Insights into the affine model for high-resolution satellite sensor orientation

As a model for sensor orientation and 3D geopositioning for high-resolution satellite imagery (HRSI), the affine transformation from object to image space has obvious advantages. Chief among these is that it is a straightforward linear model, comprising only eight parameters, which has been shown to yield sub-pixel geopositioning accuracy when applied to Ikonos stereo imagery. This paper aims to provide further insight into the affine model in order to understand why it performs as well as it does. Initially, the model is compared to counterpart, ‘rigorous’ affine transformation formulations which account for the conversion from a central perspective to affine image. Examination of these rigorous models sheds light on issues such as the effects of terrain and size of area, as well as upon the choice of reference coordinate system and the impact of the adopted scanning mode of the sensor. The results of application of the affine sensor orientation model to four multi-image Ikonos test field configurations are then presented. These illustrate the very high geopositioning accuracy attainable with the affine model, and illustrate that the model is not affected by size of area, but can be influenced to a modest extent by mountainous terrain, the mode of scanning and the choice of object space coordinate system. Above all, the affine model is shown to be both a robust and practical sensor orientation/triangulation model with high metric potential.     

Precision rectification of high resolution satellite imagery without ephemeris data

The huge capability of high resolution satellite imageries (HRSI), that includes spatial, spectral, temporal and radiometric resolutions as well as stereoscopic vision introduces them as a powerful new source for the Photogrammetry, Remote Sensing and GIS communities. High resolution data increases the need for higher accuracy of data modeling. The satellite orbit, position, attitude angles and interior orientation parameters have to be adjusted in the geometrical model to achieve optimal accuracy with the use of a minimum number of Ground Control Points (GCPs). But most high resolution satellite vendors do not intend to publish their sensor models and ephemeris data. There is consequently a need for a range of alternative, practical approaches for extracting accurate 2D and 3D terrain information from HRSI. The flexibility and good accuracy of the alternative models demonstrated with KFA-1000 and the well-known SPOT level 1A images. A block of eight KFA-1000 space photos in two strips with 60% longitudinal overlap and 15% lateral sidelap and SPOT image with rational function, DLT, 2D projective, polynomials, affine, conformal, multiquadric and finite element methods were used in the test. The test areas cover parts of South and West of Iran. Considering the quality of GCPs, the best result was found with the DLT method with a RMSE of 8.44 m for the KFA-1000 space photos.     

Quality Assessment Of Digital Surface Models Generated From IKONOS Imagery

The growing applications of digital surface models (DSMs) for object detection, segmentation and representation of terrestrial landscapes have provided impetus for further automation of 3D spatial information extraction processes. While new technologies such as lidar are available for almost instant DSM generation, the use of stereoscopic high-resolution satellite imagery (HRSI), coupled with image matching, affords cost-effective measurement of surface topography over large coverage areas. This investigation explores the potential of IKONOS Geo stereo imagery for producing DSMs using an alternative sensor orientation model, namely bias-corrected rational polynomial coefficients (RPCs), and a hybrid image-matching algorithm. To serve both as a reference surface and a basis for comparison, a lidar DSM was employed in the Hobart testfield, a region of differing terrain types and slope. In order to take topographic variation within the modelled surface into account, the lidar strip was divided into separate sub-areas representing differing land cover types. It is shown that over topographically diverse areas, heighting accuracy to better than 3 pixels can be readily achieved. Results improve markedly in feature-rich open and relatively flat terrain, with sub-pixel accuracy being achieved at check points surveyed using the global positioning system (GPS). This assessment demonstrates that the outlook for DSM generation from HRSI is very promising.     

Approximate approaches to geometric corrections of high resolution satellite imagery

The exploitation of different non-rigorous mathematical models as opposed to the satellite rigorous models is discussed for geometric corrections and topographic/thematic maps production of high-resolution satellite imagery (HRSI). Furthermore, this paper focuses on the effects of the number of GCPs and the terrain elevation difference within the area covered by the images on the obtained ground points accuracy. From the research, it is obviously found that non-rigorous orientation and triangulation models can be used successfully in most cases for 2D rectification and 3D ground points determination without a camera model or the satellite ephemeris data. In addition, the accuracy up to the sub-pixel level in plane and about one pixel in elevation can be achieved with a modest number of GCPs.     

