Spectral transformation of ASTER and Landsat TM bands for lithological mapping of Soghan ophiolite complex,south Iran

Spectral transformation methods, including correlation coefficient (CC) and Optimum Index Factor (OIF), band ratio (BR) and principal component analysis (PCA) were applied to ASTER and Landsat TM bands for lithological mapping of Soghan ophiolitic complex in south of Iran. The results indicated that the methods used evidently showed superior outputs for detecting lithological units in ophiolitic complexes. CC and OIF methods were used to establish enhanced Red–Green–Blue (RGB) color combination bands for discriminating lithological units. A specialized band ratio (4/1, 4/5, 4/7 in RGB) was developed using ASTER bands to differentiate lithological units in ophiolitic complexes. The band ratio effectively detected serpentinite dunite as host rock of chromite ore deposits from surrounding lithological units in the study area. Principal component images derived from first three bands of ASTER and Landsat TM produced well results for lithological mapping applications. ASTER bands contain improved spectral characteristics and higher spatial resolution for detecting serpentinite dunite in ophiolitic complexes. The developed approach used in this study offers great potential for lithological mapping using ASTER and Landsat TM bands, which contributes in economic geology for prospecting chromite ore deposits associated with ophiolitic complexes.     

An object-level strategy for pan-sharpening quality assessment of high-resolution satellite imagery

Current satellite imaging systems offer a trade-off between high spatial and high spectral resolution providing panchromatic images at a higher spatial resolution and multispectral images at a lower spatial resolution but rich in spectral information while a wide range of applications need the highest level of this information, simultaneously. Image fusion techniques as means of enhancing the information content of initial panchromatic and multispectral images produce new images, titled pan-sharpened, which inherent the advantages of the initial images. Considering the impact of fusion accuracy on the quality of corresponding applications, it is necessary to evaluate the quality of these processed images. During the last decade, a lot of quality evaluation metrics have been proposed which are mostly inspired by traditional image quality metrics. These methods are mostly based on applying quality metrics at the pixel level and evaluating final quality value based on averaging of obtained metric values through the whole image. However, obtained results clearly show that the behaviour of image fusion quality is inconsistent amongst different image objects. In this article, by applying image fusion quality metrics (IFQMs) to image objects, an object-level strategy for quality assessment of the image fusion process is proposed. The proposed strategy is applied to different satellite imagery covering residential and agricultural areas. Experimental results show higher capabilities of object-level quality assessment strategy in the quality assessment of the fusion process. Evaluating fusion quality at the object level provides the potential of fusion quality assessment for each individual image object in compliance with different parameters such as the type of objects and the effective size of objects in data set.     

Examining LiDAR – WorldView-3 data synergy to generate a detailed stand map in a mixed forest in the north-west of Turkey

Although stand delineation approach based on aerial photographs and field survey produces high accuracy maps, it is labour-intensive and time consuming. Furthermore, conventional forest stand maps may have some uncertainties that can hardly be verified due to the experiments and skills of photo-interpreters. Therefore, researchers have been seeking more objective and cost-effective methods for forest mapping. LiDAR (Light Detection and Ranging) data have a high potential to automatically delineate forest stands. Unlike optical sensors, LiDAR height data provides information about both the horizontal and vertical structural characteristics of forest stands. However, it deprives of spectral data that may be successfully used in separating tree species. In this study, we investigate the potential of LiDAR – WorldView-3 data synergy for the automatic generation of a detailed forest stand map which can be used for a tactical forest management plan. Firstly, image segmentation was applied to LiDAR data alone and LiDAR/WorldView-3 data set in order to obtain the most suitable image objects representing forest stands. Visual inspection of the segmentation results showed that image objects based on the LiDAR/WorldView-3 data set were more compatible with the reference forest stand boundaries. After the segmentation process, the LiDAR and LiDAR/WorldView-3 data sets were independently classified using object-based classification method. We tested two levels of classification. The first was a detailed classification with 14 classes considering reference stand types. The second was the rough classification with 9 classes where some stand types were combined. The mean, standard deviation and texture features of LiDAR metrics and spectral information were used in the classification. The accuracy assessment results of LiDAR data showed that the Overall Accuracy (OA) was calculated as 0.31 and 0.43, and the Kappa Index (KIA) was calculated as 0.26 and 0.32 for the detailed and rough classifications, respectively. For the LiDAR/WorldView-3 data set, the OA values were calculated as 0.50 and 0.61, and the KIA were calculated as 0.46 and 0.55 for the detailed and rough classifications, respectively. These results showed that the forest stand map derived from the LiDAR/WorldView-3 data synergy is more compatible with the reference forest stand map. In conclusion, it can be said that the forest stand maps produced in this study may provide strategic forest planning needs, but it is not sufficient for tactical forest management plans.     

