数值分析、计算;3、大大提高了项目的开发效率。在上述静止卫星自动化处理系统所形成的数据仓库的基础上,依此方案实现了基于WebGIS的分布式热红外遥感影像发布、共享系统。
随着信息技术的发展,高精度、数字化、网络化、海量地震观测数据的获取已经成为可能,正是密集丰富的地球信息促进地震预测预报研究和地球科学研究的发展,利用现代网络信息技术,把观测系统、科学计算系统、数据库系统和基础资源互连互通、资源共享,建立现代地震网络计算应用和网络科技环境平台,实现网络实时协同研究、实验仪器远程使用、资源共享的信息技术环境,提升我国地球科学研究和地震预测等科技创新能力,同时也是我国网络科技环境的有机组成部分,并为国家网络科技环境建设提供参考和经验。本文以国家地震网络计算应用系统大框架为支撑,依托于地质研究所网络远程计算分节点建设,在自主开发的静止卫星准实时处理系统日常运行基础上,设计了涵盖连续历史数据的海量规模的数据仓库、数据交换和数据服务中心,设计了Web Service与WebGIS系统集成框架,开发了静止卫星亮温场远程准实时计算服务系统,实现了为网络客户端提供全国范围内任意自选区域的亮温场、变化场计算模型与计算应用。经过以上方面的研究工作,从而实现了把观测系统、科学计算系统、数据库系统和基础资源互连互通、资源共享。
本文主要取得了如下研究成果:
(1)利用Vc++平台,从底层开发实现了具有自主知识产权的静止卫星数据准实时处理综合系统。通过全自动去噪算法、短周期合成去云算法、静止卫星精确定位算法的实现,有效地提高了热红外地表亮温数据质量,并生成了动态性较强的地表亮温数据库。该系统的完成为地震热红外研究提供了实用的技术手段和技术基础。
(2)以静止卫星数据仓库为支撑,通过Web Service与WebGIS的系统集成,实现了静止亮温场远程计算服务,研究了动态区域亮温信息提取算法、为网络客户端提供全国范围内任意自选区域的亮温场、变化场计算模型与计算应用,把目前较为成熟的Web Service技术和网格计算进行了初步结合应用。
(3)首次提出了静止卫星亮温时区差校正模型。利用静止卫星每5日合成数据对4个不同时区地理位置点的亮温进行年采样统计,得到了自然月1-3月(冬季),4-6月(春季),7-9月(夏季),10-12月(秋季)4个不同阶段4个位置的共16条亮温日变化曲线,从曲线图上可以明显看出时区差对亮温所造成的影响。基于曲线变化规律,给出了亮温时区差校正的3种情况及校正公式。通过上面的校正模型,能够较好地消除不同地方因时区差所造成的亮温的增高和降低。
(4)利用数据仓库理念和统计学方法,对2006年到2008年9个监测区进行了全面研究得出了通常情况下亮温随时间演化和按空间分布的规律。通过对2008年新疆于田地震研究区震前、后的逐幅热红外地表亮温图像解译,2008年震前、震后逐幅数据亮温变化曲线,以及2006-2008年每5日合成数据亮温变化曲线对比分析得知:在震前35天开始,于田地震附近的康西瓦断裂带亮温值明显比周围增高,属于亮温增高阶段;震前8天时间内,于田地震附近的康西瓦断裂带亮温值明显比周围增高,在震前7天亮温达到最高值263.36K;震前4小时于田地震附近的康西瓦断裂带亮温值出现下降趋势。在地震发生后,亮温值开始下降,下降幅度约4K。2008年于田监测区震前25天亮温均值比2006年、2007年同期亮温值分别高出1.1-6.84K,3.8-14.2K。
(5)通过建立地震网络计算应用和网络科技环境平台,对静止卫星数据准实时处理综合系统、基于WebGIS的遥感影像发布系统、远程计算服务系统进行了网络实时协同研究,从而实现了把观测系统、科学计算系统、数据库系统和基础资源互连互通、资源共享。
Satellitic thermal infrared remote sensing has become a promising technique for monitoring fault activities and earthquake precursors for its many advantages, such as a wide field of vision, high spatial resolution, short observation period, and also owing to its good reflection to thermal infrared anomalies of some major earthquakes. However, the thermal thermal infrared radiation of the earth’s surface is influenced by the external non-seismic factors, such as cloud layers, terrain, object styles, and weathe. All the non-seismic factors cannot be excluded only with the satellite data in a period around the earthquake. A general research on the historic satellite data of at least two years using temporal and spatial compositive analysis of statistics is of great necessity to find out the universal features. For seismic thermal infrared remote sensing, the time resolution of the geostationary satellite is higher than that of the polar-orbiting satellite (a panorama graph which covers about 1/3 of the whole earth can be captured each half hour during the flood season or each hour during the non-flood season), which is favorable to generating short period and high quality brightness temperature data over all the surface of China and capturing the earthquake precursor information. Nevertheless, the lack of the seismology oriented extensive satellite data processing system and a massive professional data warehouse needed by seismologists has seriously restricted the research. The observation and application technology with satellitic thermal infrared remote sensing has been listed in the medium- and long-term program for the development of science and technology in China and the plans for earthquake prevention and disaster reduction. Moreover, the satellitic thermal infrared remote sensing, the ground application system, the technology for processing the space-earth Integration observation data, and the means for recognizing and extracting the seismic information have been listed in the program for the development of seismic science and technology published by the five ministries and commissions as an important field to develop and a prior research subject.
A meteorological satellite receiving system has been established since August 2007, and the satellite data received everyday is up to 3G. Hence, about 1000G original data will be received every year which are a large database in addition with 3TB original data received from January 2006 to August 2007. The workload would be extensive if these data were preprocessed in receiving, correcting, backup, and generating images for specific purposes only by manual guard, so it is difficult to ensure the timeliness and reliability of satellite data. This thesis suggests for a model of calibrating the differences of the surface brightness temperature of the geostationary satellite generated by time zone differences, the algorithm of short-period eliminating cloud, the precision orientation algorithm of geostationary satellite image, and resolves the problems of automated noise and cloud elimination, data correction, encoding, decoding and geo-info processing. The studies include processing algorithms, researching, developing and applying the means for processing the geostationary satellite data. Based on the researches, a quasi-real time satellite data auto-processing system has been developed and through the operation of the system, a massive cloud-eliminated database and a suited imagery info database have been set up, containing data from 2006 up to the present.