Bias-corrected rational polynomial coefficients for high accuracy geo-positioning of QuickBird stereo imagery

The rational function model (RFM) is widely used as an alternative to physical sensor models for 3D ground point determination with high-resolution satellite imagery (HRSI). However, owing to the sensor orientation bias inherent in the vendor-provided rational polynomial coefficients (RPCs), the geo-positioning accuracy obtained from these RPCs is limited. In this paper, the performances of two schemes for orientation bias correction (i.e., RPCs modification and RPCs regeneration) is presented based on one separate-orbit QuickBird stereo image pair in Shanghai, and four cases for bias correction, including shift bias correction, shift and drift bias correction, affine model bias correction and second-order polynomial bias correction, are examined. A 2-step least squares adjustment method is adopted for correction parameter estimation with a comparison with the RPC bundle adjustment method. The experiment results demonstrate that in general the accuracy of the 2-step least squares adjustment method is almost identical to that of the RPC bundle adjustment method. With the shift bias correction method and minimal 1 ground control point (GCP), the modified RPCs improve the accuracy from the original 23 m to 3 m in planimetry and 17 m to 4 m in height. With the shift and drift bias correction method, the regenerated RPCs achieve a further improved positioning accuracy of 0.6 m in planimetry and 1 m in height with minimal 2 well-distributed GCPs. The affine model bias correction yields a geo-positioning accuracy of better than 0.5 m in planimetry and 1 m in height with 3 well-positioned GCPs. Further tests with the second-order polynomial bias correction model indicate the existence of potential high-order error signals in the vendor-provided RPCs, and on condition that an adequate redundancy in GCP number is available, an accuracy of 0.4 m in planimetry and 0.8 m in height is attainable.     

三调正射影像生产中道路扭曲的快速纠正方法

土地调查中数字正射影像(DOM)底图生产是开展资源与环境监测、国情普查的基础.针对正射纠正后影像中存在大量扭曲区域,特别是道路区域,本文提出全新作业模式,即通过编辑道路扭曲区域数字高程模型(DEM),进行实时局部正射纠正来实现.高分辨测绘卫星影像高分二号和北京二号两组实验数据生产表明,该方法实现了影像道路扭曲区域的快速纠正,纠正后道路区域边缘地物没有出现明显错位现象.同时,一定数量道路区域控制点的局部纠正前后精度对比,表明该方法很大程度提高了道路扭曲区域的纠正精度,平面精度优于4 m,满足我国1:1万正射影像生产精度要求.      

An improved geopositioning model of QuickBird high resolution satellite imagery by compensating spatial correlated errors

A lot of studies have been done for correcting the systematic biases of high resolution satellite images (HRSI), which is a fundamental work in the geometric orientation and the geopositioning of HRSI. All the existing bias-corrected models eliminate the biases in the images by expressing the biases as a function of some deterministic parameters (i.e. shift, drift, or affine transformation models), which is indeed effective for most of the commercial high resolution satellite imagery (i.e. IKONOS, GeoEye-1, WorldView-1/2) except for QuickBird. Studies found that QuickBird is the only one that needs more than a simple shift model to absorb the strong residual systematic errors. To further improve the image geopositioning of QuickBird image, in this paper, we introduce space correlated errors (SCEs) and model them as signals in the bias-corrected rational function model (RFM) and estimate the SCEs at the ground control points (GCPs) together with the bias-corrected parameters using least squares collocation. With these estimated SCEs at GCPs, we then predict the SCEs at the unknown points according to their stochastic correlation with SCEs at the GCPs. Finally, we carry out geopositioning for these unknown points after compensating both the biases and the SCEs. The performance of our improved geopositioning model is demonstrated with a stereo pair of QuickBird cross-track images in the Shanghai urban area. The results show that the SCEs exist in HRSI and the presented geopositioning model exhibits a significant improvement, larger than 20% in both latitude and height directions and about 2.8% in longitude direction, in geopositioning accuracy compared to the common used affine transformation model (ATM), which is not taking SCEs into account. The statistical results also show that our improved geopositioning model is superior to the ATM and the second polynomial model (SPM) in both accuracy and reliability for the geopositioning of HRSI.     

