Geometric accuracy assessment of the orthorectification process from very high resolution satellite imagery for Common Agricultural Policy purposes

This study has, as its main aim, the assessment of different sensor models to achieve the best geometric accuracy in orthorectified imagery products obtained from IKONOS Geo Ortho Kit and QuickBird basic imagery. The final orthoimages are compared, both geometrically and visually, with the panchromatic orthophotos based on a photogrammetric flight with an approximate scale of 1 : 20 000, which are now used for the European Union Common Agricultural Policy in Andalusia (Spain). Two‐dimensional root mean square (RMS_2d) errors in independent check points are used as accuracy indicators. The ancillary data were generated by high accuracy methods: (1) check and ground control points (GCPs) were measured with a differential global positioning system and (2) an accurate digital elevation model was used for image orthorectification. Two sensor models were used to correct the satellite data: (1) a three‐dimensional (3D) rational function refined by the user with zero‐ (RPC0) or first‐(RPC1) order polynomial adjustment and (2) the 3D Toutin physical model (CCRS). For the IKONOS image, the best results in the final orthoimages (RMS_2d of about 1.15 m) were obtained when the RPC0 model was used. Neither a large number of GCPs (more than nine), nor a better distribution of them, improved the results obtained with the RPC0. For the QuickBird image, the CCRS model generated the best results (RMS_2d of about 1.04 m), although it was sensitive to the number and distribution of the GCPs used in its computation.     

Geocoding RISAT-1 MRS images using bias-compensated RPC models

The purpose of this paper is two-fold. First, the use of the rational polynomial coefficients (RPCs) model is studied for geocoding of Medium Resolution Scan (MRS) ground range (GR) images from the RISAT-1 SAR mission. As the GR images are obtained after many preprocessing image corrections for topographic effect, range cell migration, etc., the number of ground control points (GCPs) required for orthorectification to meet desired geometric quality needs to be established. This assumes importance due to difficulty in visual identification of the GCPs in 18 m-resolution MRS SAR images. Second, three possible methods of bias-compensated RPC models are studied for geocoding. These cases are (A) modified RPC with shift bias, (B) regenerated RPC with shift bias, and (C) regenerated RPC with affine transform model. Experiments are carried out with a set of eight scenes acquired over planar regions especially to avoid the impact of SAR-specific geometric effects such as foreshortening and layover. Geometric accuracy of the orthoimages obtained from these cases is verified at GCPs used for processing as control points and at new GCPs used as check points. It is observed that the modified RPC with the shift bias case required more GCPs to meet the desired geopositioning accuracy. Even though both the regenerated RPC models have shown near similar performance, the regenerated RPC with shift bias compensation is found to reach the required geopositioning accuracy with least number of the GCPs, suggesting it as a strong candidate for realizing operational high precision RISAT-1 geocoded products for multi-temporal data analysis.     

LiDAR-Derived High Quality Ground Control Information and DEM for Image Orthorectification

Orthophotos (or orthoimages if in digital form) have long been recognised as a supplement or alternative to standard maps. The increasing applications of orthoimages require efforts to ensure the accuracy of produced orthoimages. As digital photogrammetry technology has reached a stage of relative maturity and stability, the availability of high quality ground control points (GCPs) and digital elevation models (DEMs) becomes the central issue for successfully implementing an image orthorectification project. Concerns with the impacts of the quality of GCPs and DEMs on the quality of orthoimages inspire researchers to look for more reliable approaches to acquire high quality GCPs and DEMs for orthorectification. Light Detection and Ranging (LiDAR), an emerging technology, offers capability of capturing high density three dimensional points and generating high accuracy DEMs in a fast and cost-effective way. Nowadays, highly developed computer technologies enable rapid processing of huge volumes of LiDAR data. This leads to a great potential to use LiDAR data to get high quality GCPs and DEMs to improve the accuracy of orthoimages. This paper presents methods for utilizing LiDAR intensity images to collect high accuracy ground coordinates of GCPs and for utilizing LiDAR data to generate a high quality DEM for digital photogrammetry and orthorectification processes. A comparative analysis is also presented to assess the performance of proposed methods. The results demonstrated the feasibility of using LiDAR intensity image-based GCPs and the LiDAR-derived DEM to produce high quality orthoimages.     

