Accuracy comparison of Pléiades satellite ortho-images using GPS device based GCPs against TerraSAR-X-based GCPs

Henrico, Ivan; Combrinck, Ludwig; Eloff, Corne

doi:10.4314/sajg.v5i3.7

Cited by 4 publications

(6 citation statements)

References 7 publications

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“…However, by applying a stratified distribution and by arranging the GCPs within the project area, it is also possible to improve the vertical accuracy (Martínez-Carricondo et al, 2018). Henrico et al (2016) evaluated the geolocation accuracy of high-resolution satellite ortho-images by using different ground control methods. The findings from their research indicate that manual GCPs produce a more accurate ortho-image in terms of positional accuracy.…”

Section: Gnss Surveymentioning

confidence: 99%

Classification of 3D UAS-SfM Point Clouds in the Urban Environment

Ntuli,

Forbes

2023

SA J of Geomatics

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The classification of three-dimensional (3D) point clouds derived through the use of cost-effective and time-efficient photogrammetric technologies can provide helpful information for applications, particularly in the mapping context. This paper presents a practical study of 3D Unmanned Aerial System (UAS) – Structure-from-Motion (SfM) point cloud classification using mainly open-source software. Following a supervised classification approach that makes use of only the dimensionality of points, the entire scene was classified into three land-cover categories: ground, high vegetation, and buildings. By applying the above-mentioned approach, the level of competence in classifying a 3D point cloud of a heterogeneous scene situated in the University of KwaZulu-Natal, South Africa, was evaluated. The resulting overall classification accuracy of 81.3%, with a Kappa coefficient of 0.70, was determined by means of a confusion matrix. The results achieved indicate the potential use of open-source software and 3D UAS-SfM point cloud classification in mapping and monitoring complex environments and in other applications that might arise.

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Section: Gnss Surveymentioning

confidence: 99%

Classification of 3D UAS-SfM Point Clouds in the Urban Environment

Ntuli,

Forbes

2023

SA J of Geomatics

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“…16 Pléiades twins (1A&1B) are being subjected for various type of research. Its post-launch geometric quality was handled by the researchers such as Bernard et al, 17 deLussy et al, 18 Delvit et al, 19 Greslou and deLussy, 13 Delvit et al, Michel et al, 20 de Franchis et al, 11 Perko et al, 21 Postelniak, 22 Poli et al, 23 Abduelmola, 24 Gim and Shin, 25 Henrico et al, 26 Dukuzemariya, 27 Kartal et al, 28 and Perko et al [29][30][31] Its height accuracy was also subjected by the studies of Durand et al, 32 Berthier et al, 33 Giraud et al, 34 Stumpf et al, 35 Eisank et al, 36 Jacobsen, 37 Nasir et al, 38 Noh and Howat, 39 Qayyum et al, 40 Ghuffar, 41 Ok et al, 42 Sadeq et al, 43 Sofia et al, 44 Mertes et al, 45 Peng et al, 46 Ok et al, 47 Piermattei et al, 48 and Loghin et al 49 Moreover, the author also managed three projects for handling the Pléiades 1A tri-stereo panchromatic and VNIR images with respect to the 2/3D georeferencing accuracy, image quality, generation and validation of Digital Surface Model (DSM)/Digital Terrain Model (DTM), generation of pan-sharpened image and its quality assessment. 50 When all accessible literature was reviewed, it was obvious that the 3D georeferencing accuracy of Pléiades 1A images and the DSM/DTM generation and validation were handled using RFM, and its private sensor-dependent orientation model was not carried out yet.…”

Section: Existing Studies and Contribution Of This Articlementioning

confidence: 99%

“…Pléiades twins (1A&1B) are being subjected for various type of research. Its post-launch geometric quality was handled by the researchers such as Bernard et al., 17 deLussy et al., 18 Delvit et al., 19 Greslou and deLussy, 13 Delvit et al., Michel et al., 20 de Franchis et al., 11 Perko et al., 21 Postelniak, 22 Poli et al., 23 Abduelmola, 24 Gim and Shin, 25 Henrico et al., 26 Dukuzemariya, 27 Kartal et al., 28 and Perko et al 29 – 31 Its height accuracy was also subjected by the studies of Durand et al., 32 Berthier et al., 33 Giraud et al., 34 Stumpf et al., 35 Eisank et al., 36 Jacobsen, 37 Nasir et al., 38 Noh and Howat, 39 Qayyum et al., 40 Ghuffar, 41 Ok et al., 42 Sadeq et al., 43 Sofia et al., 44 Mertes et al., 45 Peng et al., 46 Ok et al., 47 Piermattei et al., 48 and Loghin et al 49 .…”

