北京一地基微波辐射计的观测数据一致性分析和订正实验

基于辐射传输理论,以地基微波辐射计亮温数据质量控制研究为目的,以北京一台多通道微波辐射计为例,对其2010和2011年每天8:00和20:00(BT)的“晴空”观测亮温数据进行了分析,并利用独立来源的大气层结资料通过辐射传输方程进行亮温模拟计算,检验了亮温数据的“晴空”观测和数值模拟结果之间的一致性,发现了因“定标”和“搬迁”引起的数据不连续和不一致问题,考虑到“定标”使观测和数值模拟结果之间的一致性优于定标之前而“搬迁”改变的是地基微波辐射计的工作环境,通过对观测数据进行分段拟合订正,改善了观测数据的连续性和一致性。该研究对基于辐射传输理论的观测数据质量控制和提高观测资料的可利用性有参考价值。     

神舟4号”飞船微波辐射计亮温反演海面温度、风速和大气水汽含量

“神舟4号”飞船微波辐射计是我国自行研制的第一个星载被动微波遥感器。自从“神舟4号”飞船发射以后,RAD获得了大量的地球表面南北纬40°以内的不同通道的微波辐射电压数据。通过定标调整,得到地球表面的微波辐射亮温。利用同步的RAD和TMI产品数据,建立了海面温度、风速和大气水汽含量的反演算法。然后利用TMI数据产品对反演算法进行了检验。结果表明二者具有很好的一致性,在无雨的情况下,海面温度、风速和大气水汽含量的均方根误差分别为1.40℃、0.35ms和2.71mm。     

微波月亮-人类对月球的全新视角——中国“嫦娥一号”卫星微波探测仪若干探测结果

中国“嫦娥一号”探月卫星自2007年10月24日成功发射并于同年11月7日进入其工作轨道。在轨工作一年多,完成了全部使命,期间获取了大量的科学数据。其中“嫦娥一号”月球微波探测仪(Chang’e-1 Lunar Microwave Sounder-CELMS)已多次覆盖全月表面,首次获取了全月微波亮温分布数据,创建了“微波月亮”(Microwave Moon-MicM)。“微波月亮”的建立为月球科学研究、宇宙科学研究、月球资源研究及应用、未来月球基地的建立等带来了全新的信息,与“可见月亮”、“红外月亮”及其它相关探测结果(如X、γ谱仪,中子谱仪)、地基探测及未来月球轨道上观测和就位探测等多方信息的融合、分析,将大大提升人类对太空、月球及宇宙起源、生命起源等问题的认识和研究水平,在人类探月活动中具有里程碑意义。
在“嫦娥一号”卫星微波探测仪绕月探测之前,从来没有从月球轨道对全月球进行微波探测的活动。很多涉及月球微波特征研究,如月表微波亮温分布、月壤厚度及氦-3资源量分布信息、涉及月球历史等的研究多数是靠Apollo、Luna的落月点实测数据为依据,加上其它探测(如光学等)结果融合分析并逻辑延伸而得来的,因此其结果存在相当的多解或不确定性,这就使我们对月球微波辐射特性的真实情况了解很少,甚至可能有偏差。着重讨论“微波月亮”的含义,其相关信息内涵,几种特征区、点的分析等。根据微波探测仪的数据,获得了全月月壤厚度分布、氦-3资源量评估、全月亮温及其变化规律等研究结果,得出了一些与现今其它研究结果不同的结论。     