Orthorectified image mosaic of Antarctica from 1963 Argon satellite photography: image processing and glaciological applications

Using the state‐of‐the‐art digital imaging technology, extended block adjustment, orthorectification and mosaicking, individual Declassified Intelligence Satellite Argon photographic images are precisely assembled into a map quality mosaic of coastal Antarctica. The geometric accuracy of the mosaic is estimated to be approximately equivalent to the original resolution of the Argon photography, which is about 140 m. We compare the Argon mosaic with later satellite images to investigate changes in ice sheet geographic features and dynamical glaciological processes.     

Block adjustment with airbrone SAR very high-resolution images using trajectory constraints

For mapping a large area with airbrone synthetic aperture radar (SAR), very high-resolution (VHR) images using radargrammtry, block adjustment, where strips and blocks of images are processed together, is a preferred method for geometric processing with the advantage of reducing the needed number of ground control points (GCPs). However, the weak intersection geometry between adjacent images from the same strip conflicts with the solvability of the iterative least squares adjustment. In order to overcome this challenge, this article focuses on block adjustment with airbrone SAR VHR images using r-D model combined with trajectory constraints from azimuth tie points (ATPs). Initially, r-D model is briefly introduced. Then, the trajectory constraint equations are proposed and formulated with ATPs. Finally, an improved solution method is applied to increase the computational efficiency of the least squares process. Experiments are carried out using Chinese airbrone SAR VHR images over Shanxi Yanliang, China. The results show that the proposed method can effectively improve the accuracy of block adjustment in both range and elevation direction, with the root mean square error reduced from 0.440 to 0.253 m in range direction and from 0.501 to 0.256 m in elevation direction, respectively. The effects of the distribution and number of GCPs are also investigated, based on which some rules-of-thumb are derived.     

A WTLS-based rational function model for orthorectification of remote-sensing imagery

The rational function model (RFM) is widely applied to orthorectification of aerial and satellite imagery. This article proposes a new method named Ortho-WTLS to solve the RFM in remote-sensing imagery orthorectification. Based on a weighted total least squares (WTLS) estimator, the proposed method allows one to handle coordinates of ground control points (GCPs) that contain errors and are of unequal accuracies. This situation occurs, e.g. if GCPs are automatically selected. In the proposed model, first, the relationship of two linearization methods for an RFM with errors contained in GCPs is investigated and results in a hybrid linearization. Next, based on WTLS, RFM coefficients are estimated with an iterative computation function. Finally, the performance of the Ortho-WTLS method thus obtained is investigated using simulated images and remotely sensed images by collecting GCPs with varying errors. Experimental results show that the Ortho-WTLS method achieves a more robust estimation of model parameters and a higher orthorectification accuracy when compared with standard LS-based RFM estimation. We conclude that the quality of GCPs has a large impact on the accuracy and that an increasing number of low-precision GCPs may lead to a decrease in orthorectification quality.     

Multi-Observed Block Adjustment for Satellite ImagesWithout Ground Control Points

In order to ensure the accuracy of target area’s ground information,it is necessary to do geometric correction for remote sensing images.Geometric correction has a great influence on the application of remote sensing images.Traditional geometric correction needs ground control points.However,it is difficult to obtain ground control points in some places,such as abroad,western China and desert.To improve positioning accuracy without ground control points,multi\|overlapping block adjustment model is built.Different from traditional method,error equations are built depending on multi\|projection in image space of a single object.In this way,error equations can converge to more accurate solutions.By adjusting the rational polynomial coefficients of each image,the positioning errors in different directions are compensated to a certain extent.Thus the positioning accuracy of remote sensing images is improved.First,block adjustment model and error compensation model are built with RPC coefficients.Then,conjugate gradient algorithm is used to solve the error equations iteratively.Finally the RPC coefficients are adjusted to improve the accuracy of positioning without ground control points.The ZY\|3 data test shows that multi\|overlapping block adjustment model increase the plane positioning accuracy of remote sensing images from 19.8m to 12.9m and the method can effectively improve the absolute positioning accuracy of remote sensing images.     

Automatic registration of SeaWiFS and AVHRR imagery

An automatic approach for integrating images from multitemporal and multisensor remote sensing is outlined based on coastlines derived from satellite images. One point on a coastline is taken as a candidate point of ground control points (GCPs). A correlation-relaxation (CR) technique is used to search for the corresponding point in the second image. A decision rule is used to guarantee the correctness of GCPs which are used to compute a polynomial equation for registering two images. The relationship between the accuracy of registration and the number of GCPs indicates that a large number of GCPs will lead to more accurate image registration. The correctness of GCPs can also improve the accuracy of geometric registration. The approach can be used particularly well to register images of coastal areas. Examples are given for registration of SeaWiFS and AVHRR imagery.     

