Very High Resolution Mapping with the Pléiades Satellite Constellation (original) (raw)
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Mapping with Pléiades—End-to-End Workflow
Remote Sensing, 2019
In this work, we introduce an end-to-end workflow for very high-resolution satellite-based mapping, building the basis for important 3D mapping products: (1) digital surface model, (2) digital terrain model, (3) normalized digital surface model and (4) ortho-rectified image mosaic. In particular, we describe all underlying principles for satellite-based 3D mapping and propose methods that extract these products from multi-view stereo satellite imagery. Our workflow is demonstrated for the Pléiades satellite constellation, however, the applied building blocks are more general and thus also applicable for different setups. Besides introducing the overall end-to-end workflow, we need also to tackle single building blocks: optimization of sensor models represented by rational polynomials, epipolar rectification, image matching, spatial point intersection, data fusion, digital terrain model derivation, ortho rectification and ortho mosaicing. For each of these steps, extensions to the st...
3D Mapping with High Resolution Images
2002
High-resolution images, EROS-A1, IKONOS and QuickBird-2 from 2 m to 0.6 m pixel spacing respectively, are geometrically processed with a 3D parametric model developed at the Canada Centre for Remote Sensing. A positioning accuracy of one pixel for the ortho-images can be obtained if 7-10 ground control points (GCPs) used in the 3D parametric model computation are better than 1-pixel accurate (cartographic and image coordinates) and if the digital terrain model (DTM) used in the ortho-rectification process is more accurate than 5-m. When the GCPs are less accurate (around 3-5 m) 20 are necessary to avoid the error propagation through the 3D parametric model. Furthermore, a DTM is extracted from stereo IKONOS images using automatic image matching. A general accuracy of 6.5 m (68% level of confidence) when compared to an airborne lidar DTM (0.5 m accurate) is obtained but is correlated with the land covers. However, the accuracy on bare soils improves to 1.5 m (68% level of confidence). Since the surface heights are included in DTM, the surface and the height of buildings can be extracted from the stereo IKONOS DTM. Different methods are proposed, which should used an expert system to integrate a priori information on the buildings in the different processing steps.
Towards automated DEM generation from high resolution stereo satellite images
International Society for …, 2008
High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). In this paper, a system for highly automated DSM and orthoimage generation based on CARTOSAT-1 imagery is presented. The proposed system processes photometrically corrected level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. Ground control points are used to estimate affine RPC correction. Accurate GCP are not always available, especially for remote areas and large scale reconstruction. In this paper, GCP are automatically derived from lower resolution reference images (Landsat ETM+ Geocover and SRTM DSM). It is worthwhile to note that SRTM has a much higher lateral accuracy than the Landsat ETM+ mosaic, which limits the accuracy of both DSM and orthorectified images. Thus, affine RPC correction parameters are estimated by aligning a preliminary DSM to the SRTM DSM, resulting in significantly improved geolocation of both DSM and orthoimages. Robust stereo matching and outlier removal techniques and prior information such as cloud masks are used during this process. DSM with a grid spacing of 10 m are generated for 9 CARTOSAT-1 scenes in Catalonia. Checks against independent ground truth indicate a lateral error of 3-4 meters and a height accuracy of 4-5 meters. Independently processed scenes align at subpixel level and are well suited for mosaicing.
Topographical Mapping from Stereo Satellite Data-Preliminary Findings
Proceeding of Asian …, 1992
The advent of high resolution Charged-Coupled-Device (CCD) and steerable capability of sensor on board the SPOT satellite provides necessary geometry for the restitution of 3-D vision requirements from its overlapping scenes acquired from the east and west orbit. Unlike the perspective geometry of conventional aerial photography, CCD sensor produces dynamic digital images which can be restituted digitally by auto-stereocorrelation technique. This paper reports the preliminary assessment of 3-dimensional mapping using SPOT-1 PLA data. Results of the test area covering 13km2 north and Kualal Lumpur revealed an accuracy with a standard deviation of 38.7m in planimetry and 18.6m in height. Refinement of ground control point framework and the algorithms adopted in this study is suggested to obtain the required accuracy for producing topographical maps. Due to the limitations in the system, it is suggested to restrict the area of work to consist only one particular terrain in order to achieve the goal.
The Potential of Low Altitude Aerial Data for Large Scale Mapping
Jurnal Teknologi, 2014
Unmanned Aerial Vehicle (UAV) system offers many advantages in several applications such as topographic mapping, thematic mapping, slope mapping, geohazard studies, monitoring, etc. This study utilizes UAV system for large scale mapping by using a digital camera attached to a fixed wing UAV. The main objective of this study is to explore the potential of UAV for large scale mapping and to evaluate the accuracy of the photogrammetric output produced from the UAV system. The UAV was used to acquire low altitude aerial photograph based on photogrammetric technique and subsequently accuracy assessment is performed. The Ground Control Points (GCPs) and Check Points (CPs) were established using GPS rapid static technique for photogrammetric data processing. The GCPs were used in to produce 3D stereomodel and other photogrammetric output while the CP is used for accuracy assessment. For digital image processing of the aerial photograph and map production, Erdas Imagine 8.6 software is employed. For accuracy assessment, the coordinates of the selected points in the 3D stereomodel were compared to the conjugate points observed using GPS and the root mean square error (RMSE) is computed. From this study, the results showed that the achievable RMSE are ± 0.510 m, ± 0.564 m and ± 0.622 m for coordinates X, Y and Z respectively. For this study, the digital map was also produced using the photogrammetric technique and it is compared with an engineering plan produced from ground surveying technique (i.e. total station). From this study, it can be concluded that accuracy of sub-meter is achieved using the UAV system. Also, this study demonstrates that the UAV system has the potential for large scale mapping in the field of surveying and other diversified applications, especially for small area, minimum budget and less manpower.
