Advanced coastal elevation model enhances vertical precision
News

Advanced coastal elevation model enhances vertical precision

Scientists at Deltares have developed an impressive global coastal digital terrain model (DTM) at 1 arc-second (~30m) resolution. In their work, they extensively use elevation models as input for numerical models, but they noticed that current, freely available elevation models are not accurate enough for their purposes. The experts decided to create a new elevation model – DeltaDTM – making use of the latest remote sensing data.

To model future extreme water levels due to sea-level rise, subsidence and the worsening of storm surges, high-accuracy elevation data (within 1m) for all coastal areas of the world is required. Local airborne Lidar data is sometimes used for this purpose, but is not available everywhere due to its costliness.

Usability of global elevation models

In areas where this data is missing, for instance in southeast Asia, researchers fall back on global elevation models to assess coastal flood risk, among other factors. However, these models measure the upper part of canopy and buildings as well, and thus do not represent the bare earth and height everywhere. The differences between the model and terrain can be tens of metres for vegetated areas.

The newly developed DeltaDTM is the first global coastal elevation model that has an accuracy within 1m, marking an important step in the usability of global elevation models to assess sea-level rise, for instance. Maarten Pronk, a PhD candidate at the Delft University of Technology and an elevation modelling expert at Deltares, was responsible for creating the model.

Maarten Pronk explained: “Ever since the global satellite Lidar data became available, we have made plans to improve global terrain models. Former colleagues Ronald Vernimmen and Aljosja Hooijer (now both at Data for Sustainability) and I started out with a 5km model (GLL_DTM). We have now improved upon this work, by including even more Lidar data and fusing with existing elevation models, to reach a 30m resolution. It required a thousand times more computer power, which we solved by extensively parallelizing our workflow in the Julia programming language.”

Marieke Eleveld, senior remote sensing expert and Maarten Pronk’s colleague at Deltares, stated: “DeltaDTM benefits from fusion of datasets using the strengths of fundamentally different remote sensing techniques and with the synergy from these higher-level satellite datasets we can correct for biases and remove points that are not on the ground but are from tree canopies or buildings.”

Global Lidar data

The high accuracy of DeltaDTM is achieved by combining the most recent radar-based global CopernicusDEM elevation model with satellite Lidar data, freely distributed by the NASA ICESat-2 and GEDI missions. “These missions are ongoing, so we can expect further updates and improvements to DeltaDTM in the near future,” said Maarten Pronk. DeltaDTM was already used by his Deltares colleague Panos Athanasiou for the extraction of global coastal characteristics.

“We anticipate that this global coastal lowland relief can serve as a valuable base in many other geospatial analyses,” said Marieke Eleveld, senior remote sensing expert.

All technical details and links to the DeltaDTM dataset are available in this open-access paper. This paper is part of Maarten Pronk’s PhD research in collaboration with the 3dgeoinfo research group at Delft University of Technology.

The newly developed DeltaDTM is the first global coastal elevation model that has an accuracy within 1m. (Image courtesy: Deltares)
Hydrography Newsletter

Value staying current with hydrography?

Stay on the map with our expertly curated newsletters.

We provide educational insights, industry updates, and inspiring stories from the world of hydrography to help you learn, grow, and navigate your field with confidence. Don't miss out - subscribe today and ensure you're always informed, educated, and inspired by the latest in hydrographic technology and research.

Choose your newsletter(s)