Improving georeferencing accuracy of Very High Resolution satellite imagery using freely available ancillary data at global coverage

ABSTRACT

While impressive direct geolocation accuracies better than 5.0?m CE90 (90% of circular error) can be achieved from the last DigitalGlobe’s Very High Resolution (VHR) satellites (i.e. GeoEye-1 and WorldView-1/2/3/4), it is insufficient for many precise geodetic applications. For these sensors, the best horizontal geopositioning accuracies (around 0.55?m CE90) can be attained by using third-order 3D rational functions with vendor’s rational polynomial coefficients data refined by a zero-order polynomial adjustment obtained from a small number of very accurate ground control points (GCPs). However, these high-quality GCPs are not always available. In this work, two different approaches for improving the initial direct geolocation accuracy of VHR satellite imagery are proposed. Both of them are based on the extraction of three-dimensional GCPs from freely available ancillary data at global coverage such as multi-temporal information of Google Earth and the Shuttle Radar Topography Mission 30?m digital elevation model. The application of these approaches on WorldView-2 and GeoEye-1 stereo pairs over two different study sites proved to improve the horizontal direct geolocation accuracy values around of 75%.     

Absolute geolocation accuracy of high-resolution spotlight TerraSAR-X imagery – validation in Wuhan

TerraSAR-X (TSX) can acquire high-resolution SAR images and due to its high orbit precision as well as its ability to acquire data from different off-nadir viewing angles, the high-precision stereo geolocation can be obtained. In this study, we investigate the absolute geolocation accuracy of TSX high-resolution images in Wuhan, China. We present a direct stereo SAR geolocation method and analyze the 2D and 3D geoposition accuracy of two corner reflectors. The sub-meter localization accuracy was achieved using only atmospheric correction information available in the TSX metadata.     

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.     

Mitigation of atmospheric perturbations and solid Earth movements in a TerraSAR-X time-series

The TerraSAR-X (TSX) synthetic aperture radar (SAR) marks the recent emergence of a new generation of spaceborne radar sensors that can for the first time lay claim to localization accuracies in the sub-meter range. The TSX platform’s extremely high orbital stability and the sensor’s hardware timing accuracy combine to enable direct measurements of atmospheric refraction and solid Earth movements. By modeling these effects for individual TSX acquisitions, absolute pixel geolocation accuracy on the order of several centimeters can be achieved without need for even a single tiepoint. A 16-month time series of images was obtained over a fixed test site, making it possible to validate both an atmospheric refraction and a solid Earth tide model, while at the same time establishing the instrument’s long-term stability. These related goals were achieved by placing trihedral corner reflectors (CRs) at the test site and estimating their phase centers with centimeter-level accuracy using differential GPS (DGPS). Oriented in pairs toward a given satellite track, the CRs could be seen as bright “points” in the images, providing a geometric reference set. SAR images from the high-resolution spotlight (HS) mode were obtained in alternating ascending and descending orbit configurations. The highest-resolution products were selected for their small sample dimensions, as positions can be more precisely determined. Based on the delivered product annotations, the CR image positions were predicted, and these predictions were compared with their measured image positions both before and after compensation for atmospheric refraction and systematic solid Earth deviations. It was possible to show that when the atmospheric distortion and Earth tides are taken into account, the TSX HS products have geolocation accuracies far exceeding the specified requirements. Furthermore, this accuracy was maintained for the duration of the 16-month test period. It could be demonstrated that with a correctly calibrated sensor, and after accounting for atmospheric and tidal effects, tiepoint-free geolocation is possible with TSX with an absolute product accuracy of about 5 cm.     