The quality of the thermal infrared surface brightness temperature data has been the first limitation to the research of seismicity by thermal infrared anomalies. The first important problem to be solved is the noise and interference lines to the original data during the application of automated processing. Aiming at this, this thesis researches and develops the algorithm of automated recognizing and eliminating noise and interfering lines. The second problom is the interference of the cloud layer. If the earth surface is covered by the cloud layer, the thermal infrared information probed by the satellite will be the information of the cloud layer instead of the earth surface. At present, the main means for eliminating the interference of the cloud layer is to compare and analyze the multi-temporal graphs of the same region during a period (e.g. 10 days). Assuming that a region has the weather of cloudless during this period, the image of this period can be used as a part to generate a composite image. For the polar-orbiting satellite used for seismic thermal infrared monitoring, only two-night images (with a remote possibility of three images)for the same region in China one day can be used because of its long revisiting period (the revisiting period is 24 hour for a single satellite). So it will take 10 days to synthesize a large area cloud-eliminated land surface Brightness temperature image,such as the whole China area(for the same receiving point), but hardly including the western region(because the elevation angle of the receiving antenna is small ). Meanwhile, a fewer images for some local areas for pixel comparing lead to the lower quality of cloud-eliminated synthetic image. Thus the consecutive national synthetic land surface brightness temperature images with high quality and a short period are hard to be made. Based on the characters of high time resolution and broad covering scope of the geostationary satellite, this work makes use of the pixel of a larger NE value to replace the pixel of of a smaller NE value according the 2nd thermal channel with the satellite data between 0:00 and 3:00 a.m. every 3-5 days (the influences from sun elevation angle, relative azimuth angle, sunshine and cooling down time are generally the same), and realize the concrete algorithm. The result shows that it is better to synthesize a cloud-eliminated image with every 5 days’satellite data. For the thermal infrared channels, although they are in an atmosphere window, the atmosphere effects still exist(mainly presented as the water absorption), so as to weak the thermal infrared radiation energy received by the satellite sensor. The thesis inverses land surface brightness temperature with the total 211 images at 4:00 a.m. from September 18, 2007 to August 15, 2008 in 9 regions by the split-window method. The result of inversion shows that the atmospheric effects on land surface brightness temperature are about -12~8K. The database of land surface brightness temperature in the mainland of China and adjacent areas is obtained by the above method.
The thesis realizes the transparent gateway with double-export-link based on the Netfilter/Iptables technique according to the need of data sharing system and remote computing, and thus improves visit speed to sharing center of the earthquake geological and seismic dynamics data and reduces network congestion. The new idea of the ArcIMS and. NET Platform integrated development programmes by the use of ArcIMS Servlet Connector connectors is put forward. The advantages are as follows: 1. It retains the development mode of using ArcIMS Servlet Connector; 2. The Asp.net server powerful functionality is integrated into make the user achieve a higher value analysis and calculation; 3. It greatly enhances the development efficiency. The thesis realizes the distributed remote sensing image release and sharing system on the basis of WebGIS according this solution based on the data warehouse formed by the geostationary satellite automatic processing system.
With the developments of information technology, it becomes possible to obtain the magnanimity seismic observation data of high precision, digitization and network. It is the intensively rich Earth's information which promotes earthquake prediction research and Earth science research. By using the modern network information technology, the observation systems, scientific computing systems, database systems and infrastructure resources are connected and shared with each other. The information technology environment of network real-time collaborative study, experiment instrument remote use and resource sharing formed by building the modern earthquake network computing application and network scientific environment platform will enhance scientific and technological innovation capability of earth sciences and earthquake prediction efforts. It is also a part of the national network technology environment and provides information and experiences for its construction. Based on the framework of the state earthquake network computing application system, relying on the network remote computing sub node of Institute of Geology, and daily running of the near-real time processing system of geostationary satellite which is developed independently by ourselves, the thesis builds a data warehouse covering historical magnanimity data, a center of data exchange and data services, and designs the integration framework of Web Service and WebGIS system, develops a remote computing service system for geostationary satellite brightness temperature field and realizes the computing model and computing applications of brightness temperature field of any region for the network client. With the above research, the observation systems, scientific computing systems, database systems and infrastructure resources are connected and shared with each other.
The primary research results are of this work as follows:
(1) It realized the quasi-real time processing system of geostationary satellite with independent intellectual property rights by developing from the bottom with Vc++ platform, and effectively improved the data quality of thermal infrared land surface brightness temperature by realizing the automatic de-noising algorithm, the short-period synthesis eliminating cloud algorithm and the precision orientation algorithm of geostationary satellite image.
(2)It realized the brightness temperature field of geostationary satellite remote computing service, developed the algorithm of extracting brightness temperature data of dynamic area, and provided the computing model and applications of brightness temperature field of any region for the network client by designing the integration framework of Web Service and WebGIS system. The current more mature Web Service and grid computing were preliminarily integrated.
(3) A model of calibrating the differences of the brightness temperature of geostationary satellite generated by time zone differences is suggested for the first time. A total of 16 curves of four positions in four different stages are given through sample statistics of brightness temperature of every 5 days synthetic data which are from four different time zones. The above four stages are made of January -March (Winter), April-June (Spring), July-September (Summer), October-December (Autumn). Three kinds of correct situations and correct formulas based on curves change are able to better eliminate brightness temperature rising or dropping caused by time zone differences.
(4) It gained the brightness temperature changing along with time evolution and spatial distribution through studying on the brightness temperature of 9 monitoring areas data from 2006 to 2008 with data warehouse concept and statistical methods. It presents case study on the earthquake in Yutian, Xinjiang. The result shows that the brightness temperature value at the Kangxiwa fault nearly the epicenter began to increase 35 days before the event. Eight days prior to the shock, this value became much higher than the surroundings, reaching maximum 263.36K 7 days before the event. And 4 hours to the seismic occurrence, this value tended to decline. After the earthquake, it continued to drop by about 4K. The average value of 2008 is 1.1-6.84K higher than 2006 and 3.8-14.2K higher than 2007 in the same period 25 days prior to the shock.
(5) The observation systems, scientific computing systems, database systems and infrastructure resources are connected and shared with each other, by establishing technology environment and platform of seismic network computing applications, and researching how the quasi-real time processing system of geostationary satellite, the remote sensing image release system based on WebGIS, and the remote computing service system cooperate with each other.
