Determining total ozone content in the atmosphere using satellite measurements

In this paper a simple method is presented which is applicable for fast determination of total ozone content in the earth atmosphere by using IR radiation intensity data from satellite measurements. The method is based on the property that transmittance of inhomogeneous atmosphere in the 9.6 μm band can be well approximated by the transmittance of a homogeneous ozone slab characterized by its effective pressure and temperature. The effective pressure and temperature were determined as mean values weighted by the average ozone profile of each season. The transmission functions were computed from an empirical formula. Free parameters in the formula were determined by a multiple regression scheme, on the basis of the transmittance data either measured in the laboratory or evaluated by computations using a line by line integration procedure. The main advantage of the described method is an easy and fast computation procedure. According to comparison with direct ozone sounding the accuracy is good enough: the average relative error lies between 5 and 7%.     

Implications of a Data Reduction Framework to Assignment of Fuzzy Membership Values in Continuous Class Maps

This paper develops a data reduction framework for assigning fuzzy membership values to continuous geographic data. The goal of classification is defined quantitatively using explicit criteria of error and confusion introduced by the classification process. A new method of assigning fuzzy membership values is designed to reduce overall error, and compared with standard, similarity-based methods. As a case study, a continuous forest-type map is created for an area of the northeastern United States using data from the U.S. Forest Service. Given certain reasonable assumptions regarding the interpretation of continuous classes, the new method is shown to provide small but consistent reductions in error and confusion. More generally, the data reduction framework provides explicit meaning to the use of continuous classes in ecological mapping, allowing for quantitative measurement of the error introduced by the classification process.     

空间目标三维重构误差分析与相机参数设计方法

针对空间目标三维重构任务中的相机参数设计问题,提出一套由目标重构精度反演观测相机参数及观测方案的方法。通过梳理三维重构误差传播机理,将误差传播归结为相机内参数影响特征点齐次坐标和齐次坐标影响重构精度两个过程,给出了三维重构误差计算方法。基于误差下限分析计算结果,给出了观测距离、拍照间隔与相机姿态指向等任务参数的设计原则,建立了由重构精度反演相机焦距和像素尺寸的方法,形成一套以重构精度为核心指标的观测方案和相机参数设计方法。针对模拟空间目标的仿真试验校验了重构误差估算算法及相机参数和观测方案设计方法的有效性。     

基于多层次特征的高分影像海岸带地物分类

针对高分辨率影像地物光谱丰富复杂的问题，文章提出了一种结合像元-对象-空间格局特征的水域、盐田等海岸带精细地物分类方法。首先基于像元和空间格局特征分别利用遗传算法优化随机森林参数进行分类；其次将两种分类结果采用D-S证据理论融合；然后基于不同地物斑块的空间上下文信息，采用粒子群算法优化支持向量机（Support Vector Machine，SVM）参数实现面向对象的二次分类。为验证方法的有效性，收集山东省莱州湾海岸带附近区域的“高分二号”卫星影像，开展了水域及水利设施用地、盐田、工矿用地、交通运输用地、住宅用地、沿海滩涂、海域与耕地8类地物的分类实验，总体精度达到97.21%，Kappa系数为0.964 2。实验结果表明，文章提出的高分影像海岸带地物分类方法兼顾像元、对象及空间格局特征优点，能够实现多层次细致分类，并同时兼具较短的训练时长与较高的分类精度。该研究成果可为中国海岸带生态环境监测与土地利用规划提供一定技术支撑。     

基于聚类的航天器多余物粒径特征识别方法

针对焊锡粒多余物粒径特征识别过程中,粒径区分度不足和粒径特征参数类间交叉对分类准确率的不利影响,提出基于聚类的高精密航天器多余物粒径特征识别方法.从信号时域与频域分析技术出发,选取多个特征参数构建多余物粒径初始特征参数向量;采用Fisher比量化各个特征参数对粒径的区分能力并削除贡献率较低的特征参数,从而构建最终多余物...     