粗／精轨道数据对卫星InSAR DEM精度影响的对比分析

本文在介绍InSAR系统中卫星轨道状态矢量内插方法的基础上，从理论和实际两方面分析了轨道数据误差对参考椭球面相位、地形干涉相位和数字高程模型（DEM）精度的影响。以上海局部地区作为实验场，采用ERS-1／2卫星SAR影像数据，分别使用欧洲空间局粗略轨道数据和荷兰Delft大学空间研究中心精密轨道数据进行了干涉处理，生成了两种情况下的DEM，并对相关精度进行了对比与分析。研究结果表明，使用精轨数据建立的DEM的精度明显高于基于粗轨数据建立的DEM的精度。     

Evaluation of the RPC Model for Ziyuan-3 Three-line Array Imagery

Ziyuan-3 (ZY-3) satellite is the first civilian stereo mapping satellite in China and was designed to achieve the 1: 50,000 scale mapping for land and ocean. Rigorous sensor model (RSM) is required to build the relationship between the three-dimensional (3D) object space and two-dimensional (2D) image space of ZY-3 satellite imagery. However, each satellite sensor has its own imaging system with different physical sensor models, which increase the difficulty of geometric integration of multi-source images with different sensor models. Therefore, it is critical to generate generic model, especially rational polynomial coefficients (RPCs) of optical imagery. Recently, relatively a few researches have been conducted on RPCs generation to ZY-3 satellite. This paper proposes an approach to evaluate the performance of RPCs generation from RSM of ZY-3 imagery. Three scenario experiments with different terrain features (such as ocean, hill, city and grassland) are designed and conducted to comprehensively evaluate the replacement accuracies of this approach and analyze the RPCs fitting error. All the experimental results demonstrate that the proposed method achieved the encouraging accuracy of better than 1.946E?04 pixel in both x-axis direction and y-axis direction, and it indicates that the RPCs are suitable for ZY-3 imagery and can be used as a replacement for the RSM of ZY-3 imagery.     

Direct georeferencing of oblique and vertical imagery in different coordinate systems

Reconstruction of 3D models through integrating vertical and oblique imagery has been studied extensively. For a 3D reconstruction, object point cloud coordinates could be calculated using direct georeferencing (DG) obtained from the direct orientation data of a GPS/INS system. This paper implemented DG approaches for vertical and oblique imagery in the earth centered earth fixed frame (e-frame), local tangent frame (l-frame), and map projection frame (p-frame), respectively. In the p-frame, the earth curvature correction formulas were derived through naturalizing oblique imagery to vertical imagery to achieve a high positioning precision. Five basic stereo-pair models for vertical and oblique imagery were simulated to verify the positioning accuracy of different frames. Simulation experiments showed that DG in the e-frame and l-frame of these five scenarios were rigorous, and no systematic errors were imported by the DG model as these frames are Cartesian. DG in the p-frame has obvious systematic errors which are aroused by the earth curvature and projection deformation unconformity in the vertical and horizontal directions. These errors, however, can be compensated effectively through correcting image coordinates of the oblique imagery by extending the standard image coordinate correction approach and the exterior orientation (EO) height term. After the correction, the absolute positioning error is lower than 1/20 GSD for simulation test-1. In the p-frame, the process is straightforward, and it is convenient for producing maps. For high accuracy DG, though, it is recommended to adopt e-frame or l-frame options.     

地性线的山地区域的卫星影像几何精纠正

提出了一种山地区域基于DEM地性线的控制纠正新方法,该方法以数字地形模型DEM为无几何变形的控制基准纠正卫星影像。阐述了提取沟谷、山脊、山峰和凹地区域的地性线的原理和算法,给出了山地区域基于地性线进行卫星图像几何精纠正实施步骤,进一步讨论了地性线提取、控制点采集存在的问题,以及解决问题的途径。实验结果表明,对于山地区域,地性线的空间数量数倍于水系、道路等常规地图层;地性线来源于DEM,其空间稳定性和可靠性更高,可以用于山地区域的卫星影像的严格控制纠正。用该方法进行几何纠正处理,几何误差能控制在一个像元的水平上。     