一种适于移动设备的全景图快速拼接方法

针对传统移动端全景图生成方法存在拼接速度慢、消耗内存以及存在接缝和“鬼影”等问题,提出了一种适用于移动设备的全景图生成算法。算法首先对源序列图像进行色彩校正,从而保证色彩及亮度均匀,以缩短后期图像融合时间;然后在全景图拼接过程中检测“鬼影”,同时运用梯度域目标移除和区域填充方法移除“鬼影”,利用泊松融合进行拼接后的平滑处理;同时在图像拼接过程中优化了内存分配机制,以减少在图像拼接过程中的内存消耗。通过编程实现了该算法,在配置为332MHz处理器和128MB内存的手机上对不同光照下拍摄的分辨率为1280×720的照片进行测试,并与传统的全局全景图拼接算法进行对比,若利用全局全景图拼接算法对2至9张源序列图像进行拼接,内存消耗为12.3~23.6MB,而提出的算法占用更少内存,分别为9.9~14.5MB。实验结果表明该方法消除图像接缝及“鬼影”较彻底,拼接速度快且节省内存,生成的最终全景图质量较好,可用于移动设备上的全景图拼接。     

基于混沌和图像内容的脆弱水印方案

针对脆弱水印方案的“伪认证攻击”问题,提出了基于混沌和图像内容的脆弱水印方案。该方案基于矩阵奇异值的特性,选取与图像内容密切相关的图像矩阵奇异值作为水印,并用混沌系统对其加密增强水印的安全性。认证时通过水印差别图和奇异值差值双重比较来抵抗简单脆弱水印嵌入方法的“伪认证攻击”。理论分析和仿真实验表明:该算法能有效地抵抗“伪认证攻击”,具有更好的安全性能。     

基于高空间分辨率的热污染遥感监测研究进展

综述了卫星遥感热红外海表温度反演原理,并对海表温度中的“皮温”和“体温”进行了界定;着重总结了热红外遥感海表温度反演的主要方法-单通道法、分裂窗法、多角度法等;详细介绍了具有较高热红外通道空间分辨率卫星传感器Landsat TM/ETM+、CBERS-02 IRMSS、ASTER、HJ-1B IRS的海表温度反演算法,并对各卫星热红外通道特点进行了对比;最后,对影响热红外温度反演精度的因素进行了简要分析,指出了目前研究存在的问题并对未来的研究方向进行了展望。     

汶川地震道路震害高分辨率遥感信息提取方法探讨

发生在四川省汶川县的“5.12”大地震给四川乃至全国带来了巨大的损失,道路是本次抗震救灾过程中的“生命线”,如何对道路的损毁状况进行快速准确的监测成为抗震救灾的一项重要工作。以汶川地震的重灾区--北川县为研究对象,利用震前震后的高分辨率遥感影像,通过面向对象的图像分类方法进行道路识别,并通过震前道路识别结果与震后影像的叠加和震前震后道路识别结果的变化检测提取出损毁的路段。信息提取的结果已在第一时间提交给相关部门,为生命线的尽快抢通提供了及时、科学的依据。     

图形演化下的图学学科

本文回顾了人类在适应自然、改造自然的过程中对图形的需求以及图形的发展对 社会进步的作用,从图形引出文字、图形引出数字的本源出发,追溯图之源。用一个“形” 、 “意” 、 “元” 、“用”四维结构演绎图形的属性、地位和作用,并从这 4 个维度分析图形的演化过程, 揭示了图形在“形”维度的高维化、“意”维度的深度化、“元”维度的融合化和“用”维度的 渗透化的发展趋势。阐述了在这个图形演化趋势下的图学科学的形成、变革与发展,揭示图学 科学的内涵。在此认知下给出了一个基于图形要素的图学学科框架体系。     

GIS 支持下三峡库区主要地类自动分类方法研究

针对三峡库区遥感图像变异大的特征, 设计建立了主要地类自动分类系统并在其子系统中完成了地形光谱纠正、辅助数据生成及数据合成等预处理工作; 提出了一种可交互作业的计算机全自动土地利用类型分类方法。应用专业的图像处理软件eCognition 为平台, 通过图像图斑化、选取样本、寻找最佳波段并生成判别函数来进行自动分类, 在很大程度上克服了“同物异谱”、“异物同谱”、“边界过渡”等现象对分类结果的影响。在应用地理信息系统和自动分类方法来获取波谱特征复杂地区的土地利用信息的技术路线和方法方面作了有效探索。     