Section: Introductionmentioning

confidence: 99%

Geo3o1: a tool for 3D georeferencing accuracy assessment of tri-stereo images by state-of-the-art sensor dependent orientation model

Topan

2022

J. Appl. Rem. Sens.

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.We subjected a tool for 3D georeferencing accuracy assessment of tri-stereo primary images of Pléiades 1A/1B/Neo, SPOT 6/7, and Göktürk-1, developed in the MATLAB environment considering their private sensor-dependent orientation model. Although the orientation model has been developed by the image vendors, the major contribution of Geo3o1 was the two-step adjustment process. The basic stages of estimating the 3D georeferencing accuracy were (i) estimating the direct georeferencing accuracy by raw orientation parameters, (ii) pre-adjustment of look angles using ground control points (GCPs), and (iii) bundle adjustment. In addition, the efficiency and validation of exterior orientation parameters and also the correlation among interior and exterior orientation parameters could be analyzed. Geo3o1 has the capability of handling the images in stereo or tri-stereo modes. The case study has been carried out by the Pléiades 1A panchromatic tri-stereo primary images with 50-cm geometric resolution. About 90 points were used as GCPs/ICPs in two distribution scenarios. The accuracy on ground was estimated centimeter level at GCPs whereas the accuracy was naturally coarser at ICPs at ∼ ± 1 GSD. The efficiency and validation of exterior orientation parameters and the correlations were also shown by two samples. The research was carried out over an undulating, mountainous area in Zonguldak, Türkiye.

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“…These methods showed acceptable accuracy and improved the road feature extraction from satellite images. Alrajhi et al [15] developed an automatic procedure that can orthorectify high-resolution satellite images with no GCPs and can respond to real-time geospatial data updates. Furthermore, Whiteside and Bartolo [16] investigated orthorectified images with the aid of the sensor's rational polynomial coefficients (RPCs) and GCPs using differential global positioning system (DGPS) with an accuracy of 10 cm.…”

Section: Introductionmentioning

confidence: 99%

“…Zhang et al [1] proposed a new method for integrated PCI-RPC and ArcGIS-Spline tools for orthorectification in satellite images. The integrated approach improved the RMSE accuracy from 2.94 m to 1.10 m. Henrico et al [15] developed an orthorectification process based on highquality 2 m DEM and applied two different GCP collection methods. First, field survey method with the aid of DGPS was adopted.…”

Section: Introductionmentioning

confidence: 99%

Orthorectification of WorldView‐3 Satellite Image Using Airborne Laser Scanning Data

et al. 2021

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Satellite images have been widely used to produce land use and land cover maps and to generate other thematic layers through image processing. However, images acquired by sensors onboard various satellite platforms are affected by a systematic sensor and platform-induced geometry errors, which introduce terrain distortions, especially when the sensor does not point directly at the nadir location of the sensor. To this extent, an automated processing chain of WorldView-3 image orthorectification is presented using rational polynomial coefficient (RPC) model and laser scanning data. The research is aimed at analyzing the effects of varying resolution of the digital surface model (DSM) derived from high-resolution laser scanning data, with a novel orthorectification model. The proposed method is validated on actual data in an urban environment with complex structures. This research suggests that a DSM of 0.31 m spatial resolution is optimum to achieve practical results (root-mean-square error = 0.69 m ) and decreasing the spatial resolution to 20 m leads to poor results (root-mean-square error = 7.17 ). Moreover, orthorectifying WorldView-3 images with freely available digital elevation models from Shuttle Radar Topography Mission (SRTM) (30 m) can result in an RMSE of 7.94 m without correcting the distortions in the building. This research can improve the understanding of appropriate image processing and improve the classification for feature extraction in urban areas.

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Accuracy comparison of Pléiades satellite ortho-images using GPS device based GCPs against TerraSAR-X-based GCPs

Abstract: Conducting single frame orthorectification on satellite images to create an ortho-image requires four basic components, namely an image, a geometric sensor model, elevation data (for example a digital elevation model (DEM)) and ground control points (GCPs

Cited by 4 publications

References 7 publications

Classification of 3D UAS-SfM Point Clouds in the Urban Environment

Classification of 3D UAS-SfM Point Clouds in the Urban Environment

Geo3o1: a tool for 3D georeferencing accuracy assessment of tri-stereo images by state-of-the-art sensor dependent orientation model

Orthorectification of WorldView‐3 Satellite Image Using Airborne Laser Scanning Data

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