Comparison of Planimetric and Thematic Accuracy of OrbView-3 and IKONOS Images

Spatial mapping from space using high-resolution satellite sensor data instead of conventional data collection techniques widely gained popularity. This study aims to analyze the planimetric and thematic accuracy of high-resolution OrbView-3 and IKONOS orthoimages. OrbView-3 and IKONOS images of a test area were acquired and these images were geometrically corrected using rational polynomial functions to conduct accuracy assessment. 40 Ground Control Points (GCPs) generated from static Global Positioning System (GPS) survey were used in the orthorectification procedure. 182 Test Points (TPs) produced from terrestrial surveying technique were used to analyze the accuracy of orthorectifications. Root Mean Square Error (RMSE) values obtained for GCPs and TPs were used to determine the planimetric accuracy of these images. Thematic accuracy analyses were conducted in radiometric and spatial base. Transects, lines and polygons were created to analyze the radiometric quality of data sets and to determine minimum distinguishable distance and distinguishable area. Both planimetric and thematic accuracy analyses illustrated that OrbView-3 and IKONOS images could be used to create 1:10000 scale map of the concerned region with appropriate planimetric and thematic quality.     

嫦娥一号立体影像的摄影测量内部精度估算

本文采用APOLLO影像模拟生成的嫦娥一号三线阵CCD影像及其卫星的轨道与姿态模拟参数,按等效框幅像片(EFP)法和自由外方位元素(FEO)法分别计算摄影测量坐标系内的外方位元素及模型点坐标,生成了数字高程模型(DEM)、等高线、正射影像及三维地形仿真影像,评估了从模拟月球三线阵CCD影像生成的摄影测量成果的预期精度。     

资源三号测绘卫星影像平面和立体区域网平差比较

针对弱交会条件下卫星遥感影像区域网平差无法正确求解的问题,本文提出了利用数字高程模型（DEM）作为高程约束的平面区域网平差方法提高其对地目标定位精度的策略。首先,选取带仿射变换项的有理函数模型（RFM）作为卫星影像平面区域网平差的数学模型。其次,在平差过程中更新连接点的地面坐标时仅求解地面点的平面坐标,高程值利用DEM进行内插获得。最后,在布设少量控制点的情况下通过平面区域网平差求解所有参与平差的卫星影像定向参数和连接点的地面平面坐标。利用两个地区的资源三号正视影像的平面区域网平差以及前正后三视影像的立体区域网平差的对比试验表明,对于资源三号卫星影像在1:50000DEM的支持下,平面平差可以达到和立体平差相当平面精度。对于近似垂直正视的资源三号影像,全球1km格网的DEM和90m格网的SRTM可以取代1:50000DEM作为高程控制,平面精度几乎没有损失。最终,试验结果证明了平面区域网平差方法的有效性和可行性。     

直线特征约束的高分辨率卫星影像区域网平差方法

以"像方观测直线与像方预测直线必须重合"作为几何约束条件,以有理函数模型(RFM)作为高分辨率卫星影像的几何处理模型,提出了一种直线特征约束的高分辨率卫星影像区域网平差方法。本文方法仅需像方直线与物方直线相对应,无须像方直线上的像点与物方直线上的地面点一一对应。通过对圣迭戈试验区的两景IKONOS影像、斯波坎试验区的两景QuickBird影像和普罗旺斯试验区的两景SPOT-5影像进行试验,结果表明:本文方法可以充分利用直线特征作为控制条件,有效补偿RPC参数中的系统误差,获得的IKONOS、QuickBird和SPOT-5影像区域网平差的平面与高程精度均优于1个像素。     