FY-3B微波成像仪图像质量评价

2010年11月5日发射升空的我国新一代极轨气象卫星FY-3B (“风云三号”B星)携带的微波成像仪,可以全天候获取来自地球表面和大气的电磁辐射信息。针对在轨测试期间微波成像仪1.7 s和1.8 s两种扫描周期,详细比较了二者图像质量的差异。在图像质量评价研究中,使用统计方法比较了图像的动态范围;通过功率谱计算,对比了图像的空间纹理特征;通过信息熵计算,分析了图像信息量的不同;此外,还研究了图像的对比度以及通道间配准的情况。结果表明:1.7 s图像的空间纹理结构、高频图像的对比度以及通道间配准明显优于1.8 s,表明1.7 s扫描周期下的图像质量优于1.8 s,该结论可以作为微波成像仪仪器指标设计的参考。     

基于红外云图的台风中心智能定位方法

台风中心附近的云墙是同心圆状云带且其灰度值范围较固定,针对该特点,利用红外云图对台风中心进行智能定位,提出由云图预处理、Snake活动轮廓模型提取台风云墙轮廓点、最小二乘法拟合圆组成的3步定位方法。实验结果表明,该方法定位速度快、精度高,能满足气象业务的实时性要求。     

星载微波遥感观测海表温度的研究进展

随着卫星遥感技术的快速发展,星载微波遥感作为观测海温的手段之一,受到越来越多的关注。总结了国内外星载微波遥感观测海温的发展历程和微波遥感反演海温的理论基础,归纳了多元线性回归算法和非线性迭代算法两种主要的算法类型,在此基础上介绍了国外的TMI和AMSR-E以及国内FY-3和HY-2等卫星上搭载的先进微波传感器仪器的运行参数、通道特征及其相应的反演算法,最后分析了微波遥感反演海温的影响因素,指出了目前研究中存在的问题,并对今后的研究方向进行了展望。     

被动微波遥感在青藏高原积雪业务监测中的初步应用

积雪范围、积雪深度和雪水当量等参数的遥感监测与反演对气候模式的建立以及积雪灾害的评估具有重要意义。被动微波遥感在这些参数的反演方面具有明显优势,但目前尚未应用到青藏高原地区的积雪遥感业务监测上来。2001年10月至2002年4月,利用SSM/I数据对青藏高原地区的积雪范围和积雪深度进行了实时监测,为西藏、青海遥感应用部门提供逐日的雪深分布图。对这次监测的总效果进行了分析和评价,并对发生在青海省内一次较大的降雪过程进行了遥感分析,结果表明:SSM/I反演的积雪范围变化趋势与MODIS结果总体上较为一致;SSM/I的雪深监测结果为当地遥感部门对大于10 cm的雪深做出正确判断提供了重要信息,是对雪灾定位的重要信息源。     

基于FY-3C MWHTS的台风降水反演算法研究

为估测台风带来的地表瞬时降雨率，利用FY-3C上搭载的微波湿温探测仪（Microwave Humidity and Temperature Sounder，MWHTS)的L1级在轨观测亮度温度数据与多卫星降水分析TMPA（Tropical Rainfall Measuring Mission（TRMM）Multi-Satellite Precipitation Analysis）3B42降水产品数据，通过多元线性回归和BP神经网络两种算法对台风区的降水情况进行了反演研究。结果表明，由这两种算法反演的降水分布图可以清晰地看到台风中心、云墙以及螺旋雨带等台风的位置、分布及结构信息，这与TMPA 3B42降水产品数据估测到的台风降水分布图相一致。此外，从定量的角度来看，TMPA 3B42降水数据与这两种反演算法反演的地表瞬时降水量（mm/hr）都具有较高的相关性和较小的偏差和均方根误差，反演的精度较高。故这两种算法都可以用来反演台风区的降水量，同时也表明FY-3C MWHTS微波在轨观测资料在台风区监测及降水研究中能发挥出较高的应用价值。     

