FABDEM

A 30 m global map of elevation with forests and buildings removed

Introduction Introducing FABDEM: a new complete map of the Earth’s terrain that is shown to be more accurate than existing global elevation datasets.

Product key features

01

Resolution

Terrain data available at 30m resolution.

02

Data

Based on the Copernicus-GLO 30 DEM.

03

Algorithms

Uses machine learning to efficiently remove all forests and buildings from the earth’s surface.

04

Partners

Developed in partnership with the University of Bristol.

05

Licences

Available under a commercial licence or free for non-commercial use.

06

Training

FABDEM has been trained on a unique set of reference elevation data from 12 countries, covering a wide range of climate zones and urban extents.

FABDEM About the data

FABDEM (Forest And Buildings removed Copernicus DEM) is the first global digital elevation model (DEM) with forests and buildings removed at a 30-meter resolution. The data uses a correction algorithm to remove biases within the Copernicus GLO 30 Digital Surface Model (DSM) arising from the presence of objects on the earth’s surface. This has resulted in an improved dataset where users can model natural hazards globally with more detail than ever before. Built in tandem with the University of Bristol,  the data is available at 1 arc-second grid spacing (approximately 30m at the equator) across the globe.

This data is ideal for professionals needing to understand flood risk on a global scale or in data-scarce regions of the world. Having undertaken extensive validation, published in Environmental Research Letters, the data was shown to be more accurate than other available global DEMs. Not only this, but the finer spatial resolution in comparison to some other global DEMs allows smaller topographic features to be represented, such as narrow flow paths which enable users to better represent flow dynamics within narrow valleys.

Commercial licence

For users planning on accessing, reproducing or reselling this data for commercial advantage, business use or monetary gain.

Non-commercial licence

For users intending to use this data for research purposes. Researchers must credit the University of Bristol and Fathom, where data is shown.

Digital elevation models Do you need a Digital Surface Model (DSM) or a Digital Terrain Model (DTM)?

A Digital Elevation Model (DEM) is typically a raster GIS layer comprising of grids with values describing elevation above a given datum (typically mean sea level). 

Elevations contained within DEMs represent a variety of features. The main two are: Digital Surface Models (DSMs) and Digital Terrain Models (DTMs).

DSMs represent not only the Earth’s terrain, but all objects upon it. This includes features like trees and buildings, which when modelling a peril like flooding can drastically alter the elevation and distort simulated flood severity.

For professionals looking to model natural hazards, elevation values instead must represent the Earth’s terrain surface with surface features removed. 

Traditionally, global DEMs have contained surface objects such as forests and buildings due to the complexity of removing bias at such a large scale. Some existing DEMs, such as MERIT, have some features removed but not others (e.g. MERIT removes forests but not buildings).

However, with advancements in instrumental accuracy in tandem with the application of machine learning techniques, we are now able to develop true global bare-earth DEMs, or DTMs.

Now, scientists from the University of Bristol and Fathom have released FABDEM – a 30-meter resolution global digital terrain model, removing forest and building artefacts.

FABDEM compared against MERTI DEM and locally sourced LiDAR. St Louis, Missouri.
FABDEM compared against MERIT DEM and locally sourced LiDAR. St Louis, Missouri.
FABDEM compared against MERTI DEM and locally sourced LiDAR. Rockhampton, Australia.
FABDEM compared against MERIT DEM and locally sourced LiDAR. Rockhampton, Australia.
FABDEM compared against MERTI DEM and locally sourced LiDAR. Kansas City, Missouri.
FABDEM compared against MERIT DEM and locally sourced LiDAR. Kansas City, Missouri.
FABDEM compared against MERTI DEM and locally sourced LiDAR. Houston, Texas.
FABDEM compared against MERIT DEM and locally sourced LiDAR. Houston, Texas.

Developing FABDEM

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