大气对可见光和近红外遥感数据的影响

本文讨论了总辐照度、大气透过率和程辐射亮度对遥感数据的影响。导出了不同高度的程辐射亮度表达式。给出了三个不同地区上述三参数在可见和近红外光谱区不同波段的观测结果。用相应的大气模式计算了不同高度的大气透过率及程辐射亮度。预计了0.4—0.5,0.5—0.6,0.6—0.7,0.7—1.1微米波段在不同大气条件和不同高度遥感器接收到的总辐射亮度、目标物本征辐射亮度和程辐射亮度。给出了总辐射亮度随程辐射亮度和目标物反射率的变化关系。分析了这些数据与大气条件的关系。     

高光谱遥感地形影响建模与仿真

针对地形起伏对高光谱遥感图像几何变形和辐射变化的影响,建立高光谱遥感地形影响模型.该模型利用传感器位置、姿态和视场角建立模拟图像像元坐标和地面空间坐标之间的成像几何关系,利用地表反射率、数字高程模型等数据,考虑大气辐射传输过程,计算起伏地形下传感器入瞳辐亮度图像,并经过空间分辨率转换,生成最终遥感模拟图像,实现高光谱遥感地形影响精确建模.利用西藏驱龙地区Hyperion数据和其它相关数据进行仿真分析,将模拟图像和原始图像进行对比,结果比较吻合,表明该模型具有较好的模拟效果.     

基于卫星云图的大区域云层预测方法

云层覆盖是影响对地观测卫星成像的一个重要问题,如果遥感图像中云层比例太高,或者特定目标不可见,则遥感图像就会失效。对地观测卫星能够根据云层预测信息,在多个观测目标之间进行选择。面向对地观测卫星任务规划的应用,设计了大区域范围的短期云层预测方法,首先通过光流法获取云运动矢量,然后依据云运动矢量外推获得预测的云层图像,同时引入拉普拉斯算子刻画云层运动过程中的扩散现象,利用风云二号卫星的真实云图序列数据,通过神经网络的反向传播算法优化扩散因子,以提升云层预测的效果。通过对结果进行分析,引入的拉普拉斯算子方法能够提高云层预测的精度,80%分位数的云层覆盖率误差约为11.7%,该精度的云层预测可以用于指导对地观测卫星任务规划。     

空间TDICCD相机动态信噪比计算方法研究

信噪比是空间光学相机系统的主要设计指标之一,可用于表征相机的辐射性能。文章通过建立遥感卫星轨道模型,分析计算一年中任意时刻用太阳高度角和卫星观测角描述太阳、卫星、地面目标点之间的相对位置关系,并将计算得到的卫星观测角和太阳高度角等参数导入大气传输软件MODTRAN,输出在相机入瞳处的地面目标光谱辐亮度,再根据信噪比的计算方法,最后完成TDICCD相机动态的信噪比计算值。通过该方法,可以计算任一时刻任一观测目标的信噪比,这将有利于判断在某一时刻的能量是否满足观测要求,以随时改变TDICCD的探测器级数,使得成像像质达到最佳。     

某高空飞艇光学吊舱热状态及飞行策略研究

使用光学遥感设备开展地球大气层临边观测是研究中高层大气目标特性变化规律的重要手段之一.光学遥感设备的热状态对其光学精度及系统信噪比控制至关重要,能够直接影响观测数据质量乃至观测任务的实现.针对中高层大气OH自由基超分辨空间外差光谱仪在高空飞艇平台探测的热状态需求,分析了光谱仪吊舱的热环境,给出了光学吊舱的热平衡控制方程,并对上升/下降段和平飞段先后开展了热状态计算,得到光学吊舱在不同状态下的温度变化规律、光电部件的温度场等计算结果.结果表明热控方案能够满足光谱仪的热状态需求.根据热状态分析计算结果,制定了飞行前后及飞行过程中光学吊舱的热控策略.本文分析方法和飞行策略可为同类飞行设备热控状态设计及研究提供数据参考.      

