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Abstract
Accurate elevation data, which can be extracted from very high-resolution (VHR) satellite images, are vital for many engineering and land planning applications. In this way, the main goal of this work is to evaluate the capabilities of VHR Deimos-2 panchromatic stereo pairs to obtain digital surface models (DSM) over different land covers (bare soil, urban and agricultural greenhouse areas). As a step prior to extracting the DSM, different orientation models based on refined rational polynomial coefficients (RPC) and a variable number of very accurate ground control points (GCPs) were tested. The best sensor orientation model for Deimos-2 L1B satellite images was the RPC model refined by a first-order polynomial adjustment (RPC1) supported on 12 accurate and evenly spatially distributed GCPs. Regarding the Deimos-2 based DSM, its completeness and vertical accuracy were compared with those obtained from a WorldView-2 panchromatic stereo pair by using exactly the same methodology and semiglobal matching (SGM) algorithm. The Deimos-2 showed worse completeness values (about 6% worse) and vertical accuracy results (RMSEZ 42.4% worse) than those computed from WorldView-2 imagery over the three land covers tested, although only urban areas yielded statistically significant differences (p < 0.05).
Highlights
The new generation of very high-resolution (VHR) commercial satellites with ground sample distance (GSD) lower than 1 m started in September 1999 with the launching of the IKONOS-2 satellite.Nowadays, an increasing number of VHR optical satellites with stereo image capabilities are commercially available
After the sensor orientations for Deimos-2, following the best operational approach provided by the results described in Section 5.1, and after the WV2 stereo pairs were carried out, three grid spacing format digital surface models (DSM) for each subarea were extracted
This paper is focused on the capabilities of Deimos-2 PAN level 1B (L1B) stereo pairs (1 m GSD) to extract high quality DSMs over different land covers
Summary
The new generation of very high-resolution (VHR) commercial satellites with ground sample distance (GSD) lower than 1 m started in September 1999 with the launching of the IKONOS-2 satellite.Nowadays, an increasing number of VHR optical satellites with stereo (or triplet) image capabilities are commercially available. (from 2018, 0.9 m GSD) and SuperView1A/1B (from 2018, 0.5 m GSD) Most of these VHR sensors have already been studied over the last 20 years [1,2,3,4,5,6,7,8,9,10,11], with orthoimages and digital surface models (DSM) being the flagship georeferenced products derived from them. Both products need a sensor orientation phase ( known as the triangulation process) as a previous and crucial step. Regarding this sensor orientation phase, a zero-order (rational polynomial coefficient (RPC0)) polynomial transformation is usually the best option when using the triangulation method developed by Grodecki and Dial [12] based on 3D rational functions with vendor image support data (i.e., rational polynomial coefficients (RPC)) refined by a polynomial transformation in the image space
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