我们于2007年8月份架设了风云静止卫星接收系统,每天接收到的卫星数据量多达3G,每年将接收到1000G的原始数据,加上追加的从2006年1月到2007年8月的原始数据3TB,数据量庞大。如果这些数据仅仅依靠人工值守进行接收、校正、备份、专题图生成等预处理,工作量巨大,很难保证卫星数据获取的及时性和可靠性。针对静止卫星数据的特点,本文通过静止卫星数据处理的方法研究、改进和应用,提出了静止卫星地表亮温时区差校正模型,静止卫星短周期去云算法,实现了静止卫星图像精确定位算法,解决了全自动去噪、去云、数据订正、合成、编码、时间解码和地理信息处理等一系列技术问题;在此基础上,从底层开始自主开发了卫星数据准实时自动处理系统,避免了大量的人工操作,获得了大量的、时间上不间断的、空间上覆盖全国的卫星热红外无云遥感影像库,以及相应的、经过适当设计的卫星影像信息库,组成了包含大量历史数据并且具有自动动态更新能力的数据仓库,积累了从2006年至今的数据。
热红外地表亮温数据的质量问题一直是利用热红外遥感数据进行地震活动性热红外异常研究的瓶颈。首先要解决的就是自动化处理应用中遇到的原始数据的噪声和干扰线问题,针对此本文研究和发展噪声、干扰线的自动识别算法并予以消除。其次是云层干扰问题,如果地表上空被云层覆盖,卫星探测到的则是云顶的热红外辐射信息。目前云层消除的主要手段是利用一个时期内(例如十天)同一地区的多景影像进行对比分析。假设在这一时期内任一地段出现过无云天气,则可利用该时段的影像生成合成影像的局部。对于目前地震热红外监测所利用的极轨卫星来说,由于其重访周期长(单颗星,24h),在中国区域内每天夜间对同一地点重复观测的数据两幅(极少时间为3幅),若要获得大面积如全国范围内的无云合成地表亮温大概需要10天左右的数据(对于同一接收点)才能完成,且西部地区很难完全覆盖(卫星接收天线仰角小),局部地区可进行像素比对的图幅数据少,因此利用极轨气象卫星很难得到高质量、短周期的连续的全国合成地表亮温数据。本文根据静止卫星时间分辨率高、覆盖范围大的特点,通过对每3-5天夜间0点-3点的数据(这样无论太阳高度角、相对方位角还是日照、降温时间的影响都是大体相同的)利用热红外通道2辐射值进行比对以NE值大的像素替代NE值小的像素来消除云层实验,得出每5天一个周期进行像素对比合成消除云层能够达到较好的效果,并进行了具体算法实现。对于热红外通道来说虽然处在大气窗区,但仍存在大气影响(主要表现为水汽吸收),使得到达星载传感器的下垫面热红外辐射能量受到了大气削弱。本文利用分裂窗方法,通过对9个监测区样本从2007年9月18日至2008年8月15日夜间4点的共211幅影像数据进行了地表亮温反演,反演结果表明大气对地表亮温会造成-12~8K的影响,本文通过此方法有效地实现了对影像的大气校正,生成了中国区域及邻区的无云地表亮温影像库。
结合亮温场远程计算与数据共享系统的需求,构建了基于Netfilter/Iptables技术的双出口透明网关,提高了地震地质与地震动力学数据共享分中心的访问速度,减少网络拥塞;提出了利用ArcIMS Servlet Connector连接器,把ArcIMS与.NET平台集成开发方案的新思路,这样的优点有:1、保留了利用ArcIMS Servlet Connector的开发方式;2、把Asp.net服务器端的强大功能融合进去,以便用户实现更高级的数值分析、计算;3、大大提高了项目的开发效率。在上述静止卫星自动化处理系统所形成的数据仓库的基础上,依此方案实现了基于WebGIS的分布式热红外遥感影像发布、共享系统。
随着信息技术的发展,高精度、数字化、网络化、海量地震观测数据的获取已经成为可能,正是密集丰富的地球信息促进地震预测预报研究和地球科学研究的发展,利用现代网络信息技术,把观测系统、科学计算系统、数据库系统和基础资源互连互通、资源共享,建立现代地震网络计算应用和网络科技环境平台,实现网络实时协同研究、实验仪器远程使用、资源共享的信息技术环境,提升我国地球科学研究和地震预测等科技创新能力,同时也是我国网络科技环境的有机组成部分,并为国家网络科技环境建设提供参考和经验。本文以国家地震网络计算应用系统大框架为支撑,依托于地质研究所网络远程计算分节点建设,在自主开发的静止卫星准实时处理系统日常运行基础上,设计了涵盖连续历史数据的海量规模的数据仓库、数据交换和数据服务中心,设计了Web Service与WebGIS系统集成框架,开发了静止卫星亮温场远程准实时计算服务系统,实现了为网络客户端提供全国范围内任意自选区域的亮温场、变化场计算模型与计算应用。经过以上方面的研究工作,从而实现了把观测系统、科学计算系统、数据库系统和基础资源互连互通、资源共享。
本文主要取得了如下研究成果:
(1)利用Vc++平台,从底层开发实现了具有自主知识产权的静止卫星数据准实时处理综合系统。通过全自动去噪算法、短周期合成去云算法、静止卫星精确定位算法的实现,有效地提高了热红外地表亮温数据质量,并生成了动态性较强的地表亮温数据库。该系统的完成为地震热红外研究提供了实用的技术手段和技术基础。
(2)以静止卫星数据仓库为支撑,通过Web Service与WebGIS的系统集成,实现了静止亮温场远程计算服务,研究了动态区域亮温信息提取算法、为网络客户端提供全国范围内任意自选区域的亮温场、变化场计算模型与计算应用,把目前较为成熟的Web Service技术和网格计算进行了初步结合应用。
(3)首次提出了静止卫星亮温时区差校正模型。利用静止卫星每5日合成数据对4个不同时区地理位置点的亮温进行年采样统计,得到了自然月1-3月(冬季),4-6月(春季),7-9月(夏季),10-12月(秋季)4个不同阶段4个位置的共16条亮温日变化曲线,从曲线图上可以明显看出时区差对亮温所造成的影响。基于曲线变化规律,给出了亮温时区差校正的3种情况及校正公式。通过上面的校正模型,能够较好地消除不同地方因时区差所造成的亮温的增高和降低。
(4)利用数据仓库理念和统计学方法,对2006年到2008年9个监测区进行了全面研究得出了通常情况下亮温随时间演化和按空间分布的规律。通过对2008年新疆于田地震研究区震前、后的逐幅热红外地表亮温图像解译,2008年震前、震后逐幅数据亮温变化曲线,以及2006-2008年每5日合成数据亮温变化曲线对比分析得知:在震前35天开始,于田地震附近的康西瓦断裂带亮温值明显比周围增高,属于亮温增高阶段;震前8天时间内,于田地震附近的康西瓦断裂带亮温值明显比周围增高,在震前7天亮温达到最高值263.36K;震前4小时于田地震附近的康西瓦断裂带亮温值出现下降趋势。在地震发生后,亮温值开始下降,下降幅度约4K。2008年于田监测区震前25天亮温均值比2006年、2007年同期亮温值分别高出1.1-6.84K,3.8-14.2K。
(5)通过建立地震网络计算应用和网络科技环境平台,对静止卫星数据准实时处理综合系统、基于WebGIS的遥感影像发布系统、远程计算服务系统进行了网络实时协同研究,从而实现了把观测系统、科学计算系统、数据库系统和基础资源互连互通、资源共享。
Satellitic thermal infrared remote sensing has become a promising technique for monitoring fault activities and earthquake precursors for its many advantages, such as a wide field of vision, high spatial resolution, short observation period, and also owing to its good reflection to thermal infrared anomalies of some major earthquakes. However, the thermal thermal infrared radiation of the earth’s surface is influenced by the external non-seismic factors, such as cloud layers, terrain, object styles, and weathe. All the non-seismic factors cannot be excluded only with the satellite data in a period around the earthquake. A general research on the historic satellite data of at least two years using temporal and spatial compositive analysis of statistics is of great necessity to find out the universal features. For seismic thermal infrared remote sensing, the time resolution of the geostationary satellite is higher than that of the polar-orbiting satellite (a panorama graph which covers about 1/3 of the whole earth can be captured each half hour during the flood season or each hour during the non-flood season), which is favorable to generating short period and high quality brightness temperature data over all the surface of China and capturing the earthquake precursor information. Nevertheless, the lack of the seismology oriented extensive satellite data processing system and a massive professional data warehouse needed by seismologists has seriously restricted the research. The observation and application technology with satellitic thermal infrared remote sensing has been listed in the medium- and long-term program for the development of science and technology in China and the plans for earthquake prevention and disaster reduction. Moreover, the satellitic thermal infrared remote sensing, the ground application system, the technology for processing the space-earth Integration observation data, and the means for recognizing and extracting the seismic information have been listed in the program for the development of seismic science and technology published by the five ministries and commissions as an important field to develop and a prior research subject.