利用6S进行月光条件下遥感器信号模拟研究

以太阳为光源的卫星遥感器,可以采用6S或MODTRAN等辐射传输计算软件对其入瞳处的辐亮度进行计算。而在微光或月光条件下,遥感器是对观测目标反射的月亮辐射进行遥感观测,因此在进行辐射传输计算时需要代入月球的辐照度数据。可以利用已公布的月球表面反射率和已知的大气层外太阳辐照度来计算月球辐照度,并对6S辐射传输计算进行适当的修改进行计算。通过对月球辐照度计算原理进行了详细的描述并计算得到了波长在0.250μm~1.500μm范围内的月球表面辐照度,并给出了一个宽波段遥感器的微光动态范围。     

空间目标表面包覆材料褶皱对光散射特性的影响

空间目标表面包覆材料的不规则褶皱对其光散射特性具有显著影响.对空间目标表面褶皱进行分类并分析不规则褶皱形成的主要原因.以金聚酰亚胺薄膜样片为研究对象,搭建样片辐射亮度测量系统,获取不同褶皱程度样片的辐射亮度数据.将辐射亮度转换为星等进行分析发现,理论计算与实验测量得到的星等曲线趋势存在较大差异,主要表现为:平面材料的单一镜面反射现象消失;样片在多个角度上出现分散的较强散射点;褶皱程度越高,分散的强散射点越多.结果表明,在对空间目标的光散射特性进行数值计算时,必须充分考虑表面包覆材料褶皱的影响,根据褶皱情况修正数值计算模型,这对空间目标的探测和识别具有重要意义.      

基于YOLOv8的卫星遥感图像快速目标检测方法

目标检测相关技术已经广泛应用于空间目标监视、卫星自动寻轨等领域,也是计算机视觉领域最重要和最具有挑战性的研究分支之一,逐渐成为国内外军事领域的应用热点.在现代空天对抗中,通过卫星遥感图像获取近地飞行器目标,借以快速判断敌方部队的有生力量,将使我方部队占据战略优势.针对卫星观测距离过远、遥感图像背景复杂等问题,研究基于一阶段轻量化网络YOLOv8的小样本目标检测算法.通过图像翻转、马赛克数据增强及mixup数据增强等图像增强手段提高了模型的泛化性能;通过多次调整优化函数、降低类别损失增益及降低掩模比等参数调整策略提高了模型的平均精度;通过使用参数预设及加载原优化函数导出的模型提高了模型的运算效率.提出的方法在公开的飞行器数据集进行了验证,验证指标包括查准率-查全率(precision-recall)、平均精度(mAP)和画面每秒传输帧数(FPS).结果表明本文提出的改进型网络模型能满足卫星遥感图像的快速目标检测需要.     

实时仿真中的逼真虚拟地球实现

针对虚拟现实中真实感不强的问题,提出了一种具有高精度地表纹理的虚拟地球实现方法,构建了一个地表纹理像素精度高达21 600像素×10 800像素、地球表面轮廓凹凸效果和大气层光晕效果的虚拟地球.采用几何计算来构建地球形状模型,将地球按经纬度分成128块,分别计算每块区域顶点坐标、法向量、纹理坐标;采用混合纹理技术对地表纹理、云层纹理及云层法向量图进行3层纹理混合实现地球表面的云层和轮廓凹凸效果;采用实时移动与放缩带大气层纹理的正方形面板来实现大气光晕效果;采用可见性判断和纹理精度管理的方法,实时判断地球表面区域的可见性、选择不同精度纹理粘贴、剔除不可见区域,减少绘制开销.实验显示,该方法在加载1.02 GB纹理像素的情况下,达到了45帧/s的帧速率.      

多光谱遥感数据之相关性

多光谱遥感比单波段或全色遥感具有优越性,因为它能提供更多的信息,有利于识别一些类似的目标。但是,多光谱遥感数据在不同波段之间存在着相关性,减少了它理论上可能提供的信息量。本文讨论了计算多光谱遥感数据相关性的一般方法。分析结果表明,当所需遥感辨别的目标种类较少时,每个波段的数据的概率分布函数是不知的,且与波长有关。此时,相关函数并无规律性,随不同的波段而变。当所需遥感辨别的目标种类足够多时,任何波段的数据的概率分布均趋向于正态分布,规范化的平均光谱函数h(λ)趋向于平稳过程的形式,而相关函数趋向于单调下降,且仅与波段间隔距离有关。本文中举了两个例子,一个是对不同水质遥感辨别的问题,另一个是假设的增加一些目标种类的问题,以作对前一例子的对比。计算结果说明前述有关相关函数性质的论点是正确的。本文也对由于多光谱遥感数据中存在的相关性而带来遥感系统设计的问题,以及利用这种相关性改善遥感系统性能的可能性,做了简短的论述。     