Landsat satellite imagery of the Qattara Depression area,Egypt

The Qattara Depression lies in the northern part of the Western Desert of Egypt at a distance of some tens of kilometers to the south of the Mediterranean Sea Coast. The depression in question is the largest one in the great Sahara extending across North Africa. It covers an area of some 19,000 km² at ? 60 m level and the absolute level of its lowest point is about ? 134 m. The depression extends for about 300 km in a roughly ENE-WSW direction, while its width is variable reaching to a maximum of about 145 km. Feasibility studies are currently carried out for the Qattara solar-hydro-electric project which aims at generating hydro-electric power by the drop of the Mediterranean Sea water into the depression after passing through a canal/tunnel system. Peak load electric power may be also generated by raising the water to the small hollow of Deir Kirayim, situated at a higher level near the depression, and allowing it to drop to a low level.For the purpose of assessing the regional criteria involved in the implementation of the project and the environmental impact of such implementation, the Qattara Depression and the surrounding area has been studied on a regional scale by the utilization of LANDSAT satellite imagery. The maps produced by the interpretation of the images in question include those of the geological and environmental units, structural lineations, drainage and vegetation cover. Lineation density and drainage density maps are derived by the computation of the structural lineation and drainage maps respectively. A map of groundwater conditions is worked out on the basis of the image interpretation, and the observations previously carried out on the groundwater aquifers in the Qattara Depression and the surrounding area. LANDSAT satellite image interpretation and computation are supported by intensive observations carried out in the field as well as chemical, petrological and mineralogical analyses of the samples collected.The LANDSAT satellite images proved to be of great importance in mapping the Qattara Depression floor which is hardly accessible to classical mapping, and especially in view of the large area which could be covered by imagery mapping in a reasonably short time compatible with the duration of the feasibility study. The special characters of the spaceborne multispectral imagery have been paramount in deciphering the major regional features of the investigated area.The overall synoptic picture of the regional setting of the geological and environmental units, faults, fractures and folds, drainage lines and plant cover in the large area studied has been clarified for the first time. It has been demonstrated that the Qattara Depression is actually constituted of several small depressions. The environmental impact of the project implementation has been visualized especially regarding the possible influence of the saline water on the fresh groundwater sources. The thick salt accumulation in the depression has been found to be of such extension as to increase the salinity of the Mediterranean Sea water stored in the depression following the implementation of the project. The lineation density map has been particularly of great help in the localization of sites subjected to intense crustal deformation, greater slope instability and run off surface water flooding.     

基于空谱融合特征主动学习的高光谱图像分类

针对高光谱图像分类过程中存在的样本量少和分类精度低的问题,提出一种基于空谱融合特征主动学习的高光谱图像分类方法。主要包括构造三通道图像,全卷积网络提取空间特征,空谱特征结合,主动学习方法选择训练样本几个部分。通过结合像素的光谱特性和相邻像素间的空间关联,提取出可以反映像素空谱联合特性的综合特征,提高了像素特征的表达能力。为克服高光谱图像标注数据少、缺乏训练样本的问题,应用主动学习算法,充分选择更具有代表性的样本进行训练,达到少样本情况下较高的分类正确率。通过在标准数据集上进行实验,结果表明:该方法可以达到在总样本数1%作训练样本的情况下,分类正确率达到99.79%,优于传统的高光谱分类算法。     

星载干涉合成孔径雷达高度计波束指向优化设计新方法

基于干涉合成孔径雷达(InSAR)体制的星载高度计能实现高分辨率、宽幅、高精度海面高程测量。传统合成孔径雷达(SAR)系统波束指向设计方法以SAR图像近远端噪声等效后向散射系数差异最小化为优化目标,星载InSAR高度计对海入射角小,如采用传统波束指向设计方法将面临系统近端测高性能优于远端等问题。为使远端测高性能满足应用精度指标要求,系统需提高雷达发射功率或增大雷达天线尺寸,这对卫星系统提出了较高的要求。提出了面向测高应用的星载InSAR高度计波束中心指向设计新方法。该方法通过调整雷达波束中心指向实现全场景测高性能最优化,可有效降低传统设计方法中SAR载荷对发射功率等卫星指标的要求,对未来我国发展InSAR体制海面高度计系统设计具有重要的指导意义。仿真分析结果验证了新方法相对于传统设计方法的优越性。     

航天测控系统卫星鉴定技术研究

针对基于卫星的航天测控系统精度鉴定技术开展了深入的分析和研究,提出了较为全面的卫星鉴定的思路和技术途径。在时序比对统计方法的基础上对利用卫星进行系统误差分离的方法展开了深入研究,并将比对估计统计方法和"EMBET"自鉴定方法有机结合起来。通过可行性分析和工程应用充分验证了利用卫星对航天测控系统进行精度鉴定的可行性、正确性和优越性。     

基于DJI精灵4多光谱版无人机的红树林精细分类

本文基于DJI（大疆）精灵4多光谱版无人机能够同时获取地表可见光照片和多光谱影像的特点，提出了使用摄影测量技术构建冠层高度模型（CHM）的方法，并结合多光谱影像应用于红树林分类。将上述方法应用于广东省湛江红树林国家级自然保护区高桥镇研究区，结果表明：基于无人机摄影测量技术构建的红树林CHM与多光谱影像结合后能够大幅提高红树林的分类精度，可替代传统的机载激光雷达数据；DJI精灵4多光谱版无人机数据获取效率高，能够实现高精度的红树林分类，在红树林监测业务工作中具有推广应用价值。     

传播模型驱动的三维频谱地图测绘研究

频谱地图是频谱资源管理、安全治理和频谱作战等应用的基础。针对传统频谱测绘局限于二维空间的问题,给出了一种面向空天地一体化需求的三维频谱数据采集和测绘系统架构,提出了一种传播模型驱动的频谱地图重构方案,能够实现稀疏采样条件下高精度的三维频谱地图绘制。该方法在单辐射源和多辐射源情况重构的频谱地图与基于射线跟踪方法获得理论结果吻合度较高。此外,针对典型场景的实测结果也进一步验证了本文方法的可行性。     