A meteorological satellite receiving system has been established since August 2007, and the satellite data received everyday is up to 3G. Hence, about 1000G original data will be received every year which are a large database in addition with 3TB original data received from January 2006 to August 2007. The workload would be extensive if these data were preprocessed in receiving, correcting, backup, and generating images for specific purposes only by manual guard, so it is difficult to ensure the timeliness and reliability of satellite data. This thesis suggests for a model of calibrating the differences of the surface brightness temperature of the geostationary satellite generated by time zone differences, the algorithm of short-period eliminating cloud, the precision orientation algorithm of geostationary satellite image, and resolves the problems of automated noise and cloud elimination, data correction, encoding, decoding and geo-info processing. The studies include processing algorithms, researching, developing and applying the means for processing the geostationary satellite data. Based on the researches, a quasi-real time satellite data auto-processing system has been developed and through the operation of the system, a massive cloud-eliminated database and a suited imagery info database have been set up, containing data from 2006 up to the present.
The quality of the thermal infrared surface brightness temperature data has been the first limitation to the research of seismicity by thermal infrared anomalies. The first important problem to be solved is the noise and interference lines to the original data during the application of automated processing. Aiming at this, this thesis researches and develops the algorithm of automated recognizing and eliminating noise and interfering lines. The second problom is the interference of the cloud layer. If the earth surface is covered by the cloud layer, the thermal infrared information probed by the satellite will be the information of the cloud layer instead of the earth surface. At present, the main means for eliminating the interference of the cloud layer is to compare and analyze the multi-temporal graphs of the same region during a period (e.g. 10 days). Assuming that a region has the weather of cloudless during this period, the image of this period can be used as a part to generate a composite image. For the polar-orbiting satellite used for seismic thermal infrared monitoring, only two-night images (with a remote possibility of three images)for the same region in China one day can be used because of its long revisiting period (the revisiting period is 24 hour for a single satellite). So it will take 10 days to synthesize a large area cloud-eliminated land surface Brightness temperature image,such as the whole China area(for the same receiving point), but hardly including the western region(because the elevation angle of the receiving antenna is small ). Meanwhile, a fewer images for some local areas for pixel comparing lead to the lower quality of cloud-eliminated synthetic image. Thus the consecutive national synthetic land surface brightness temperature images with high quality and a short period are hard to be made. Based on the characters of high time resolution and broad covering scope of the geostationary satellite, this work makes use of the pixel of a larger NE value to replace the pixel of of a smaller NE value according the 2nd thermal channel with the satellite data between 0:00 and 3:00 a.m. every 3-5 days (the influences from sun elevation angle, relative azimuth angle, sunshine and cooling down time are generally the same), and realize the concrete algorithm. The result shows that it is better to synthesize a cloud-eliminated image with every 5 days’satellite data. For the thermal infrared channels, although they are in an atmosphere window, the atmosphere effects still exist(mainly presented as the water absorption), so as to weak the thermal infrared radiation energy received by the satellite sensor. The thesis inverses land surface brightness temperature with the total 211 images at 4:00 a.m. from September 18, 2007 to August 15, 2008 in 9 regions by the split-window method. The result of inversion shows that the atmospheric effects on land surface brightness temperature are about -12~8K. The database of land surface brightness temperature in the mainland of China and adjacent areas is obtained by the above method.
The thesis realizes the transparent gateway with double-export-link based on the Netfilter/Iptables technique according to the need of data sharing system and remote computing, and thus improves visit speed to sharing center of the earthquake geological and seismic dynamics data and reduces network congestion. The new idea of the ArcIMS and. NET Platform integrated development programmes by the use of ArcIMS Servlet Connector connectors is put forward. The advantages are as follows: 1. It retains the development mode of using ArcIMS Servlet Connector; 2. The Asp.net server powerful functionality is integrated into make the user achieve a higher value analysis and calculation; 3. It greatly enhances the development efficiency. The thesis realizes the distributed remote sensing image release and sharing system on the basis of WebGIS according this solution based on the data warehouse formed by the geostationary satellite automatic processing system.