Generation and quality assessment of stereo-extracted DSM from geoeye-1 and worldview-2 imagery
IEEE Transactions on Geoscience and Remote Sensing, 2014
Digital surface models (DSMs) extracted from 15 different stereo pairs attained by the combination of GeoEye-1 (GE1) and WorldView-2 (WV2) panchromatic very high resolution (VHR) satellite images are tested. Two of them are pure same-date along-track stereo pairs, one from each VHR satellite, whereas the rest are mixed multidate across-track ones. A quality assessment on the DSMs extracted from the aforementioned stereo pairs, involving both accuracy and completeness, is carried out. Several factors are tested such as sensor model used in the bundle adjustment, number of ground control points (GCPs), radiometric characteristics, satellite imaging geometry, time between acquisition dates, and target land cover. A highly accurate light detection and ranging elevation data is used as ground truth. Overall, 3-D rational functions refined by a zero-order polynomial adjustment by using 7 or 12 GCPs performed slightly better regarding both DSM vertical accuracy and completeness. In relation to the pure stereo pairs, the DSM extracted from the GE1 stereo pair attained better vertical accuracy over the whole study area (90th percentile linear error, LE90, of 2.04 m) but lower completeness (74.50%) than the WV2 one (2.56 m and 83.35%, respectively). The undergoing hypothesis is that the blurrier images from WV2 could have influenced in the improvement of the matching success rate while reducing the vertical accuracy of extracted points. When all the 15 stereo pairs are considered, the vertical accuracy mainly depends on the convergence angle. In addition, the temporal difference between acquisition dates turned out to be the most influential factor regarding completeness values.
Automated DSM based georeferencing of Cartosat-1 stereo scenes
High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). A system for highly automated and operational DSM and orthoimage generation based on CARTOSAT-1 imagery is presented, with emphasis on fully automated georeferencing. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. In order to use the images for orthorectification or DSM generation, an affine RPC correction is required. This requires expensive and cumbersome GCP acquisition. In this paper, GCP are automatically derived from lower resolution reference datasets (Landsat ETM+ Geocover and SRTM DSM). The traditional method of collecting the lateral position from a reference image and interpolating the corresponding height from the DEM ignores the higher lateral accuracy of the SRTM dataset. Our method avoids this drawback by using a RPC correction based on DSM alignment, resulting in improved geolocation of both DSM and ortho images. The proposed method is part of an operational CARTOSAT-1 processor at Euromap GmbH for the generation of a high resolution European DSM. Checks against independent ground truth indicate a lateral error of 5-6 meters and a height accuracy of 1-3 meters.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Since remote sensing provides more and more sensors and techniques to accumulate data on urban regions, three-dimensional representations of these complex environments gained much interest for various applications. In order to obtain three-dimensional representations, one of the most practical ways is to generate Digital Surface Models (DSMs) using very high resolution remotely sensed images from two or more viewing directions, or by using LIDAR sensors. Due to occlusions, matching errors and interpolation techniques these DSMs do not exhibit completely steep walls, and in order to obtain real three-dimensional urban models including objects like buildings from these DSMs, advanced methods are needed.
In remote sensing, estimation of the forest stand height is an ever-challenging issue due to the difficulties encountered during the acquisition of data under forest canopies. Stereo optical imaging offers high spatial and spectral resolution ; however, the optical correlation is lower in dense forests than in open areas due to an insufficient number of matching points. Therefore, in most cases height information may be missing or faulty. With their long wavelengths of 0.2 to 1.3 m, P-band and L-band synthetic aperture radars are capable of penetrating forest canopies, but their low spatial resolutions restrict the use of single-tree based forest applications. In this study, airborne laser scanning was used as an effective remote sensing technique to produce large-scale maps of forest stand height. This technique produces very high-resolution point clouds and has a high penetration capability that allows for the detection of multiple echoes per laser pulse. A study area with a forest coverage of approximately 60% was selected in Houston, USA, and a three-dimensional color-coded map of forest stands was produced using a normalized digital surface model technique. Rather than being limited to the number of ground control points, the accuracy of the produced map was assessed with a model-to-model approach using terrestrial laser scanning. In the accuracy assessment, the standard deviation was used as the main accuracy indicator in addition to the root mean square error and normalized median absolute deviation. The absolute geo-location accuracy of the generated map was found to be better than 1 cm horizontally and approximately 40 cm in height. Furthermore, the effects of bias and relative standard deviations were determined. The problems encountered during the production of the map, as well as recommended solutions , are also discussed in this paper.