Route Knowledge in Complex Environments: An Analysis of Pedestrian Recall Using Stereoscopic Panoramic Interactive Navigation

In this study, we investigate whether data collected on route knowledge is influenced by the method of data collection. The results of stereoscopic panoramic interactive navigation re-enactment sessions and conventional paper and pencil maps are compared against observational tracing data of pedestrian route choice behavior in the city center of Eindhoven, The Netherlands. The findings of the study suggest that the data collected through maps better describe empirical observations of pedestrian route choice behavior that the data collected through stereoscopic panoramic interactive navigation sessions.     

基于北斗三号短报文的共视数据压缩传输方法

共视时间比对通过交换两地共视数据完成远距离高精度的时间比对。针对无地面通信网地区,本文提出了一种基于北斗短报文的共视数据压缩传输方法,该方法通过将共视数据进行压缩,利用北斗的短报文功能对压缩后的共视数据进行实时传输,在无地面通信网的地区进行了共视时间比对试验。试验结果表明,本文设计的共视数据压缩方法具有较好的压缩效果,可以通过北斗短报文实现无地面通信网的情况下的实时共视时间比对。     

一种卫星多光谱图像亚像元波段配准精度自动评价方法

多光谱图像波段配准精度是多光谱影像数据的一项重要指标。文章实现了一种基于相位一致特征的多光谱图像亚像元波段配准精度自动评价方法。通过对CBERS-02B卫星CCD多光谱图像波段配准精度自动评价,表明该方法对于亮度和对比度具有不变性,能均匀稳定提取多光谱数据不同波段影像大量同名特征匹配点,自动给出影像的不同区域的亚像元配准精度,实现对整景影像数据的较为完整准确评价。根据评价结果进行了地面处理系统校正,使行列方向除局部区域外均达到配准精度。     

航天密封舱设备安装精度仿真分析方法

针对航天密封舱设备安装精度受密封舱内压影响却没有实用的理论预示方法,提出了仿真分析设备安装精度的方法。该方法根据有限元结构仿真分析得到的位移,导出设备的安装精度;另外,提出了精测数据的分析方法,使设备的安装精度变化规律更明显,更容易看出设备旋转的旋转轴、旋转方向、旋转角度,也使精测数据与仿真数据的对比更容易,可为验证仿真分析的准确性提供前提条件。利用一个算例对文章提出的仿真分析方法进行了验证。结果表明,仿真分析方法能准确地确定设备安装角度变化的旋转轴和旋转方向,计算出的旋转角度值与精测结果也基本一致。     

基于速度增量修正的卫星入轨段外测数据定轨新方法

在传统的数值积分精密定轨方法基础上,提出基于器箭分离速度增量修正的定轨方法,实现了器箭分离前后两段外测数据的联合定轨。仿真计算结果和任务实战数据验证结果表明,该方法大大提高了地月转移轨道入轨段外测定轨精度,比传统初轨确定方法提高约一个数量级。     

基于复数域Transformer-Unet混合模型的PolSAR地物分类

传统的基于深度学习的极化合成孔径雷达（Polarimetric Synthetic Aperture Radar,PolSAR）地物分类方法,通过堆叠卷积层提取图像局部特征,难以建立长距离依赖关系。基于自注意力机制的深度学习模型Transformer（变换）在图像分类任务中取得了成功,其自注意力机制能够捕获全局像素之间的关联性,同时PolSAR地物分类任务被证实：相比于实数域,其在复数域上表现出更好的分类效果。因此,本文将Transformer引入到复数域中,提出了一种基于复数域的Transformer和Unet（语义分割网络）混合模型（CT-Unet）用于PolSAR地物分类,将Transformer与CNN相结合,对复数类型的PolSAR数据进行特征提取,使用西安数据集和德国数据集进行PolSAR地物分类的实验结果表明：提出的模型能够有效提高PolSAR地物分类的准确性,Transformer有望在PolSAR地物分类任务中弥补卷积神经网络的不足。     

我国人口受教育程度分类模型

模糊聚类分析是研究将事物进行分类的科学,其目的是利用一定的数学方法将研究的样品或变量归并为若干类,使得每一类中的所有个体之间具有密切的关系,而不同类之间个体关系相对比较疏远。本文用模糊聚类方法将我国人口受教育程度分成了四类的模式,按该模式可以对其他省市进行了预测分类。     

我国人口受教育程度分类模型

模糊聚类分析是研究将事物进行分类的科学,其目的是利用一定的数学方法将研究的样品或变量归并为若干类,使得每一类中的所有个体之间具有密切的关系,而不同类之间个体关系相对比较疏远.本文用模糊聚类方法将我国人口受教育程度分成了四类的模式,按该模式可以对其他省市进行了预测分类.