线阵推扫式影像外定向的一种新算法

线阵推扫式影像外方位元素间的强相关性,导致法方程病态,外方位元素的最小二乘估计值误差较大.本文提出采用岭-压缩组合估计解决线阵列推扫式影像的外定向问题.该算法是综合岭估计和压缩估计的一种新有偏算法,它通过对最小二乘估计值的不同分量进行不同比例的压缩使估计值最优.文中采用10 m分辨率的SPOT 1全色影像和2.5 m分辨率的SPOT 5全色影像进行实验,并与商业遥感软件Erdas的实验结果进行比较.研究结果表明该算法能有效地克服线阵推扫式影像外方位元素间的相关性,定位精度较高,定向点精度在1个像素内,检查点精度在1.5个像素内,达到Erdas软件的定位精度.     

Comparison of four UAV georeferencing methods for environmental monitoring purposes focusing on the combined use with airborne and satellite remote sensing platforms

This work is aimed at the environmental remote sensing community that uses UAV optical frame imagery in combination with airborne and satellite data. Taking into account the economic costs involved and the time investment, we evaluated the fit-for-purpose accuracy of four positioning methods of UAV-acquired imagery: 1) direct georeferencing using the onboard raw GNSS (GNSSNAV) data, 2) direct georeferencing using Post-Processed Kinematic single-frequency carrier-phase without in situ ground support (PPK1), 3) direct georeferencing using Post-Processed Kinematic double-frequency carrier-phase GNSS data with in situ ground support (PPK2), and 4) indirect georeferencing using Ground Control Points (GCP). We tested a multispectral sensor and an RGB sensor, onboard multicopter platforms. Orthophotomosaics at <0.05 m spatial resolution were generated with photogrammetric software. The UAV image absolute accuracy was evaluated according to the ASPRS standards, wherein we used a set of GCPs as reference coordinates, which we surveyed with a differential GNSS static receiver. The raw onboard GNSSNAV solution yielded horizontal (radial) accuracies of RMSEr≤1.062 m and vertical accuracies of RMSEz≤4.209 m; PPK1 solution gave decimetric accuracies of RMSEr≤0.256 m and RMSEz≤0.238 m; PPK2 solution, gave centimetric accuracies of RMSEr≤0.036 m and RMSEz≤0.036 m. These results were further improved by using the GCP solution, which yielded accuracies of RMSEr≤0.023 m and RMSEz≤0.030 m. GNSSNAV solution is a fast and low-cost option that is useful for UAV imagery in combination with remote sensing products, such as Sentinel-2 satellite data. PPK1, which can register UAV imagery with remote sensing products up to 0.25 m pixel size, as WorldView-like satellite imagery, airborne lidar or orthoimagery, has a higher economic cost than the GNSSNAV solution. PPK2 is an acceptable option for registering remote sensing products of up to 0.05 m pixel size, as with other UAV images. Moreover, PPK2 can obtain accuracies that are approximate to the usual UAV pixel size (e.g. co-register in multitemporal studies), but it is more expensive than PPK1. Although indirect georeferencing can obtain the highest accuracy, it is nevertheless a time-consuming task, particularly if many GCPs have to be placed. The paper also provides the approximate cost of each solution.     

利用双高度层ADS40影像进行区域网空中三角测量

空中三角测量是利用航摄像片与被摄目标之间的空间几何位置关系,根据少量的野外控制点,计算节点的平面坐标与高程以及航摄像片的外方位元素的方法,是摄影测量过程中的重要环节。随着导航定位技术的发展,高精度POS装置被广泛安装到航拍飞机上,用于记录航拍时刻相机的位置与姿态,从而进行辅助空中三角测量。本文研究利用双高度层的ADS40航线影像,结合POS数据,利用一定数量的控制点,基于ORIMA软件进行空中三角测量,并对其解算精度与同一区域单高度层航线影像的空三精度进行比较。     

