低成本大视场深度相机阵列系统

在测距传感器不断轻量化、小型化以及室内外地图一体化导航应用的驱动下,三维（3D）室内移动测量成为当今研究和应用的热点,在室内建模、室内定位等新兴领域中的应用越来越广泛。3D室内移动测量系统通常配备激光扫描仪、全景相机、惯性测量单元（inertial measurement unit,IMU）系统和里程计等传感器,虽能实现3D室内点云数据的采集,但其距离传感器-激光扫描仪价格昂贵且便携性较差。彩色深度（RGB depth,RGB-D）相机为低成本3D室内移动测量系统构建提供了新的距离成像传感器选择,但主流型号RGB-D相机视场角小,继而导致数据采集效率远低于传统激光扫描仪,难以做到点云数据的完整覆盖与稳健采集,且易造成同时定位与制图（simultaneous localization and mapping,SLAM）过程中跟踪失败。针对以上问题,构建了一种低成本室内3D移动测量系统采集设备,通过组合多台消费级RGB-D相机构成大视场RGB-D相机阵列,提出了一种阵列RGB-D相机内外参数标定方法,并通过实验检验了设计系统采集的点云数据的精度。     

激光荧光雷达系统的测量方法与应用

本文叙述了应用激光荧光雷达系统测量海上溢油类别以及植被、岩矿、土壤、地被物等荧光光谱的方法与技术。该装置由N_2激光源、OSA光学光谱分析仪、卡斯格伦望远镜接收系统三部分组成。该装置可在室内,也可在室外25—60m远处测量各种物质的受激发射荧光。该仪器用标准灯谱进行了校正。     

CBERS-02B星HR与多光谱影像融合及评价

CBERS-02B星搭载了高分辨率全色相机HR和多光谱传感器CCD,HR影像可以与CCD影像融合,优势互补形成新的影像,既保持HR的高空间分辨率又保持CCD的光谱分辨率,HR影像同样可以与其它传感器影像融合形成新的影像。本文使用6种不同的融合方法融合HR与多光谱CCD以及SPOT5多光谱影像,并对融合结果进行了定性和定量评价,得到了HR与SPOT5多光谱影像融合较好的方法,表明了HR与其它传感器影像融合的潜力,同时也对HR和SPOT5多光谱融合影像及与CCD融合影像进行了初步的对比分析。     

主被动多传感器组合的宽角成像系统设计与实验

按照国家航空应急测绘的需求提出了一种多传感器组合成像系统。在此系统中,将组合数码相机、视频和红外相机、激光雷达（light detection and ranging,LiDAR）和小型合成孔径雷达（miniature synthetic aperture radar,MiniSAR）集成到统一的时空基准,分别且同时地实现大像幅光学成像,白天和夜间视频影像获取与传输,三维激光点云获取,以及全天候的微波遥感。详细阐述了组合宽角相机在改善影像质量和作业效率方面的优势。根据上述设计,将实验系统安装在中航时无人机上进行了飞行检验,给出了所获取的白天和夜间数据成果。     

航摄多传感器集成检校与精度分析

基于机载POS系统定位定向原理,建立解算国产POS与数码相机集成系统偏心角、偏心分量的数学模型,经过POS、相机、惯性稳定平台等多传感器集成的航空摄影试验,分析系统误差检校和POS直接地理定位的精度,验证该检校模型的正确性与可行性。     

智能手机移动测量方法的设计与实现

近年来,智能手机在快速的发展过程中逐渐集成了多种传感器,包括位置传感器、磁力计和加速度计等姿态传感器和数码相机等;同时,由于它所具备的体积小、成本低的优点,为实现手机影像移动量测提供了可能。本文通过Android系统平台及智能手机集成的多传感器,提出了一种新型的智能手机影像量测方法。该方法首先对手机相机进行标定获取内方位元素,并进行Android应用程序的开发,在获取影像数据的同时获得手机的位置姿态数据;然后对影像数据进行特征点提取、匹配及错误点删除,并根据位置姿态数据和同名点图像坐标,利用空间前方交会计算目标点的三维坐标;最后通过光束法平差进行整体优化。试验结果表明该方法获取的位置信息可达到较高的精度.     

