Methods for evaluating the resolution of 3D data derived from satellite images
This work addresses the need for standardized resolution evaluation in satellite-derived 3D data, which is crucial for applications like large-scale scene modeling, but it appears incremental as it builds on existing evaluation methods.
The paper tackles the problem of measuring the resolution of 3D data from satellite images, such as point clouds and digital surface models, and presents automated evaluation tools and workflows using high-resolution airborne lidar as reference, with results analyzed on varying data quality.
3D data derived from satellite images is essential for scene modeling applications requiring large-scale coverage or involving locations not accessible by airborne lidar or cameras. Measuring the resolution of this data is important for determining mission utility and tracking improvements. In this work, we consider methods to evaluate the resolution of point clouds, digital surface models, and 3D mesh models. We describe 3D metric evaluation tools and workflows that enable automated evaluation based on high-resolution reference airborne lidar, and we present results of analyses with data of varying quality.