FY-3B微波成像仪资料的地理定位误差与订正

风云3号B星(FY-3B)上的微波成像仪(MWRI)通过10.65 GHz,18.7 GHz,23.8GHz,36.5 GHz和189.0 GHz5个频率的双极化通道对地球表面进行监测。自卫星发射至今,MWRI资料的地理定位误差还未进行深入研究。为了提高FY-3B MWRI L1级数据地理定位精度,基于海、陆响应的升、降轨亮温差理论NDM(Node Differential Method),通过卫星位置和速度矢量建立卫星姿态模型、采用非线性最优化方法估计卫星姿态偏差,进而对MWRI 89 GHz通道的地理定位误差进行分析与订正。结果表明,2015年1—9月份俯仰、滚动和偏航角度的平均偏差分别为-0.220°,0.068°和0.062°,对应沿轨误差大约3—4 km,跨轨误差小于1 km。定位误差订正后,地中海、澳大利亚区域海岸线附近的升降轨亮温差明显减小;观测亮温在红海和南美洲东南部区域的分布和海岸线更加吻合,定位精度得到明显提高。     

基于几何配准的多模式SAR影像配准及其误差分析

星载合成孔径雷达影像干涉处理时所需方位向配准精度因成像模式的差异而有所不同,目前在精密轨道条件下以几何配准为基础辅以影像信息的配准方案因其严格的理论模型和较高的精度成为干涉处理的首选。本文以TerraSAR-X影像为例,论证了不同成像模式影像所需的配准精度和卫星轨道精度,并通过理论分析和试验证明了精密轨道条件下,利用几何配准即可满足TerraSAR-X等卫星的条带模式影像干涉处理的需要;聚束模式影像需要在几何配准的基础上利用影像相干性或谱分集进一步优化配准结果。鉴于增强谱分集偏移量估计精度最高,本文进一步利用增强谱分集对比分析了不同轨道不同DEM条件下的几何配准误差。研究结果表明:卫星轨道切向误差是几何配准的主要误差源,目前常用3种DEM几何配准差异远小于0.001个像素,均可满足Sentinel-1影像干涉配准的需要。     

高分辨率光学卫星遥感影像高精度无地面控制精确处理的理论与方法

卫星影像全球无地面控制高精度几何定位是卫星摄影测量技术发展追求的主要目标,也是实现困难地区和境外地区测图的关键支撑技术。本文围绕我国国产遥感卫星的技术发展,详细论述了高分辨率光学卫星遥感影像高精度无地面控制几何定位的理论与方法,在天星地一体化全链路误差建模分析的基础上,提出了在轨几何定标理论与方法、稳态重成像几何处理模型与方法及大规模无地面控制区域网平差理论与方法。将本文方法应用于资源三号卫星影像的数据处理,试验结果满足1∶50 000测图精度,证明了理论和方法的正确性。     

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.     

Orthorectification of VHR optical satellite data exploiting the geometric accuracy of TerraSAR-X data