CBERS-02B卫星遥感影像的区域网平差

针对中巴资源一号卫星(CBERS-02B)卫星遥感影像姿态角误差较大的特点,提出了利用区域网平差方法提高其对地目标定位精度的策略和具体计算过程。首先对参与平差的每景影像选取4个地面控制点进行影像姿态角常差检校,然后采用与地形无关方案解求各自的RPC参数,最后选取带仿射变换项的有理函数模型(RFM)进行多重覆盖影像的区域网平差。对两个地区的0级CBERS-02B单条CCD立体影像对的区域网平差试验表明,对地目标定位的平面和高程精度均达到了±3个像元的水平,且高程精度明显优于平面精度。相对于常规的卫星遥感影像区域网平差方法,平面和高程精度均有明显提升,几乎达到国外同等高分辨率卫星遥感影像的几何定位精度。这说明中国卫星遥感影像亦具有较好的几何定位潜力,在区域网平差之前进行系统误差预改正是必要和可行的。     

基于GPS实测控制点的SPOT 5 1A数据几何校正方法精度比较

采用高精度的星基差分GPS实测控制点对SPOT 5 1A数据几何校正方法进行比较，对校正误差的产生原因进行分析。结果表 明，正射模型法的校正精度远高于多项式法的校正精度;多项式法在X方向上的误差远大于Y方向上的误差；正射模型法的误差在2个 方向上差别不大。卫星扫描角度引起的像元畸变是多项式方法产生较大误差的重要原因。     

单侧控制条件下SPOT5 HRG影像的定向试验

高分辨率卫星影像已经成为获取地理信息的重要数据源,而其定向是一项关键技术。本文利用单侧不同数量及分布的控制点对SPOT5 HRG影像进行了定向试验,探讨了在单侧控制条件下SPOT5 HRG影像的定向精度情况,为地面控制点获取较困难地区的影像定向提供了一条参考途径。     

Assessing optical earth observation systems for mapping and monitoring temporary ponds in arid areas

Remote sensing methods for locating and monitoring temporary ponds over large areas in arid lands were tested on a study site in Northern Senegal. Three main results are presented, validated with field data and intended to highlight different spectral, spatial and temporal characteristics of the methods: (1) Among several water indices tested, two Middle Infrared-based indices (MNDWI—Modified Normalized Difference Water Index and NDWI₁—Normalized Difference Water Index) are found to be most efficient; (2) an objective method is given prescribing the necessary sensor spatial resolution in terms of minimal detected pond area; and (3) the potential of multi-temporal MODIS imagery for tracking the filling phases of small ponds is illustrated. These results should assist in epidemiological studies of vector-borne diseases that develop around these ponds, but also more generally for land and water management and preservation of threatened ecosystems in arid areas.     

提高卫星三线阵CCD影像空中三角测量精度及摄影测量覆盖效能

利用数字模拟方法,进一步探讨了类似MOMS-02参数的卫星三线阵CCD影像单航线、航线首末4角隅设一个控制点(以下简写为单航线4控点)的空中三角测量高程精度低的问题。研究得出,宽高比特别小(1:9)只是原因之一,更主要的因素还在于平差整过程数学关系带有近似性(包括EFP法和定向片法)。提出了改善精度的措施,并拟订了提高卫星三线阵CCD影像空中三角测量精度及摄影测量覆盖效能的系统。模拟计算表明,航线长度可以≥2B,在有外方位元素或无外方位元素少量控制点条件下,不论二线交会区,还是三线交会区均可达到高程精度为6m的摄影测量成果。     

基于中间件的高分辨率卫星影像正射纠正的分布式处理

当前摄影测量系统软件正向分布式并行处理方向发展,目前大家研究比较多的是在高性能计算机系统(如刀片机)下进行并行数据处理,而研究普通PC机集群分布式并行处理数据则相对比较少。因此本文在多PC机环境下按照分布式处理思想提出了一种对高分辨率卫星影像进行正射纠正的基于中间件模式的分布式并行处理系统,着重叙述了该系统的组成以及任务调度中的相关处理等问题,并在实践中验证了它的可行性。