In a significant stride towards enhancing digital terrain modeling, researchers have successfully combined data from two advanced satellite missions to create high-resolution digital terrain models (DTMs) that could rival and even surpass existing global digital elevation models (DEMs). This breakthrough, led by Petra Pracná from the Department of Spatial Sciences at the Czech University of Life Sciences Prague, opens new avenues for precision agriculture, forestry, and energy sector applications.
The study, published in *Science of Remote Sensing* (translated to *Vědy dálkového průzkumu*), leverages observations from the Ice, Cloud and Elevation Satellite-2 (ICESat-2) and the Global Ecosystems Dynamics Investigation (GEDI) to generate gridded DTMs. The research team compared the accuracy of these two data sources under various conditions, including terrain slope, land cover, beam strength, and day/night cycles. The findings revealed that ICESat-2 data consistently outperformed GEDI footprints in terms of terrain elevation accuracy.
“ICESat-2 data consistently outperformed GEDI footprints in terms of terrain elevation accuracy across a range of conditions,” Pracná noted. This superior performance is a game-changer for industries that rely on precise terrain data, such as wind energy and solar power, where accurate elevation models are crucial for site selection and infrastructure planning.
The study also assessed the sampling intensity with respect to observation accuracy and grid resolution, finding that combining ICESat-2 and GEDI data significantly boosted sampling intensity. Over 60% of cells contained at least one observation, enabling the interpolation of DTMs at a 90-meter resolution. These spaceborne lidar DTMs achieved root mean square errors (RMSEs) between 9.9 and 14.7 meters, comparable to the Copernicus GLO-90 DEM (9.9–15.6 meters).
However, the local accuracy of the interpolated DTMs depended on both the number of input observations and their accuracy. Where at least 4–6 observations per 90-meter cell with vertical accuracy better than 5 meters were available, the spaceborne lidar DTMs outperformed the Copernicus DEM. In forests, the RMSE was 3.7 meters compared to 11.2 meters for the Copernicus DEM, and in non-forested areas, it was 2.6 meters compared to 3.1 meters.
This research demonstrates that spaceborne lidar-derived DTMs could replace global DEMs, offering higher accuracy and more detailed terrain information. For the energy sector, this means more precise site assessments, better infrastructure planning, and improved operational efficiency. As Petra Pracná explains, “The local accuracy of the interpolated DTMs depended on both the number of input observations and their accuracy. Where at least 4–6 observations per a 90-meter cell with vertical accuracy better than 5 meters were available, spaceborne lidar DTMs outperformed the Copernicus DEM.”
The implications for the energy sector are profound. Accurate terrain models are essential for wind farm site selection, solar panel placement, and transmission line routing. High-resolution DTMs can help energy companies identify optimal sites, reduce construction costs, and minimize environmental impact. Moreover, precise elevation data can improve the accuracy of energy yield predictions, enhancing the overall feasibility and profitability of renewable energy projects.
As the energy sector continues to evolve, the demand for high-resolution, accurate terrain data will only grow. This research paves the way for future developments in remote sensing technology, offering a more precise and reliable tool for terrain modeling. With the continued advancement of spaceborne lidar technology, we can expect even more accurate and detailed DTMs in the future, further revolutionizing the energy sector and other industries that rely on precise terrain information.