With the developments of information technology, it becomes possible to obtain the magnanimity seismic observation data of high precision, digitization and network. It is the intensively rich Earth's information which promotes earthquake prediction research and Earth science research. By using the modern network information technology, the observation systems, scientific computing systems, database systems and infrastructure resources are connected and shared with each other. The information technology environment of network real-time collaborative study, experiment instrument remote use and resource sharing formed by building the modern earthquake network computing application and network scientific environment platform will enhance scientific and technological innovation capability of earth sciences and earthquake prediction efforts. It is also a part of the national network technology environment and provides information and experiences for its construction. Based on the framework of the state earthquake network computing application system, relying on the network remote computing sub node of Institute of Geology, and daily running of the near-real time processing system of geostationary satellite which is developed independently by ourselves, the thesis builds a data warehouse covering historical magnanimity data, a center of data exchange and data services, and designs the integration framework of Web Service and WebGIS system, develops a remote computing service system for geostationary satellite brightness temperature field and realizes the computing model and computing applications of brightness temperature field of any region for the network client. With the above research, the observation systems, scientific computing systems, database systems and infrastructure resources are connected and shared with each other.
The primary research results are of this work as follows:
(1) It realized the quasi-real time processing system of geostationary satellite with independent intellectual property rights by developing from the bottom with Vc++ platform, and effectively improved the data quality of thermal infrared land surface brightness temperature by realizing the automatic de-noising algorithm, the short-period synthesis eliminating cloud algorithm and the precision orientation algorithm of geostationary satellite image.
(2)It realized the brightness temperature field of geostationary satellite remote computing service, developed the algorithm of extracting brightness temperature data of dynamic area, and provided the computing model and applications of brightness temperature field of any region for the network client by designing the integration framework of Web Service and WebGIS system. The current more mature Web Service and grid computing were preliminarily integrated.
(3) A model of calibrating the differences of the brightness temperature of geostationary satellite generated by time zone differences is suggested for the first time. A total of 16 curves of four positions in four different stages are given through sample statistics of brightness temperature of every 5 days synthetic data which are from four different time zones. The above four stages are made of January -March (Winter), April-June (Spring), July-September (Summer), October-December (Autumn). Three kinds of correct situations and correct formulas based on curves change are able to better eliminate brightness temperature rising or dropping caused by time zone differences.
(4) It gained the brightness temperature changing along with time evolution and spatial distribution through studying on the brightness temperature of 9 monitoring areas data from 2006 to 2008 with data warehouse concept and statistical methods. It presents case study on the earthquake in Yutian, Xinjiang. The result shows that the brightness temperature value at the Kangxiwa fault nearly the epicenter began to increase 35 days before the event. Eight days prior to the shock, this value became much higher than the surroundings, reaching maximum 263.36K 7 days before the event. And 4 hours to the seismic occurrence, this value tended to decline. After the earthquake, it continued to drop by about 4K. The average value of 2008 is 1.1-6.84K higher than 2006 and 3.8-14.2K higher than 2007 in the same period 25 days prior to the shock.
(5) The observation systems, scientific computing systems, database systems and infrastructure resources are connected and shared with each other, by establishing technology environment and platform of seismic network computing applications, and researching how the quasi-real time processing system of geostationary satellite, the remote sensing image release system based on WebGIS, and the remote computing service system cooperate with each other.
引文
1.陈渭民,夏浣清,陈光宇,等.卫星气象学[M].北京:气象出版社, 1989.
2.强祖基,徐秀登,赁常恭.卫星热红外异常—临震前兆[J].科学通报, 1990, 135(17):46-49.
3.叶民权,吴其勇,杨忠东.卫星热红外异常与强震关系研究实例[J].科学通报, 1994,39(22):2074-2077.
4. Rao P K,等编.气象卫星-系统、资料及其在环境中的应用[M].许健民等译.北京:气象出版社, 1994.
5.刘春生,等.火情监测系统[J].黑龙江气象, 1995, 2:29-41.
6.郭跃宏,阎民正,白晓勤,等.试谈卫星遥感(热红外)技术在山西地震重点监视防御区的应用[J].山西地震, 1996, 3:2-12.
7.孙涵,居为民,汤志成.气象卫星遥感资料微机处理系统(V312)简介[J].气象, 1997, 23(12):18-20.
8.刘文.静止气象卫星资料精处理方法研究[J].山东气象, 1997,17(2):37-40.
9.吕琪琦,丁鉴海,崔承,等,张北6.2级地震前的卫星热红外异常[J].地震, 1998, 18(3):240-244.
10.贾晋康.卫星遥感热红外辐射观测在地震监测预报中的应用(综述)[J].四川地震, 1998, 3:1-5.
11.王炳忠,太阳辐射计算讲座第一讲太阳能中天文参数的计算[J].太阳能, 1999, (02).
12.刘玉洁,杨忠东. MODIS遥感信息处理原理与算法[M].北京:科学出版社, 2001.
13.陆风,许健民,张其松.风云二号气象卫星姿态和沿步进方向失配角参数对图像影响的模拟研究[J].应用气象学报, 2001, 12(4):393-399.
14.周成虎,等.遥感影像地学理解与分析[M].北京:科学出版社, 2001.
15.刘放,程万正,张永久,等.卫星遥感热红外辐射与川滇强震探讨[J].地震, 2001, 21(2):65-69.
16.孙延明,等.异地并行设计中WEB数据库设计[J].计算机工程与应用, 2001, 37(22):111-113.
17.何明元,石汉青.静止气象卫星资料处理[J].解放军理工大学学报(自然科学版), 2002, 3(1):75-78.
18.张元生,沈文荣,徐辉.新青8.1级地震前卫星热红外异常[J].西北地震学报, 2002,24 (1):1-6.
19.徐秀登,钟韵.南黄海6.1级地震前热红外异常[J].地震学刊, 2002, 22(4):1-6.
20.陈云浩,王洁,李晓兵.夏季城市热场的卫星遥感分析[J].国土资源遥感, 2002, 4:55-59.
21.彭木根.数据仓库技术与实现[M ].北京:电子工业出版社, 2002.
22.武森,高学东.数据仓库与数据挖掘[M ],北京:冶金出版社, 2003, 9:141- 142.
23.陈渭民.卫星气象学[M].北京:气象出版社, 2003.
24.陈世平,杨秉新,王怀义,等.空间相机设计与试验[M].北京:宇航出版社, 2003.