融合多种棋盘格约束的面阵相机和线激光外参标定

面阵相机和线激光扫描仪的组合在移动测量、自动驾驶、机器人等领域中得到了广泛应用。影像纹理和激光深度数据融合的首要问题是两种传感器的外参标定。对此,提出了一种融合多种约束条件的相机和线激光外参标定算法。该算法建立激光扫描线与V型棋盘平面间的点-面、线-面、点-线等多种约束求解和优化激光与相机间的外参,减少了激光点和像点噪声对结果的影响。实验结果表明,该算法相较于之前的算法有更高的精度和鲁棒性。并通过计算激光交点到V型棋盘面交线的距离,提出了定量评价激光与相机外参精度的标准。     

盐城东台中巴地球资源卫星04星影像

<正>中巴地球资源系列卫星(CBERS)由中国航天科技集团公司和巴西空间研究院联合研制,是中巴两国在航天科技领域合作的重要体现,被赞誉为"南南合作的典范",主要应用于国土、林业、水利、农情、环境保护等领域的监测,规划和管理。CBERS-04卫星配备有分辨率为5 m的全色、10 m的多光谱相机(PAN),20 m的多光谱相机(MUX),40 m/80 m的红外相机(IRS)以及分辨率为67 m的宽视场相机(WFI),满足了获取持续稳定的中分辨率普查数据的迫切需求。     

资源三号测绘卫星传感器校正产品几何模型

资源三号测绘卫星为了获取较大的幅宽和较高的空间分辨率,其三线阵相机和多光谱相机采用了多片CCD拼接成像的方式获取地面影像。如直接提供分片的CCD影像产品,用户难以使用。传感器校正产品解决了CCD影像拼接的问题,拼接后的影像不仅视觉无缝,同时几何无缝。该产品同时解决了多光谱波段间配准的问题,且生产过程中引入的投影差误差和交会误差可以忽略不计。该产品消除了大部分畸变,故拥有极高的RFM替代严密成像几何模型精度。本文利用安平和登封地区的三线阵数据进行验证,试验区三线阵传感器校正产品RFM替代精度优于1%像元,无地面控制点立体定位精度优于15 m,带控制点平面误差在3 m以内,高程误差在2 m之内,且三线阵平差平面定位精度要优于两线阵。     

一种航空多光谱数字相机系统的设计与实现

介绍一种基于面阵CCD传感器件的航空多光谱数字相机系统的设计和实现 ,该系统的核心部件是 10 2 4× 10 2 4像元的面阵CCD相机 ,系统采用更换滤光片的方法来获得针对不同应用的最佳多波段组合 ,解决了多相机曝光参数实时控制、多相机同步触发、多通道高速数据采集、图像数据高速记录等问题 ,集成GPS系统 ,并成功进行了一系列地面实验和航空遥感实验     

Object-based habitat mapping using very high spatial resolution multispectral and hyperspectral imagery with LiDAR data

This study investigated the combined use of multispectral/hyperspectral imagery and LiDAR data for habitat mapping across parts of south Cumbria, North West England. The methodology adopted in this study integrated spectral information contained in pansharp QuickBird multispectral/AISA Eagle hyperspectral imagery and LiDAR-derived measures with object-based machine learning classifiers and ensemble analysis techniques. Using the LiDAR point cloud data, elevation models (such as the Digital Surface Model and Digital Terrain Model raster) and intensity features were extracted directly. The LiDAR-derived measures exploited in this study included Canopy Height Model, intensity and topographic information (i.e. mean, maximum and standard deviation). These three LiDAR measures were combined with spectral information contained in the pansharp QuickBird and Eagle MNF transformed imagery for image classification experiments. A fusion of pansharp QuickBird multispectral and Eagle MNF hyperspectral imagery with all LiDAR-derived measures generated the best classification accuracies, 89.8 and 92.6% respectively. These results were generated with the Support Vector Machine and Random Forest machine learning algorithms respectively. The ensemble analysis of all three learning machine classifiers for the pansharp QuickBird and Eagle MNF fused data outputs did not significantly increase the overall classification accuracy. Results of the study demonstrate the potential of combining either very high spatial resolution multispectral or hyperspectral imagery with LiDAR data for habitat mapping.     

The Z/I Imaging Digital Camera System

Market needs for airborne and spaceborne imagery used in photogrammetry and GIS applications are changing. Fundamental changes in sensors, platforms and applications are currently taking place. Most recently, new high resolution spaceborne sensors have become available. Besides classical photogrammetry, new thematic applications will drive the future image market. Savings in cost and time, together with the need for higher and reproducible radiometric resolution or spectral information will push forward the change from analogue to digital imagery. High resolution satellites will compete with airborne film-based photography and digital camera systems.
With the availability of a digital airborne camera, it is possible to completely close the digital chain from image acquisition to exploitation and data distribution. The key decision regarding the camera design in this case is whether a linear or area array sensor should be used. In view of the high geometric accuracy requirements in photogrammetry, Z/I Imaging has focused development on a digital camera based on an area sensor. An essential aspect of this decision was not only the aerial camera system, but also the entire photogrammetric process to the finished photographic or mapping product. If this point of view is adopted, it becomes clear that the development of a digital camera involves more than simply exchanging film for silicon. Aspects such as data transfer rates, in-flight data processing and storage, image archiving, georeferencing, colour fusion, calibration and preprocessing have the same influence on the economic assessment of a digital camera system. This paper describes current development activities and application aspects of a digital modular airborne camera system.     