Georeferencing of UK DMC stereo-images without ground control points by exploiting geometric distortions

This article describes a new method for the georeferencing of UK-DMC imagery that does not require ground control points (GCPs). The proposed method utilizes satellite ancillary data, and the inter-imager offsets to determine the geolocation of individual pixels. The major step involved is the direct georeferencing of each pixel using satellite GPS and attitude sensor observations. The known separation between the sensors will allow us to determine the geolocations of all pixels that are taken at the same time using the same exterior orientation parameters. Traditional methods for georeferencing use GCPs, which are expensive and time-consuming tasks. Moreover, the traditional method is not suitable for a pushbroom imager because every scan line has a different set of exterior orientation parameters. Therefore, we propose a direct georeferencing approach without GCPs. The major source of error in direct georeferencing is the error in attitude measurements. The reason for this error is considered to be the thermo-elastic effects on the satellite, which affect the sensors’ positioning, causing deformation in the images. These effects have been modelled as a transformation matrix that describes the extent of deformation in the imagery, and is estimated by exploiting the geometric distortions in stereo Earth images. For this purpose, a mathematical model has been developed to demonstrate how inter-image offsets have been introduced into the imagery and affected by thermal deformation. The mathematical model is based on the sensor configuration of UK-DMC satellites. The model has been further inverted to extract the thermal deformation at a given row and column offset. The thermal deformation matrix has been found to mitigate the pointing error up to 1 km. The accuracy of the thermal deformation estimates is highly dependent on the accuracy of image offsets. The accuracy of image offsets is dependent on several factors, which include the image registration method, window size, along-track separation between the sensors, satellite attitude, and resolution of the sensors.     

Photogrammetric processing of high-resolution airborne and satellite linear array stereo images for mapping applications

This article introduces a mathematical model for photogrammetric processing of linear array stereo images acquired by high-resolution satellite imaging systems such as IKONOS. The experimental result of the generation of simulated IKONOS stereo images based on photogrammetric principles, IKONOS imaging geometry and a set of georeferenced aerial images is presented. An accuracy analysis of ground points derived from the simulated IKONOS stereo images is performed. The impact of the number of GCPs (ground control points), distribution of GCPs, and image measurement errors on the ground point accuracy is investigated. It is concluded that an accuracy of ground coordinates from 2 m to 3 m is attainable with GCPs, and 5 m to 12 m without GCPs. Two data sets of HRSC (high resolution stereo camera) and MOMS (modular opto-electronic multispectral stereo-scanner)-2P are also utilized to test the model and system. The presented data processing method is a key to the generation of mapping products such as digital terrain models (DEM) and digitial shorelines from high-resolution satellite images.     

Spatial accuracy of orthorectified IKONOS imagery and historical aerial photographs across five sites in China

High‐resolution (?1?m) satellite imagery and archival World War II era (WW2) aerial photographs are currently available to support high‐resolution long‐term change measurements at sites across China. A major limitation to these measurements is the spatial accuracy with which this imagery can be orthorectified and co‐registered. We orthorectified IKONOS 1?m resolution GEO‐format imagery and WW2 aerial photographs across five 100?km² rural sites in China with terrain ranging from flat to hilly to mountainous. Ground control points (GCPs) were collected uniformly across 100?km² IKONOS scenes using a differential Global Positioning Systems (GPS) field campaign. WW2 aerial photos were co‐registered to orthorectified IKONOS imagery using bundle block adjustment and rational function models. GCP precision, terrain relief and the number and distribution of GCPs significantly influenced image orthorectification accuracy. Root mean square errors (RMSEs) at GCPs for IKONOS imagery were <2.0?m (0.9–2.0?m) for all sites except the most heterogeneous site (Sichuan Province, 2.6?m), meeting 1:12?000 to 1:4800 US National Map Accuracy Standards and equalling IKONOS Precision and Pro format accuracy standards. RMSEs for WW2 aerial photos ranged from 0.2 to 3.5?m at GCPs and from 4.4 to 6.2?m at independent checkpoints (ICPs), meeting minimum requirements for high‐resolution change detection.     