25. Deitel H M, Deitel P J, Listfield J A, Nieto T R, Yaeger G H, Zlatkina M. C#高级程序员指南[M].周靖,姜昊,龙劲松译.北京:清华大学出版社, 2003.
26.邓志辉,王煜,陈梅花,等.中国大陆几次强地震活动的卫星红外异常分析[J].地震地质, 2003, 25(2): 327-337.
27.陈梅花,邓志辉,贾庆华.地震前卫星红外异常与发震断裂的关系研究[J].地震地质, 2003, 25(1): 100-108.
28.刘放,程万正,但尚铭.卫星遥感热红外辐射信息与云南永胜6.0级地震[J].地震研究, 2003, 26(2): 120-125.
29.康春丽,陈正位,陈立泽,等.昆仑山口西8.1级地震的卫星热红外前兆特征分析[J].西北地震学报, 2003, 25(1):12-17.
30.王玲,龚健雅.基于HDF文件的组织方式与影像提取[J].测绘通报, 2003, 4: 35-37.
31.李柳霞. MODIS影像数据预处理技术研究[D].北京:中国农业大学, 2004.
32.乐德广,郭东辉,吴伯僖.基于Netfilter的NAT技术及其应用[J].计算机工程, 2004, 30(4):35-37.
33.杨青生,刘闯. MODIS数据陆面温度反演研究[J].遥感技术与应用, 2004, 19(2):90-94
34.胡震峰.热红外遥感应用研究[J].科技傅报开发与经济, 2004, 14(1):143-145.
35.孙达,蒲英霞.地图投影[M].南京:南京大学出版社, 2005.
36.李卿,王介康,曹亮. FY-2C业务静止气象卫星及发展展望[J].上海航天, 2005[增刊]:1-8.
37.张如意,王玉花. FY-2C星辐射定标及其结果分析[J].上海航天, 2005[增刊]:31-35.
38.贾卡乐. J2EE和CORBA集成的HDF数据发布平台的研究[D].武汉:华中科技大学, 2005.
39.黄康,史周. ArcIMS原理分析及应用开发[J].地球信息科学, 2005, 7(3):61-66.
40.马照松,单新建,吴云.热红外极轨卫星地震监测系统综合技术研究[J].大地测量与地球动力学, 2005, 25(2):52-57.
41.徐希孺.遥感物理[M].北京:北京大学出版社, 2005.
42.郭晓,张元生,钟美娇.卫星热红外遥感资料在地震预报中的应用研究[J].西北地震学报, 2005, 27(3): 223-227.
43.单新建,屈春燕,马瑾.卫星热红外观测与发震断层不同段落交替活动特征分析[J].大地测量与地球动力学, 2005, 25(2):58-62.
44.郭卫英,单新建.应用多种遥感影像处理方法提取玛尼7.5级地震中的热红外异常信息[J].内陆地震, 2005, 19(2):142-148.
45.风云二号C卫星业务产品.国家卫星气象中心(NSMC), 2005-6-26.
46.田国良等,热红外遥感[M].北京:电子工业出版社, 2006:1-23.
47.姜云鹏,实现ArcIMS企业级分布式部[EB/OL]. http://blog.csdn.net/vistawn., 2006-09.
48.马照松.卫星热红外准实时数据处理综合技术与异常提取模型研究及其应用[D].北京:中国地震局地质研究所, 2006.
49.陈顺云,马瑾,刘力强,等.巴基斯坦地震前热红外辐射增强现象[J].自然科学进展, 2006, 16(11): 1487-1490.
50.屈春燕,单新建,马瑾.红河断裂热红外高温条带的成因及其与地震活动性关系的探讨[J].地震学报, 2006, 28(1):91-97.
51.屈春燕,马瑾,单新建.一次卫星热红外地震前兆现象的证伪[J].地球物理学报, 2006, 49(2):490-495.
52.屈春燕,单新建,马瑾.地震活动性热红外异常提取方法研究[J].地球科学进展, 2006, 21(7):699-705.
53.李卫东,余志伟.基于GIS的矿产资源勘探信息系统设计与应用[A].见中国矿业大学出版社.煤炭资源与安全开采技术新进展[C].江苏徐州:中国矿业大学出版社, 2007:191-198.
54. MODIS卫星遥感热红外数据处理与应用系统[J].红外, 2007, 11.
55.李卫东,单新建.基于Web Services的多源异构空间信息集成框架[J].微计算机信息, 2008, 24(7-3): 14-16.
56.李卫东,单新建,张国宏. ArcIMS添加服务器端动态图层技术的实现[J].微计算机信息, 2008, 24(3-1): 148-150.
57.李卫东,单新建,张国宏等. ArcIMS与MapObjects分布式集成框架设计与应用[J].计算机应用研究, 2008, 25(增刊):1785-1786.
58.杨素娣,崔冬,张强.一种改进的基于边界追踪的区域统计算法[J].计算机应用与软件, 2008, 25(3): 208-211.
59. Chandrasekhar S. Radiative transfer[M]. New York:Dover, 1960.
60. McMillin L. M., Estmiation of sea surfaceTemperature from two infrared window measurements with different absorption, J.G.R., 1975, 80(36):5113-5117.
61. pavlidis T. Filling algorithms for raster graphics[J]. Comput Graph Image Process, 1979, 10:126-141.
62. Pavlidis T. Algorithms for Graphics and Image Processing[M]. Computer Science Press, aryland, 1982(Chapter8).
63. Price J C. Land Surface Temperature Measurements from the Split Window Channels of the NOAA -7 AVHRR[J]. Journal of Geophysical Research, 1984, 89(D5):7231-7237.
64. McClain E P, Piehel W G, Walton C C. Comparative performance of AVHRR based multichannel sea surface temperatures[J]. .J.Geophys.Res. , 1985, 90(c6):11587-11601.
65. Snyder, J. P. Map Projections--A Working Manual[M]. U. S. Geological Survey Professional Paper 1395. Washington, DC:U. S. Government Printing Office, 1987:182-190.
66. B.И.Горкийидр.ухоаящееинфрасноеизичениеземли–индикаторсейсмическойактивности.Док. AH CCCP, 1988, 301(1):67-69.
67. Tsukasa Hosomura, Haruhisa Shimoda and Toshibumi Sakata. Generation of cloud free image from NOAA AVHRR data[A]. The 11th Asian Conference on Remote Sensing, November 15, 1990, Guangzhou, China.
25(2): 52-57.