Orthorectification of satellite data is one of the most important pre-processing steps for application oriented evaluations and for image data input into Geographic Information Systems. Although high- and very high-resolution optical data can be rectified without ground control points (GCPs) using an underlying digital elevation model (DEM) to positional root mean square errors (RMSEs) between 3 m and several hundred meters (depending on the satellite), there is still need for ground control with higher precision to reach lower RMSE values for the orthoimages. The very high geometric accuracy of geocoded data of the TerraSAR-X satellite has been shown in several investigations. This is due to the fact that the SAR antenna measures distances which are mainly dependent on the terrain height and the position of the satellite. The latter can be measured with high precision, whereas the satellite attitude need not be known exactly. If the used DEM is of high accuracy, the resulting geocoded SAR data are very precise in their geolocation. This precision can be exploited to improve the orientation knowledge and thereby the geometric accuracy of the rectified optical satellite data. The challenge is to match two kinds of image data, which exhibit very different geometric and radiometric properties. Simple correlation techniques do not work and the goal is to develop a robust method which works even for urban areas, including radar shadows, layover and foreshortening effects. First the optical data have to be rectified with the available interior and exterior orientation data or using rational polynomial coefficients (RPCs). From this approximation, the technique used is the measurement of small identical areas in the optical and radar images by automatic image matching, using a newly developed adapted mutual information procedure followed by an estimation of correction terms for the exterior orientation or the RPC coefficients. The matching areas are selected randomly from a regular grid covering the whole imagery. By adjustment calculations, parameters from falsely matched areas can be eliminated and optimal improvement parameters are found. The original optical data are orthorectified again using the delivered metadata together with these corrections and the available DEM. As proof of method the orthorectified data from IKONOS and ALOS-PRISM sensors are compared with conventional ground control information from high-precision orthoimage maps of the German Cartographic Survey. The results show that this method is robust, even for urban areas. Although the resulting RMSE values are in the order of 2-6 m, the advantage is that this result can be reached even for optical sensors which do not exhibit low RMSE values without using manual GCP measurements.     

基于有理多项式模型的GF4卫星区域影像平差处理方法及精度验证

分析了我国首颗静止轨道光学遥感卫星高分四号(GF4)特有的区域成像模式的几何特性,基于静止轨道成像基高比较小的几何特性提出一种利用平均高程面的区域网平差方法。该方法针对GF4卫星影像构建了基于有理多项式模型RFM的区域网平差模型,并在无控制条件下,对GF4卫星区域影像进行区域网平差处理,解决了GF4号区域影像由于定轨误差、定姿误差、大气折光以及镜头畸变等因素导致的拼接精度较低的问题。最后,通过两组真实数据试验对本文方法的精度及有效性进行了验证,同时分析了采用不同的误差补偿模型对于平差结果精度的影响。     

Direct georeferencing of airborne LiDAR data in national coordinates

The topographic mapping products of airborne light detection and ranging (LiDAR) are usually required in the national coordinates (i.e., using the national datum and a conformal map projection). Since the spatial scale of the national datum is usually slightly different from the World Geodetic System 1984 (WGS 84) datum, and the map projection frame is not Cartesian, the georeferencing process in the national coordinates is inevitably affected by various geometric distortions. In this paper, all the major direct georeferencing distortion factors in the national coordinates, including one 3D scale distortion (the datum scale factor distortion), one height distortion (the earth curvature distortion), two length distortions (the horizontal-to-geodesic length distortion and the geodesic-to-projected length distortion), and three angle distortions (the skew-normal distortion, the normal-section-to-geodesic distortion, and the arc-to-chord distortion) are identified and demonstrated in detail; and high-precision map projection correction formulas are provided for the direct georeferencing of the airborne LiDAR data. Given the high computational complexity of the high-precision map projection correction approach, some more approximate correction formulas are also derived for the practical calculations. The simulated experiments show that the magnitude of the datum scale distortion can reach several centimeters to decimeters for the low (e.g., 500 m) and high (e.g., 8000 m) flying heights, and therefore it always needs to be corrected. Our proposed practical map projection correction approach has better accuracy than Legat’s approach,¹ but it needs 25% more computational cost. As the correction accuracy of Legat’s approach can meet the requirements of airborne LiDAR data with low and medium flight height (up to 3000 m above ground), our practical correction approach is more suitable to the high-altitude aerial imagery. The residuals of our proposed high-precision map projection correction approach are trivial even for the high flight height of 8000 m. It can be used for the theoretical applications such as the accurate evaluation of different GPS/INS attitude transformation methods to the national coordinates.     