基于对抗和迁移学习的灾害天气卫星云图分类

针对卫星云图中的灾害天气数据存在严重不平衡问题,提出一个结合生成对抗学习（GAN）和迁移学习（TL）的卷积神经网络（CNN）框架以解决上述问题进而提高基于卫星云图的灾害天气分类精度。该框架主要包含基于GAN的数据均衡化模块和基于迁移学习的CNN分类模块。上述2个模块分别从数据和算法层面解决数据的类间不平衡问题,分别得到一个相对均衡的数据集和一个可在不同类别数据上提取相对均衡特征的分类模型,最终实现对卫星云图的分类,提高其中灾害天气的卫星云图类别分类准确率。与此同时所提方法在自建的大规模卫星云图数据上进行了测试,消融性和综合实验结果证明了所提数据均衡方法和迁移学习方法是有效的,且所提框架模型对各个灾害天气类别的分类精度都有显著提升。      

Statistical approaches to cloud classification

For the determination of clouds from satellite data there exist in general more unknown parameters than independent observations. If the bispectral observations are used from the geostationary satellites in the solar (VIS-channel) and in the infrared (IR-channel) range to derive cloud parameters, information is needed whether a pixel radiance is from a cloud free or a cloudy scene. Statistical methods are applied to derive those informations. Various proposed statistical methods are discussed.The histogram analysis developed at the University of Cologne is described in detail: bispectral (two-dimensional) histograms are partitioned into clusters. Cloud cover results are shown. A comparison is given between the results of the histogram analysis, threshold methods (VIS- and IR threshold separately and both combined) and the spatial coherence method developed by Coakly and Bretherton. The cloud cover varies in this example by a factor of two depending on the definition of the threshold between cloud free and cloudy pixels. It is further shown that after a cluster analysis of a two-dimensional histogram the derived cloud cover is not as sensitive to the threshold as for a threshold method. The methods which are discussed here are those proposed for the International Satellite Cloud Climatology Project (ISCCP). The results are from the pilot study of the ISCCP.     

ISCCP cloud analysis algorithm intercomparison

The International Satellite Cloud Climatology Project (ISCCP) will provide a uniform global climatology of satellite-measured radiances and derive a climatology of cloud radiative properties from these radiances. For this purpose, a pilot study of cloud analysis algorithms was initiated to define a state-of-the-art algorithm for ISCCP. This study compared the results of applying the nine different algorithms to the same satellite radiance data. The comparison allowed for a sharper understanding of the process of detecting clouds and shows that all algorithms can be improved by better information about clear sky radiance values (essentially equivalent to surface property information) and by better understanding of cloud size distribution variations. The dependence of all methods on cloud size distribution led to selection of an advanced bispectral threshold technique for ISCCP because this method is currently better understood and more developed. Further research on cloud algorithms is clearly suggested by these results.     

Estimation of cloud top height and effective cloud cover from infrared satellite soundings

The paper deals with a new method for simultaneous determination of cloud top height and effective cloud cover, using infrared radiance data of satellite-borne instruments. These cloud properties derived from the Selective Chopper Radiometer on the Nimbus 5 satellite are compared with nearly simultaneous observations by radiosondes and with satellite images. Encouraging results for Central-Europe during January, April, July, August and October 1974, as well as numerical simulations indicate that the method proposed here, would be useful also for global application. Another advantage of the described procedure are the small amount of computing time, and that no other data are required than 3 of infrared channel values, for each sounded spot.     

Comparison of cloud top heights measured by airborne Lidar and TIROS-N image data

The determination of the cloud top height by means of satelliteborne IR-radiometers requires the conversion of the measured radiance to an equivalent blackbody temperature and the assignment of this temperature to a geometrical height. The latter is associated with errors which add up easily to several kilometers. DFVLR did a case study to compare satellite derived cloud top heights with those from airborne Lidar measurements. The difference of the radiosonde temperature from the standard temperature profile results in a 1.8 km difference in cloud top height. The achievable accuracy using actual radiosonde temperatures is ± 0.4 km for optical thick clouds and much less for optical thin clouds.     