The design and the development of a hyperspectral and multispectral airborne mapping system

Flexible and cost-effective tools for rapid image acquisition and natural resource mapping are needed by land managers. This paper describes the hardware and software architecture of a low-cost system that can be deployed on a light aircraft for rapid data acquisition. The Hyperspectral and Multispectral Cameras for Airborne Mapping (HAMCAM) was designed and developed in the Geospatial Laboratory for Environmental Dynamics at the University of Idaho as a student-learning tool, and to enhance the existing curriculum currently offered. The system integrates a hyperspectral sensor with four multispectral cameras, an Inertial Navigation System (INS), a Wide Area Augmentation System (WAAS)-capable Global Positioning System (GPS), a data acquisition computer, and custom software for running the sensors in a variety of different modes. The outputs include very high resolution imagery obtained in four adjustable visible and near-infrared bands from the multispectral imager. The hyperspectral sensor acquires 240 spectral bands along 2.7 nm intervals within the 445–900 nm range. The INS provides aircraft pitch, roll and yaw information for rapid geo-registration of the imagery. This paper will discuss the challenges associated with the development of the system and the integration of components and software for implementation of this system for natural resource management applications. In addition, sample imagery acquired by the sensor will be presented.     

Use of Very High Spatial Resolution Remotely Sensed Imagery for Assessing Land‐Cover Changes in Shrub Habitat Preserves of Southern California

Abstract

The goal of this research was to explore the utility of very high spatial resolution, digital remotely sensed imagery for monitoring land‐cover changes in habitat preserves within southern California coastal shrublands. Changes were assessed for Los Penasquitos Canyon Preserve, a large open space in San Diego County, over the 1996 to 1999 period for which imagery was available.

Multispectral, digital camera imagery from two summer dates, three years apart, was acquired using the Airborne Data Acquisition and Registration (ADAR) digital‐camera system. These very high resolution (VHR) image data (1m), composed of three visible and one near‐infrared wavebands (V/NIR), were the primary image input for assessing land cover change. Image‐derived datasets generated from georeferenced and registered ADAR imagery included multitemporal overlays and multitemporal band differencing with threshold selection. Two different multitemporal image classifications were generated from these datasets and compared. Single‐date imagery was analyzed interactively with image‐derived datasets and with information from field observations in an effort to discern change types. A ground sampling survey conducted soon after the 1999 image acquisition provided concurrent ground reference data.

Most changes occurring within the three‐year interval were associated with transitional phenological states and differential precipitation effects on herbaceous cover. Variations in air temperatures and timing of rainfall contributed to differences that the seven‐week image acquisition offset may have caused. Disturbance factors of mechanical clearing, erosion, potentially invasive plants, and fire were evident and their influence on the presence, absence, and type of vegetation cover were likely sources of change signals.

The multitemporal VHR, V/NIR image data enabled relatively fine‐scale land cover changes to be detected and identified. Band differencing followed by multitemporal classification provided an effective means for detecting vegetation increase or decrease. Detailed information on short‐term disturbance effects and long‐term vegetation type conversions can be extracted if image acquisitions are carefully planned and geometric and radiometric processing steps are implemented.     

Development and Application of the Highway Mapping System of Ohio State University

Since 1990, the Center for Mapping at Ohio State University has been developing mobile mapping systems to automate and accelerate the collection of digital map data. These systems integrate the global positioning system (GPS) with inertial navigation units and imaging sensors to produce digital geographic data. They are modular and can be installed on various platforms, such as vans, trains and aeroplanes. New developments with the imaging system and the fully integrated data-processing environment are discussed in this article. The stereovision system enables the user to obtain three dimensional co-ordinates of any object in the field of view of the camera. Digital and video images, together with GPS positions, are stored in an object-oriented database, which merges data collected by airborne and terrestrial mapping platforms. Exploiting the enormous amount of information contained in the digital stereoscopic imagery is a challenging topic of current and future research.     