68. Burtsev S V, Kuzmin Y P. An efficient flood-filling algorithm[J]. Comput Graph, 1993, 17:549-561.
69. Lejun S, Hao Z. A new contour fill algorithm for outlined character image generation[J]. Comput Graph. 1995, 19:551-556.
70. Andreas Bitterer, et al. VisualAge and Transaction Processing in a Client/server Environment. Prentice Hall PTR, First Edition, 1998, 7:126-128.
71. NCSA: HDF Specification and Developer’s Guide, Version 4.1r5 ? November 2001.
72. NCSA: HDF User’s Guide, HDF Version 4.2 Release 0 ? December 2003.
73. ESRI INC. ArcIMS 9 Customizing the HTML Viewer[z]. ESRI, CA. 2004.
74. ESRI INC . ArcIMS 9 ArcXML programmer’s Reference Guide. ESRI, CA. 2004.
75. NCSA: HDF Reference Manual, HDF Version 4.2 Release 1 ? March 2005.
76. http://www.netfilter.org/documentation/HOWTO//packet-filtering-HOWTO.html. 2008-06.
77. http://www.netfilter.org/documentation/HOWTO//netfilter-hacking-HOWTO.html. 2008-06.
78. http://msdn.microsoft.com/library/en-us/fileio/fs/obtaining_directory_change_notifications.asp, 2008.
79. http://nsmc.cma.gov.cn/item/center_news_tip.asp?number=20070720081931.
80. Rusty Russell. Linux 2.4 Packet Filtering HOWTO[EB/OL].
81. Rusty Russell and Harald Welte. Linux netfilter Hacking HOWTO[EB/OL].
82. The DOE Common Component Architecture Project, http://www.extreme.indiana.edu/~gannon/cca_report.html.
2.强祖基,徐秀登,赁常恭.卫星热红外异常—临震前兆[J].科学通报, 1990, 135(17):46-49.
3.叶民权,吴其勇,杨忠东.卫星热红外异常与强震关系研究实例[J].科学通报, 1994,39(22):2074-2077.
4. Rao P K,等编.气象卫星-系统、资料及其在环境中的应用[M].许健民等译.北京:气象出版社, 1994.
5.刘春生,等.火情监测系统[J].黑龙江气象, 1995, 2:29-41.
6.郭跃宏,阎民正,白晓勤,等.试谈卫星遥感(热红外)技术在山西地震重点监视防御区的应用[J].山西地震, 1996, 3:2-12.
7.孙涵,居为民,汤志成.气象卫星遥感资料微机处理系统(V312)简介[J].气象, 1997, 23(12):18-20.
8.刘文.静止气象卫星资料精处理方法研究[J].山东气象, 1997,17(2):37-40.
9.吕琪琦,丁鉴海,崔承,等,张北6.2级地震前的卫星热红外异常[J].地震, 1998, 18(3):240-244.
10.贾晋康.卫星遥感热红外辐射观测在地震监测预报中的应用(综述)[J].四川地震, 1998, 3:1-5.
11.王炳忠,太阳辐射计算讲座第一讲太阳能中天文参数的计算[J].太阳能, 1999, (02).
12.刘玉洁,杨忠东. MODIS遥感信息处理原理与算法[M].北京:科学出版社, 2001.
13.陆风,许健民,张其松.风云二号气象卫星姿态和沿步进方向失配角参数对图像影响的模拟研究[J].应用气象学报, 2001, 12(4):393-399.
14.周成虎,等.遥感影像地学理解与分析[M].北京:科学出版社, 2001.
15.刘放,程万正,张永久,等.卫星遥感热红外辐射与川滇强震探讨[J].地震, 2001, 21(2):65-69.
16.孙延明,等.异地并行设计中WEB数据库设计[J].计算机工程与应用, 2001, 37(22):111-113.
17.何明元,石汉青.静止气象卫星资料处理[J].解放军理工大学学报(自然科学版), 2002, 3(1):75-78.
18.张元生,沈文荣,徐辉.新青8.1级地震前卫星热红外异常[J].西北地震学报, 2002,24 (1):1-6.
19.徐秀登,钟韵.南黄海6.1级地震前热红外异常[J].地震学刊, 2002, 22(4):1-6.
20.陈云浩,王洁,李晓兵.夏季城市热场的卫星遥感分析[J].国土资源遥感, 2002, 4:55-59.
21.彭木根.数据仓库技术与实现[M ].北京:电子工业出版社, 2002.
22.武森,高学东.数据仓库与数据挖掘[M ],北京:冶金出版社, 2003, 9:141- 142.
23.陈渭民.卫星气象学[M].北京:气象出版社, 2003.
24.陈世平,杨秉新,王怀义,等.空间相机设计与试验[M].北京:宇航出版社, 2003.
25. Deitel H M, Deitel P J, Listfield J A, Nieto T R, Yaeger G H, Zlatkina M. C#高级程序员指南[M].周靖,姜昊,龙劲松译.北京:清华大学出版社, 2003.
26.邓志辉,王煜,陈梅花,等.中国大陆几次强地震活动的卫星红外异常分析[J].地震地质, 2003, 25(2): 327-337.
27.陈梅花,邓志辉,贾庆华.地震前卫星红外异常与发震断裂的关系研究[J].地震地质, 2003, 25(1): 100-108.
28.刘放,程万正,但尚铭.卫星遥感热红外辐射信息与云南永胜6.0级地震[J].地震研究, 2003, 26(2): 120-125.
29.康春丽,陈正位,陈立泽,等.昆仑山口西8.1级地震的卫星热红外前兆特征分析[J].西北地震学报, 2003, 25(1):12-17.
30.王玲,龚健雅.基于HDF文件的组织方式与影像提取[J].测绘通报, 2003, 4: 35-37.
31.李柳霞. MODIS影像数据预处理技术研究[D].北京:中国农业大学, 2004.
32.乐德广,郭东辉,吴伯僖.基于Netfilter的NAT技术及其应用[J].计算机工程, 2004, 30(4):35-37.
33.杨青生,刘闯. MODIS数据陆面温度反演研究[J].遥感技术与应用, 2004, 19(2):90-94
34.胡震峰.热红外遥感应用研究[J].科技傅报开发与经济, 2004, 14(1):143-145.
35.孙达,蒲英霞.地图投影[M].南京:南京大学出版社, 2005.
36.李卿,王介康,曹亮. FY-2C业务静止气象卫星及发展展望[J].上海航天, 2005[增刊]:1-8.