一种基于COTS的SAR分布式目标模拟方法

针对目前合成孔径雷达(SAR)目标模拟器通常只能模拟点目标，且通用化程度和实时性较低的问题，提出了一种基于商用现成品或技术(COTS)的SAR分布式目标模拟方法。利用NI PXI平台构建了一个基于电磁仿真的SAR分布式目标模拟器，由电磁仿真软件模拟获取目标散射特性，并通过高速网口输入硬件设备进行采样及卷积操作得到仿真SAR回波数字信号，经数模转换模块完成对SAR数字信号的调制并输出模拟回波，可以直接用于SAR系统的数据验证。模拟器采用数字式一体化硬件设备，由NI PXIe-5646R和PXIe-5840进行信号的接收和发送，PXIe-7902作为系统核心进行高速实时数据运算。系统以现场可编程门阵列(FPGA)为核心，通过LabVIEW RT (Real Time)和FPGA模块直接进行访问，能实时、高速地采集和处理数据。经过测试，该目标模拟器可以生成分布式目标的射频回波信号，环路验证结果证明了本文提出方法的有效性。另外，本文提出的方法适用于多种雷达信号的模拟，通过设置不同的信号体制或接收外部信号输入，可以实现灵活的SAR目标模拟。     

嵌入式大气数据测量系统技术研究进展

针对高超声速飞行器大气数据测量问题，对嵌入式大气数据测量系统(FADS)技术研究背景、发展历程、国内外研究现状等进行了概括。重点围绕FADS关键技术、FADS解算算法及面向FADS/INS组合测量系统信息融合算法方面，对FADS技术进行了深入的剖析。最后，展望了FADS技术未来的发展方向及应用前景。     

The future role of relay satellites for orbital telerobotics

Orbital robotics focuses on a variety of applications, as e.g. inspection and repair activities, spacecraft construction or orbit corrections. On-Orbit Servicing (OOS) activities have to be closely monitored by operators on ground. A direct contact to the spacecraft in Low Earth Orbit (LEO) is limiting the operational time of the robotic application. Therefore, geostationary satellites are desirable to relay the OOS signals and extend the servicing time window. A geostationary satellite in the communication chain not only introduces additional boundary conditions to the mission but also increases the time delay in the system. The latter is not very critical if the servicer satellite is operating autonomously. However, if the servicer is operating in a supervised control regime with a human in the loop, the increased time delay will have an impact on the operator’s task performance.     

基于测绘业务的遥感图像质量标准开发研究

评价遥感图像的质量既可以采用客观的方法也可以采用主观的方法。重点研究了遥感图像质量主观评价方法。回顾了主观评价使用的量表法和任务满足度法的主要思想。由1∶500～1∶10 000比例尺制图的图示要求,概括出了若干个典型的满足一定规范要求的测绘业务,设计了一个心理物理试验,对这些测绘业务进行了研究,开发了一个面向1∶500～1∶10 000比例尺制图的主观图像质量评价标准。     

全球精密单点定位性能评估

随着中国北斗三号卫星导航系统（BDS-3）全面建成与开通，北斗卫星导航系统已步入了新发展阶段，基于BDS-3实现全方位、多层次、高精度应用已成为地学研究中一项基本任务。利用全球最新均匀分布的10个MGEX跟踪站，分别从24 h内接收到的卫星数、卫星位置精度因子（PDOP）、卫星数据解算完整率和双频非组合精密单点定位（PPP）静态/动态定位精度等方面系统深入地评估了BDS-3在全球范围内的可用性。结果表明，测站对卫星跟踪能力与配备的接收机类型和区域位置有强相关性，单BDS-3卫星在全球范围内具有较强的连续定位能力，当使用SEPT POLARX5和JAVAD TRE_3接收机的情况下，数据解算完整率可达100%。此外，水平方向和高程方向定位精度分别优于2 cm和3 cm，并且在联合使用BDS-2和BDS-3定位的条件下，可使得静态定位精度在东、北和高程方向进一步提升37.6%,25.3%和38.9%。     

LARES successfully launched in orbit: Satellite and mission description

On February 13th 2012, the LARES satellite of the Italian Space Agency (ASI) was launched into orbit with the qualification flight of the new VEGA launcher of the European Space Agency (ESA). The payload was released very accurately in the nominal orbit. The name LARES means LAser RElativity Satellite and summarises the objective of the mission and some characteristics of the satellite. It is, in fact, a mission designed to test Einstein's General Relativity Theory (specifically ‘frame-dragging' and Lense-Thirring effect). The satellite is passive and covered with optical retroreflectors that send back laser pulses to the emitting ground station. This allows accurate positioning of the satellite, which is important for measuring the very small deviations from Galilei–Newton's laws. In 2008, ASI selected the prime industrial contractor for the LARES system with a heavy involvement of the universities in all phases of the programme, from the design to the construction and testing of the satellite and separation system. The data exploitation phase started immediately after the launch under a new contract between ASI and those universities. Tracking of the satellite is provided by the International Laser Ranging Service. Due to its particular design, LARES is the orbiting object with the highest known mean density in the solar system. In this paper, it is shown that this peculiarity makes it the best proof particle ever manufactured. Design aspects, mission objectives and preliminary data analysis will be also presented.     

REMOTE SENSING IMAGE CODING METHOD COMBINING WAVELET TRANSFORM WITH CLASSIFIED VECTOR QUANTIZATION

A new remote sensing image coding scheme based on the wavelet transform and classified vector quantization (CVQ) is proposed. The original image is first decomposed into a hierarchy of 3 layers including 10 subimages by DWT. The lowest frequency subimage is compressed by scalar quantization and ADPCM. The high frequency subimages are compressed by CVQ to utilize the similarity among different resolutions while improving the edge quality and reducing computational complexity. The experimental results show that the proposed scheme has a better performance than JPEG, and a PSNR of reconstructed image is 31～33 dB with a rate of 0.2 bpp.