Principle, software and experiment of GPS-supported aerotriangulation

1 IntroductionAs is now well known, the high accurate point de-termination with airborne remOe sensing data hasalways ben one of the most fundaxnental prObletns..in aerial photOgrammtry. According to the princi-ple of the geOmtry reversal in photOgramrntry,the interior and exterior orientation elements ofaerial phOtOgraphs must first be known in order toreconstnJct the measuring stereo geometric medels.For the past 60 years, however, the interior orienta-tion parameters of carnera were main…     

Employing spatial information technologies to monitor biological control of saltcedar in West Texas

The saltcedar leaf beetle (Diorhadha spp.) has shown promise as a biocontrol agent for saltcedar (Tamarix spp.) invasions in the USA. In Texas, natural resource managers need assistance in monitoring biological control of invasive saltcedars. This study describes application of a medium-format, digital camera acquiring natural colour imagery and global positioning system (GPS) and geographic information system (GIS) technologies to check biological control of saltcedar in west Texas. On 8 July and 8 September 2011, natural colour airborne digital imagery was collected along a 155.8?km transect covering portions of Presidio and Brewster counties of Texas. The camera was tethered to a GPS receiver that geotagged each image and saved the coordinates to a key-hole marked up language file that was viewable on Google Earth. Saltcedar trees exhibiting severe feeding damage and those that were totally defoliated were easily identified in the imagery. The former appeared in orange to brown colour tones; the latter exhibited grey colour tones. Point distribution maps showing locations of saltcedar trees exhibiting feeding damage were developed from GPS information in the GIS. Coordinate points on the map were linked to the corresponding image, permitting the user to have quick access to view imagery. The results of this study show a practical method for monitoring biological control of saltcedar.     

Mt. Etna volcano high-resolution topography: airborne LiDAR modelling validated by GPS data

High-resolution digital topography is essential for land management and planning in any type of territory as well as the reproduction of the Earth surface in a geocoded digital format that allows several Digital Earth applications. In a volcanic environment, Digital Elevation Models are a valid reference for multi-temporal analyses aimed to observe frequent changes of a volcano edifice and for the relative detailed morphological and structural analyses. For the first time, a DTM (Digital Terrain Model) and a DSM (Digital Surface Model) covering the entire Mt. Etna volcano (Italy) derived from the same airborne Light Detection and Ranging (LiDAR) are here presented. More than 250 million 3D LiDAR points have been processed to distinguish ground elements from natural and anthropic features. The end product is the highly accurate representation of Mt. Etna landscape (DSM) and ground topography (DTM) dated 2005. Both models have a high spatial resolution of 2?m and cover an area of 620?km². The DTM has been validated by GPS ground control points. The vertical accuracy has been evaluated, resulting in a root-mean-square-error of ±?0.24?m. The DTM is available as electronic supplement and represents a valid support for various scientific studies.     

Detecting Squarrose Knapweed (Centaurea virgata Lam. Ssp. squarrosa Gugl.) Using a Remotely Piloted Vehicle: A Utah Case Study

Determining the location of founding weed populations is critical to minimizing the diffusion of weedy species. Remote sensing is a promising tool for early detection of these small weed patches. The objective of this study was to determine the capability of a small remotely piloted vehicle (RPV) (carrying a digital camera and GPS) to acquire aerial photography from which small infestations of squarrose knapweed (Centaurea virgata Lam. Ssp. squarrosa Gugl.) could be detected and mapped. Two Utah rangeland sites were studied. The location of squarrose knapweed found on the digital air aerial photography (true color) was compared to a complete census of knapweed conducted on the ground. Although the two study sites had different vegetation species mixes, site histories, and soil conditions, the results were comparable. Despite the large scale of the aerial photography, the knapweed detection rate on the spring photography was only 5%. In contrast, knapweed detection rates on late summer imagery were about 50%. False alarm rates at all seasons were extremely low. Despite the capability shown for weed detection with the RPV and digital camera system, the practical difficulties of using a small RPV in the field requires more research before the system can be operationalized for weed management tasks.     

天宫一号高光谱数据的船只检测实验

针对检测目标进行基于引力场的船只目标增强,计算船只目标的纹理、光谱等指标,基于支持向量机(SVM)方法,利用天宫一号高光谱数据,得到空间探测信息与地面实际目标之间存在精确的相互关系,进行船只检测实验研究.结果表明:天宫一号高光谱数据能够有效的从海水背景中提取船只信息,但船只类型仍难以有效识别.图像的自动分割对于船只的检测非常重要.传感器的多光谱与高分辨率相结合是今后研制的一个主要方向.