GIScience & Remote Sensing (Dec 2022)
An evaluation of PlanetScope images for 3D reconstruction and change detection – experimental validations with case studies
Abstract
The PlanetScope satellite constellation has over 130 Dove satellites running 24/7, which collect weekly and even daily images globally at 3–5 m resolution. It has global data coverage and high temporal resolution, which constitute the most attractive features for medium-resolution 3D reconstruction and change detection in remote sensing applications. One shortfall of the PlanetScope images is that they are often captured at very small off-nadir angles to minimize relief differences for 2D time-series image analysis, which is not intended for classic stereo 3D reconstruction due to the very small base-to-height ratios of stereo pairs. However, considering the abundant PlanetScope images, the multi-view stereo 3D reconstruction approach leveraging a large number of images may drive the possibility of achieving more accurate 3D reconstruction, and consequently, 3D change detection on a global scale. In this paper, a multi-view stereo 3D reconstruction pipeline was adopted to comprehensively evaluate the 3D potential of PlanetScope images by performing accuracy analysis for both 3D reconstruction and change detection in semi-randomly selected regions with ground truth data. Three case studies using the PlanetScope images were performed: (1) a case study on multi-view stereo 3D reconstruction, (2) a case study on 3D change detection of buildings and trees, and (3) a case study on volumetric estimation for natural disaster monitoring. Our experiments showed that the PlanetScope images provided sufficient coverage for multi-view stereo 3D reconstruction given an area of interest. It could achieve a reasonably acceptable accuracy with root-mean-square errors of 4–6 m in our test regions and detect significant 3D changes. The capability of estimating the volumetric changes was also evaluated for the recent avalanche in Chamoli, India, and the estimated volume favorably matched the results from existing studies using data with higher resolution.
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