台风中心的旋转定位

台风在大气中绕着自己的中心急速旋转、同时又向前移动的空气涡旋。由于台风中心集中了台风绝大部分的能量和含水量,也是台风破坏力集中的地方,因为台风中心的定位对于台风路径预测和灾害预报来说都是非常重要的。传统的台风中心定位方式精度底,误差大,难以满足实际需要。为了准确地进行台风中心的定位,根据台风卫星云图的数字化特征和台风运动规律,提出了旋转定位方式。它的理论基础是,根据运动学和台风学原理,台风虽然是非刚性物体,但是其中心部分可相对看成是刚体的运动,因为热带气旋中心具有转动矢零的特点。这样,在卫星云图序列动画中,找出前后两次相应特征点的轨迹,即可算出其中的转动原点,也就是转动矢量为零的点。由于该方法结合了云图特性和运动因素,因而提高了精度和合理性。由此可见,对于台风这样的运动物体,结合其运动特征的中心定位法是台风中心定位的必然方向。     

Research on Typhoon Precipitation Retrieval Algorithm based on FY-3C MWHTS

In order to estimate the instantaneous precipitation rates brought by the typhoon, the Level 1 brightness temperatures from the Microwave Humidity and Temperature Sounder (MWHTS) onboard the FY-3C satellite and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) 3B42 precipitation product data are used to retrieve the precipitation rates in the typhoon area using the multiple linear regression and BP neural network retrieval algorithms. The results show that the precipitation distribution maps retrieved by these two algorithms can be clearly observed the location, distribution and structural information of the typhoons such as typhoon center, cloud wall and spiral rain belt, which are consistent with the TMPA 3B42 precipitation product data. In addition, from a quantitative point of view, the TMPA 3B42 precipitation data and surface precipitation rate (mm/hr) retrieved by these two precipitation retrieval algorithms reach higher correlation and smaller deviations and root mean square errors, and the retrieval accuracy is higher. Therefore, these two retrieval algorithms can be used to retrieve the precipitation in the typhoon area. It also shows that microwave on-orbit observation data from the FY-3C MWHTS can play a high application value in typhoon monitoring and precipitation research.     

Snowpack and runoff generation using AMSR-E passive microwave observations in the Upper Helmand Watershed, Afghanistan

Passive microwave estimates of snow water equivalent (SWE) were examined to determine their usefulness for evaluating water resources in the remote Upper Helmand Watershed, central Afghanistan. SWE estimates from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and the Special Sensor Microwave/Imager (SSM/I) passive microwave data were analyzed for six winter seasons, 2004-2009. A second, independent estimate of SWE was calculated for these same time periods using a hydrologic model of the watershed with a temperature index snow model driven using the Tropical Rainfall Measuring Mission (TRMM) gridded estimates of precipitation. The results demonstrate that passive microwave SWE values from SSM/I and AMSR-E are comparable. The AMSR-E sensor had improved performance in the early winter and late spring, which suggests that AMSR-E is better at detecting shallow snowpacks than SSM/I. The timing and magnitude of SWE values from the snow model and the passive microwave observations were sometimes similar with a correlation of 0.53 and accuracy between 55 and 62%. However, the modeled SWE was much lower than the AMSR-E SWE during two winter seasons in which TRMM data estimated lower than normal precipitation. Modeled runoff and reservoir storage predictions improved significantly when peak AMSR-E SWE values were used to update the snow model state during these periods. Rapid decreases in passive microwave SWE during precipitation events were also well aligned with flood flows that increased base flows by 170 and 940%. This finding supports previous northern latitude studies which indicate that the passive microwave signal's lack of scattering can be used to detect snow melt. The current study's extension to rain on snow events suggests an opportunity for added value for flood forecasting.     