Surface motion of mountain glaciers derived from satellite optical imagery

A complete and detailed map of the ice-velocity field on mountain glaciers is obtained by cross-correlating SPOT5 optical images. This approach offers an alternative to SAR interferometry, because no present or planned RADAR satellite mission provides data with a temporal separation short enough to derive the displacements of glaciers. The methodology presented in this study does not require ground control points (GCPs). The key step is a precise relative orientation of the two images obtained by adjusting the stereo model of one “slave”' image assuming that the other “master” image is well georeferenced. It is performed with numerous precisely-located homologous points extracted automatically. The strong ablation occurring during summer time on the glaciers requires a correction to obtain unbiased displacements. The accuracy of our measurement is assessed based on a comparison with nearly simultaneous differential GPS surveys performed on two glaciers of the Mont Blanc area (Alps). If the images have similar incidence angles and correlate well, the accuracy is on the order of 0.5 m, or 1/5 of the pixel size. Similar results are also obtained without GCPs. An acceleration event, observed in early August for the Mer de Glace glacier, is interpreted in term of an increase in basal sliding. Our methodology, applied to SPOT5 images, can potentially be used to derive the displacements of the Earth's surface caused by landslides, earthquakes, and volcanoes.     

WorldView-1影像RFM多项式平差模型及其精度分析

简要给出了WorldView-1卫星及传感器的有关性能参数,详细论述了可用于WorldView-1影像数据几何处理的多种RFM(Rational Function Model)多项式平差模型。然后,使用云南地区的WorldView-1影像数据进行了有关试验研究,分别采用九种零阶、一阶和二阶多项式平差模型,在像方改正RFM参数的系统误差。结果表明,当地面控制点在精度、数量与分布等方面质量较好时,各种模型精度基本一致,平面精度可达到1.6个像素(0.9m)左右。此外,本文重点研究了在控制点质量较低的情况下,各种RFM多项式平差模型的改正精度。发现随着控制质量的降低,二阶多项式和一阶多项式改正的精度有显著下降,但零阶多项式改正的精度基本稳定不变。因此,本文认为零阶多项式模型,即平移模型,是一种最简单、适应性最好、精度最高的用于处理WorldView-1影像数据的平差模型。     

Block bundle adjustment of Ikonos in-track images

This letter presents a block bundle adjustment process applied to four Ikonos Geo-product in-track images with few ground control points (GCPs) over a high mountainous area of Venezuela. Various configurations of block bundle adjustment (1-4 images and different GCPs) were evaluated with independent check points. Whatever the number of images, the block bundle adjustment results were consistent with planimetric errors of about @ 5 m to - 7 m. Part of this error was due to the error of the ground data. The evaluation of the final ortho-mosaic with 1:1000 vector lines gives an approximation of relative and absolute errors to be - 2 m and - 3 m to - 4 m with maximum errors of - 6 m and - 10 m, respectively.     

The impact of number and spatial distribution of GCPs on the positional accuracy of geospatial products derived from low-cost UASs

ABSTRACT

Currently, orthophotos and Digital Terrain Models (DTMs) are commonly being generated from low-cost consumer-grade Unmanned Aerial Systems (UASs) using well-known workflows based on photogrammetric and structure-from-motion methods. To achieve high accuracy positioning standards Ground Control Points (GCPs) have to be used in the workflow. In this paper, we assess the impact of number and spatial distribution of GCPs on the positional accuracy of these two geospatial products. By using 3 well-known mapping accuracy standards and 170 checkpoints, the planimetric and altimetric accuracy is assessed for 13 cases of GCPs configuration. The results show that in general, the UAS workflow presents a better accuracy in planimetry than in altimetry. In addition, the application of the mapping standards shows that the two products are suitable for GIS and mapping applications requiring spatial details equivalent to scales less than or equal 1:3000. We also conclude that the insertion of GCPs in the central part of the block does not contribute significantly to an increase in the planimetric accuracy of the geospatial products. Finally, for the proposed minimum photogrammetric overlaps (70% and 35%), the ideal GCP distribution consists of a uniform distribution of GCPs. First, on the central part the block with a horizontal separation of 3 to 4 ground base units for the altimetric component. Second, on the periphery of the block with a separation of 7 to 8 ground base units for the planimetric component.     

基于资源三号卫星数据的数字正射影像图制作研究

资源三号卫星的成功发射填补了我国立体卫星测绘的空白,可以提供优于5m地面分辨率的遥感影像.论文提出基于资源三号卫星遥感数据的数字正射影像图（DOM）制作流程,重点对影像纠正、影像配准、影像融合、影像镶嵌等关键步骤进行研究,并通过实验验证方法的可行性.实验证明该方法具有较强的实用价值和广泛的应用前景.     