基于少量控制点的Radarsat-2影像快速几何纠正技术研究

Radarsat-2卫星依据其搭载的GPS接收机可实现3倍中误差小于60m的精确实时定轨。由此本文提出依据其影像元数据信息实现快速几何纠正的方法,该方法利用少量的几个控制点来消除Radarsat-2影像与待纠正参考系间的系统误差。从而实现Radarsat-2影像的快速几何纠正。本文并依据SAR斜距成像原理的纠正公式和实地采集的GPS数据,验证了元数据中所提供RPF模型的内部精度和外部符合精度。通过实验验证了本快速纠正技术可以获得中误差小于2个像素的平面几何纠正精度。     

Automated geometric correction of multispectral images from High Resolution CCD Camera (HRCC) on-board CBERS-2 and CBERS-2B

China–Brazil Earth Resource Satellite (CBERS) imagery is identified as one of the potential data sources for monitoring Earth surface dynamics in the event of a Landsat data gap. Currently available multispectral images from the High Resolution CCD (Charge Coupled Device) Camera (HRCC) on-board CBERS satellites (CBERS-2 and CBERS-2B) are not precisely geo-referenced and orthorectified. The geometric accuracy of the HRCC multispectral image product is found to be within 2–11 km. The use of CBERS-HRCC multispectral images to monitor Earth surface dynamics therefore necessitates accurate geometric correction of these images. This paper presents an automated method for geo-referencing and orthorectifying the multispectral images from the HRCC imager on-board CBERS satellites. Landsat Thematic Mapper (TM) Level 1T (L1T) imagery provided by the U.S. Geological Survey (USGS) is employed as reference for geometric correction. The proposed method introduces geometric distortions in the reference image prior to registering it with the CBERS-HRCC image. The performance of the geometric correction method was quantitatively evaluated using a total of 100 images acquired over the Andes Mountains and the Amazon rainforest, two areas in South America representing vastly different landscapes. The geometrically corrected HRCC images have an average geometric accuracy of 17.04 m (CBERS-2) and 16.34 m (CBERS-2B). While the applicability of the method for attaining sub-pixel geometric accuracy is demonstrated here using selected images, it has potential for accurate geometric correction of the entire archive of CBERS-HRCC multispectral images.     

Mapping spiny aster infestations with QuickBird imagery

QuickBird satellite imagery acquired in June 2003 and September 2004 was evaluated for detecting the noxious weed spiny aster [Leucosyris spinosa (Benth.) Greene] on a south Texas, USA rangeland area. A subset of each of the satellite images representing a diversity of cover types was extracted and used as a study site. The satellite imagery had a spatial resolution of 2.8 m and contained 11-bit data. Unsupervised and supervised classification techniques were used to classify false colour composite (green, red, and near-infrared bands) images of the study site. Imagery acquired in June was superior to that obtained in September for distinguishing spiny aster infestations. This was attributed to differences in spiny aster phenology between the two dates. An unsupervised classification of the June image showed that spiny aster had producer's and user's accuracies of 90% and 93.1%, respectively, whereas a supervised classification of the June image had producer's and user's accuracies of 90% and 81.8%, respectively. These results indicate that high resolution satellite imagery coupled with image analysis techniques can be used successfully for detecting spiny aster infestations on rangelands.     

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。     

Resourcesat (IRS-P6) value added data products

Remote sensing data products need to meet stringent geodetic and geometric accuracy specifications irrespective of intended user applications. Georeferencing is the basic processing step towards achieving this goal. Having known the imaging geometry and mechanism, the mathematical models built with the use of orbit and attitude information of the spacecraft can correct the remote sensing data for its geometric degradations only up to system level accuracy (IRS-P6 DP Team, 2000). The uncertainties in the orbit and attitude information will not allow the geometric correction model to generate products of accuracy that can meet user requirements unless Ground Control Points (GCP) are used as reference geo-location landmarks. IRS-P6 data processing team has been entrusted with developing a software system to generate data products that will have desired geodetic and geometric accuracies with known limitations. The intended software system is called the Value Added Data Products System (VADS). Precision corrected, Template Registered, Merged and Ortho Rectified products are the value added products planned with VADS.