An evaluation of AMSR-E derived soil moisture over Australia

This paper assesses remotely sensed near-surface soil moisture over Australia, derived from the passive microwave Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument. Soil moisture fields generated by the AMSR-E soil moisture retrieval algorithm developed at the Vrije Universiteit Amsterdam (VUA) in collaboration with NASA have been used in this study, following a preliminary investigation of several other retrieval algorithms. The VUA-NASA AMSR-E near-surface soil moisture product has been compared to in-situ soil moisture data from 12 locations in the Murrumbidgee and Goulburn Monitoring Networks, both in southeast Australia. Temporally, the AMSR-E soil moisture has a strong association to ground-based soil moisture data, with typical correlations of greater than 0.8 and typical RMSD less than 0.03 vol/vol (for a normalized and filtered AMSR-E timeseries). Continental-scale spatial patterns in the VUA-NASA AMSR-E soil moisture have also been visually examined by comparison to spatial rainfall data. The AMSR-E soil moisture has a strong correspondence to precipitation data across Australia: in the short term, maps of the daily soil moisture anomaly show a clear response to precipitation events, and in the longer term, maps of the annual average soil moisture show the expected strong correspondence to annual average precipitation.     

Typhoon eye extraction with an automatic SAR image segmentation method

Spaceborne microwave synthetic aperture radar (SAR), with its high spatial resolution (10–100 m), large area coverage, and day/night imaging capability, has been used as an important tool for typhoon monitoring. Since the microwave signal can penetrate through clouds, SAR images reveal typhoon morphology at the sea surface. Within the region of a typhoon eye, wind speed and the associated sea surface roughness are usually low. Therefore, the typhoon eye can be well distinguished as dark areas in SAR images. However, automatic typhoon eye extraction from SAR images is hampered by SAR image speckle noise and other false-alarm dark features contained in an image. In this study, we propose an image processing approach to extract typhoon eyes from SAR images. The three-step image processing includes: (1) applying an extended non-local means image denoizing algorithm to reduce image speckle noise; (2) applying a top-hat transform to denoized imagery to enhance the contrast; and (3) using a labelled watershed to segment the typhoon eye. Experimental results from analysing three Environmental Satellite SAR typhoon images show that our approach provides fast and efficient SAR image segmentation for typhoon eye extraction. Typhoon eyes are segmented correctly, and their edges are well detected. Our experimental results are comparable to manually extracted typhoon eye information. Fine-tuning of this approach will provide an automatic tool for typhoon eye information extraction from SAR images.     

A soil moisture assimilation scheme based on the microwave Land Emissivity Model and the Community Land Model

Applications of microwave remote-sensing data in land data assimilation are a topic of current interest and importance due to their high temporal and spatial resolution and availability. However, there have been few studies on land surface sub-grid scale heterogeneity and calculating microwave wetland surface emissivity when directly assimilating gridded Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) satellite brightness temperature (BT) data to estimate soil moisture. How to assimilate gridded AMSR-E BT data for land surface model (LSM) grid cells including various land cover types, especially wetland, is worthy of careful study. The ensemble Kalman filter (EnKF) method is able to resolve the non-linearity and discontinuity in forecast and observation operators, and is widely used in land data assimilation. In this study, considering the influences of land surface sub-grid scale heterogeneity, a satellite data simulation scheme based on the National Center for Atmosphere Research (NCAR) Community Land Model version 2.0 (CLM2.0), microwave Land Emissivity Model (LandEM), Shuffled Complex Evolution (SCE-UA) algorithm and AMSR-E BT observation data is presented to simulate AMSR-E BT data and calibrate microwave wetland surface emissivity; then, a soil moisture data assimilation scheme is developed to directly assimilate the gridded AMSR-E BT data, which consists of the CLM2.0, LandEM and EnKF. The experimental results indicate that the calibrated microwave wetland surface emissivities possess excellent transportability, and that the assimilation scheme is practical and can significantly improve soil moisture estimation accuracy. This study provides a promising solution to improve soil moisture estimation accuracy through directly assimilating gridded AMSR-E BT data for various land cover types such as bare soil, vegetation, snow, lake and wetland.