CBERS-02B星HR数据几何纠正模型研究

作为目前我国发射的分辨率最高的民用卫星,CBERS-02B星HR数据在大比例尺资源环境调查和基础地理信息更新等方面发挥着重大的作用。为了推广其应用,本文在不能获取卫星轨道星历参数和传感器参数的情况下,对覆盖两种不同地形类别的CBERS-02B星HR影像1级数据进行了多项式、投影变换、RPC等几种不同几何模型的纠正试验,并进行了精度分析与评定。本次试验结果表明:当控制点数量不多时,3阶多项式纠正精度相对较高,对于地形起伏较小的地区,所需的控制点数量为20个左右就可获取较高的精度,而对地形起伏较大的地区,控制点的数量则需要30个以上才能获得较高的精度;无足够控制点时RPC模型纠正精度不理想。     

Detection of attitude constant error and in-orbit calibration for the three-line CCD sensor of the ZY-3 satellite

In-orbit calibration of satellite optical sensors is of crucial importance for improving the accuracy and stability of high-resolution satellite stereo mapping and positioning. For the in-orbit calibration of Ziyuan 3 (ZY-3), the first Chinese three-line stereo mapping satellite, a rigorous imaging geometric model of the three-line sensors is established and the internal systematic error is modelled during analysis of the satellite structure and charge-coupled device (CCD) array. To improve the accuracy and stability of the in-orbit calibration, a new trajectory model, piece-point with weight polynomial model, is used and compared with models in current use. In addition, an attitude constant error model is constructed and applied to reduce attitude errors and provide a more accurate initial attitude value, thus increasing the accuracy and stability of the in-orbit calibration. In addition, ground control point (GCP) stripes, established by partitioning GCPs into stripes, are proposed and used to eliminate random errors during in-orbit calibration. Finally, in-orbit calibration is performed for single and multiple sensors and the result of the calibration is assessed using GCPs and checkpoints. Based on the calibration result, variations of the three-line CCD array on ZY-3 are calculated and analysed in the along- and cross-track directions.     

A novel approach for estimation of residual attitude of a remote-sensing satellite

ABSTRACT

This article presents a novel approach for estimation of the residual attitude of a remote-sensing satellite based on satellite images with ancillary information and ground control points (GCPs). First, a non-linear model which translates the residual errors in roll, pitch, and yaw to scan-errors and pixel-errors in the image space is established. Subsequently, using the model and given scan-errors and pixel-errors at GCPs, an estimate of residual roll, pitch, and yaw based on the least square minimization of residuals in conjunction with the Newton’s method for non-linear optimization is proposed. A simulation is carried out to show that the estimates of residual roll and pitch are within 0.0008° (equivalent to 0.5 pixel) and the residual yaw is within 0.015° (equivalent to 0.75 pixel at the extreme ends) to its true values. The results of the article can be applied to determine the residual attitude of any remote-sensing satellite. We demonstrate our results by estimating the residual attitude based on the data-products of various Indian remote-sensing satellites. The effectiveness of the approach is shown by comparing the results with that of existing technique and it is concluded that the presented technique estimates residual attitude more accurately than the existing method.     

DEM generation using Ziyuan-3 mapping satellite imagery without ground control points

ABSTRACT

This article proposes a digital elevation model (DEM) generation approach using the Shuttle Radar Topography Mission (SRTM) DEM as the elevation constraint without ground control points. First, during the process of image block adjustment, we took advantage of the relatively high vertical accuracy of the SRTM-DEM in flat terrain regions and applied effective constraints on the object-space elevation-corrected value of tie points using the SRTM-DEM, achieving improved vertical accuracy for large-scale block adjustments. Subsequently, for the DEM matching process, multiple two-linear array stereo image pairs were obtained from along-track and across-track images with different look angles over the same region after the block adjustment. Then, the matching result of each stereo image pair underwent weighted fusion, before being used to generate the final DEM product. This approach can effectively enhance the matching quality and grid density of the final DEM product. The DEM generation experiment, using Ziyuan-3 images covering 186,000 km² of Hubei Province, China, showed that the matching quality of the 10 m grid DEM was excellent. The vertical root mean square errors were 1.5 m in the flat regions and 2.96 m in the mountainous regions, thus achieving China’s 1:25,000 scale specification requirement for DEM products.