Remote sensing of clouds

The extraction of information on cloud cover from present-day multispectral satellite images poses a challenge to the remote sensing specialist. When approached one pixel at a time, the derived cloud cover parameters are inherently nonunique. More information is needed than is available in the radiances from each channel of an isolated pixel. The required additional information can be obtained for each scene, however, by analyzing the distribution of pixels in the multi-dimensional space of channel radiances. The cluster patterns in this space yield statistical information that points to the most likely solution for that scene. The geostationary and polar orbiting meteorological satellites all have, at a minimum, a solar reflection channel in the visible spectrum and a thermal infrared channel in the 8–12 micron window. With the information from the cluster patterns and application of the equations of radiative transfer, the measurements in those channels will yield cloud cover fraction, optical thickness, and cloud-top temperature for an assumed microphysical model of the cloud layer. Additional channels, such as the 3.7 micron channel on the AVHRR of the polar orbiting meteorological satellites, will will yield information on the microphysical model—e.g., distinguishing small liquid liquid droplets (typical of low level clouds) from large ice particles (typical of cirrus and the tops of cumulonimbus). New channels to be included in future satellite missions will provide information on cloud height, independent of temperature, and on a particle size and thermodynamic phase, independently of each other. A proposed STS mission using lidar will pave the way for the use of active sensors that will provide more precise information on cloud height and probe the structure of thin cirrus and the top layer of of the thicker cloud.     

观测路径和光谱分辨率对吸收性气溶胶指数的影响

吸收性气溶胶指数（AAI）在监测污染物方面有较好的应用,其反演结果受边界层高度、云高、相对湿度以及仪器指标和观测几何路径等因素影响.利用大气辐射传输模型MODTRAN,对辐射传输方程中多次散射计算的不同近似方法和不同观测几何角度下的AAI进行模拟,研究这些因素对AAI结果的作用,并分析仪器光谱分辨率对AAI探测结果的影响.结果表明,折衷考虑计算效率与精度的情况下,应选择8流近似的离散坐标法进行带有多次散射计算的辐射方程解析.AAI在不同浓度和不同类型气溶胶下随观测角度变化的趋势相同:相对方位角<120°时,AAI误差在太阳天顶角和卫星方位角均为40°～60°时最大;相对方位角在120°～180°时误差均较小;光谱分辨率对AAI反演结果无明显影响.      

Improvement in the GERB short wave flux estimations over snow covered surfaces

Because space-borne radiometers do not measure the Earth’s outgoing fluxes directly, angular distribution models (ADMs) are required to relate actual radiance measurement to flux at given solar angle, satellite-viewing geometries, surface, and atmospheric conditions. The conversion of one footprint broad-band radiance into the corresponding flux requires therefore one to first characterize each footprint in terms of surface type and cloud cover properties to properly select the adequate ADM.

A snow (and sea-ice) retrieval technique based on spectral measurements from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat 8 is presented. It has been developed to improve the scene identification and thus the ADM selection in the near-real time processing of the Geostationary Earth Radiation Budget (GERB) data at the Royal Meteorological Institute of Belgium. The improvement in the GERB short wave flux estimations over snow covered scene types resulting from angular conversion using dedicated snow ADMs (e.g., empirical snow ADMs and/or pre-computed theoretical snow ADM) instead of empirical snow-free ADMs is discussed.     

An examination of a technique for estimating the longwave radiation budget from satellite radiance observations

Intercomparisons of the zonally averaged outgoing longwave fluxes estimated from 10 μm radiance observations on NOAA polar orbiters and flat plate observations on the Nimbus 6 ERB experiment have shown the NOAA estimates to be higher than the ERB measurements. Our analysis shows that the operational technique systematically overestimates calculated fluxes for middle and high cloud conditions. A different radiative transfer model and new assumptions concerning clouds reduce the NOAA-ERB flux difference by approximately 35%.     

基于SVM的浮动车行驶模式判断模型

浮动车在低速情况下存在两种行驶模式,如不能对上述模式进行准确区分,将严重影响浮动车实时路况计算的精度和效率.研究和设计了一个基于支持向量机(SVM,Support Vector Machine)的浮动车行驶模式判断模型,并针对性地提出了一种简单的基于隶属度矩阵的特征评价和选择方法.实验表明通过上述方法选择的特征子集所训练的分类器在测试样本集上具有92.6%的分类准确性;经过行驶模式分析后,浮动车系统的准确性有显著提升.