37.张如意,王玉花. FY-2C星辐射定标及其结果分析[J].上海航天, 2005[增刊]:31-35.
38.贾卡乐. J2EE和CORBA集成的HDF数据发布平台的研究[D].武汉:华中科技大学, 2005.
39.黄康,史周. ArcIMS原理分析及应用开发[J].地球信息科学, 2005, 7(3):61-66.
40.马照松,单新建,吴云.热红外极轨卫星地震监测系统综合技术研究[J].大地测量与地球动力学, 2005, 25(2):52-57.
41.徐希孺.遥感物理[M].北京:北京大学出版社, 2005.
42.郭晓,张元生,钟美娇.卫星热红外遥感资料在地震预报中的应用研究[J].西北地震学报, 2005, 27(3): 223-227.
43.单新建,屈春燕,马瑾.卫星热红外观测与发震断层不同段落交替活动特征分析[J].大地测量与地球动力学, 2005, 25(2):58-62.
44.郭卫英,单新建.应用多种遥感影像处理方法提取玛尼7.5级地震中的热红外异常信息[J].内陆地震, 2005, 19(2):142-148.
45.风云二号C卫星业务产品.国家卫星气象中心(NSMC), 2005-6-26.
46.田国良等,热红外遥感[M].北京:电子工业出版社, 2006:1-23.
47.姜云鹏,实现ArcIMS企业级分布式部[EB/OL]. http://blog.csdn.net/vistawn., 2006-09.
48.马照松.卫星热红外准实时数据处理综合技术与异常提取模型研究及其应用[D].北京:中国地震局地质研究所, 2006.
49.陈顺云,马瑾,刘力强,等.巴基斯坦地震前热红外辐射增强现象[J].自然科学进展, 2006, 16(11): 1487-1490.
50.屈春燕,单新建,马瑾.红河断裂热红外高温条带的成因及其与地震活动性关系的探讨[J].地震学报, 2006, 28(1):91-97.
51.屈春燕,马瑾,单新建.一次卫星热红外地震前兆现象的证伪[J].地球物理学报, 2006, 49(2):490-495.
52.屈春燕,单新建,马瑾.地震活动性热红外异常提取方法研究[J].地球科学进展, 2006, 21(7):699-705.
53.李卫东,余志伟.基于GIS的矿产资源勘探信息系统设计与应用[A].见中国矿业大学出版社.煤炭资源与安全开采技术新进展[C].江苏徐州:中国矿业大学出版社, 2007:191-198.
54. MODIS卫星遥感热红外数据处理与应用系统[J].红外, 2007, 11.
55.李卫东,单新建.基于Web Services的多源异构空间信息集成框架[J].微计算机信息, 2008, 24(7-3): 14-16.
56.李卫东,单新建,张国宏. ArcIMS添加服务器端动态图层技术的实现[J].微计算机信息, 2008, 24(3-1): 148-150.
57.李卫东,单新建,张国宏等. ArcIMS与MapObjects分布式集成框架设计与应用[J].计算机应用研究, 2008, 25(增刊):1785-1786.
58.杨素娣,崔冬,张强.一种改进的基于边界追踪的区域统计算法[J].计算机应用与软件, 2008, 25(3): 208-211.
59. Chandrasekhar S. Radiative transfer[M]. New York:Dover, 1960.
60. McMillin L. M., Estmiation of sea surfaceTemperature from two infrared window measurements with different absorption, J.G.R., 1975, 80(36):5113-5117.
61. pavlidis T. Filling algorithms for raster graphics[J]. Comput Graph Image Process, 1979, 10:126-141.
62. Pavlidis T. Algorithms for Graphics and Image Processing[M]. Computer Science Press, aryland, 1982(Chapter8).
63. Price J C. Land Surface Temperature Measurements from the Split Window Channels of the NOAA -7 AVHRR[J]. Journal of Geophysical Research, 1984, 89(D5):7231-7237.
64. McClain E P, Piehel W G, Walton C C. Comparative performance of AVHRR based multichannel sea surface temperatures[J]. .J.Geophys.Res. , 1985, 90(c6):11587-11601.
65. Snyder, J. P. Map Projections--A Working Manual[M]. U. S. Geological Survey Professional Paper 1395. Washington, DC:U. S. Government Printing Office, 1987:182-190.
66. B.И.Горкийидр.ухоаящееинфрасноеизичениеземли–индикаторсейсмическойактивности.Док. AH CCCP, 1988, 301(1):67-69.
67. Tsukasa Hosomura, Haruhisa Shimoda and Toshibumi Sakata. Generation of cloud free image from NOAA AVHRR data[A]. The 11th Asian Conference on Remote Sensing, November 15, 1990, Guangzhou, China.
25(2): 52-57.
68. Burtsev S V, Kuzmin Y P. An efficient flood-filling algorithm[J]. Comput Graph, 1993, 17:549-561.
69. Lejun S, Hao Z. A new contour fill algorithm for outlined character image generation[J]. Comput Graph. 1995, 19:551-556.
70. Andreas Bitterer, et al. VisualAge and Transaction Processing in a Client/server Environment. Prentice Hall PTR, First Edition, 1998, 7:126-128.
71. NCSA: HDF Specification and Developer’s Guide, Version 4.1r5 ? November 2001.
72. NCSA: HDF User’s Guide, HDF Version 4.2 Release 0 ? December 2003.
73. ESRI INC. ArcIMS 9 Customizing the HTML Viewer[z]. ESRI, CA. 2004.
74. ESRI INC . ArcIMS 9 ArcXML programmer’s Reference Guide. ESRI, CA. 2004.
75. NCSA: HDF Reference Manual, HDF Version 4.2 Release 1 ? March 2005.
76. http://www.netfilter.org/documentation/HOWTO//packet-filtering-HOWTO.html. 2008-06.
77. http://www.netfilter.org/documentation/HOWTO//netfilter-hacking-HOWTO.html. 2008-06.
78. http://msdn.microsoft.com/library/en-us/fileio/fs/obtaining_directory_change_notifications.asp, 2008.
79. http://nsmc.cma.gov.cn/item/center_news_tip.asp?number=20070720081931.
80. Rusty Russell. Linux 2.4 Packet Filtering HOWTO[EB/OL].
81. Rusty Russell and Harald Welte. Linux netfilter Hacking HOWTO[EB/OL].
82. The DOE Common Component Architecture Project, http://www.extreme.indiana.edu/~gannon/cca_report.html.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |