Report from Geomorphometry 2009

Published: Nov 1, 2009 by Bob MacMillan

FYI: a short report from Geomorphometry 2009 by Bob MacMillan (ISRIC) published in the Pedometron newsletter #28:

“The main purpose of my participation was to keep informed about other efforts, similar to GlobalSoilMap.net, that have a interest in processing digital elevation data and other digital data sets globally or at least for extremely large areas. This conference actually contained a large number of presentations of direct relevance for the GlobalSoilMap.net project. Perhaps first and foremost were the descriptions of efforts being undertaken in Australia (Gallant and Read) and Europe (Köthe and Bock) to process SRTM DEM data at 30 m (Australia) and 90 m (Europe) grid resolution to reduce artefacts and produce a filtered and cleaned DEM that is more suitable for use to produce inputs for the GlobalSoilMap.net project. Both of these presentations highlighted the significant advantages that can be realised by applying a series of filtering and conditioning routines to the original raw SRTM DEM data. It is obvious that similar procedures would prove equally useful if applied to SRTM DEM data sets for other parts of the world under the jurisdiction of other GlobalSoilMap.net nodes. Gallant has offered to help with efforts in other Nodes if asked.

Also of great interest were several projects that demonstrated that it is indeed possible to process and produce digital output for global scale digital data sets, including global scale SRTM DEM data sets. Reuter and Nelson presented a description of WorldTerrain, a contribution of the Global Geomorphometric Atlas. Peter Guth described processing of global scale SRTM data to identify and classify organized linear landforms (dunes). Peter also provided examples of multiple scale analysis and illustrated what you get to “see” from DEMs of 1 m, 100 m and 2 km grid resolution. Guth intends to publish the many different grids of DEM derivatives he produced for his project and make these processed data available for free and widespread use by others. Marcello Gorini described a physiographic classification of the ocean flood using a multi-resolution geomorphometric approach.

Several authors presented methods that may prove of interest to the GlobalSoilMap.net project. Gallant and Hutchinson described a differential equation for computing specific catchment area that could be applied to produce an improved terrain covariate for use in the GlobalSoilMap.net project. Similarly, Peckham, gave a new algorithm for creating DEMs with smooth elevation profiles that could be used to condition rough SRTM or GDEM data sets to smooth out noise and produce more hydrologically plausible surfaces. This algorithm was of particular interest to the GlobalSoilMap.net project because it appeared to be able to introduce hydrologically and geomorphologically relevant detail into 90 m SRTM DEMs of relatively low spatial detail.

Romstad and Etzelmuller described a new approach for segmenting hillslopes into landform elements by applying a watershed algorithm to a surface defined by the total curvature at a point instead of the raw elevation value. The resulting watersheds were bounded by lines of maximum curvature, effectively structuring each hillslope into components partitioned by lines of maximum local curvature. This is harder to explain than to understand when illustrated but it is remarkably simple to implement and may provide a new way of automatically segmenting hillslopes in a simple and efficient fashion.

Metz and others presented an algorithm for fast and efficient processing of massive DEMs to extract drainage networks and flow paths. This is of considerable interest and relevance to the GlobalSoilMap.net project because of the project’s need to process SRTM data globally to compute hydrological flow networks and various indices that are computed based on flow networks (e.g. elevation above channel, distance from divide). This algorithm can process data sets of hundreds of millions of cells (11,424 rows by 13,691 cols) in a few minutes instead of a few days (or not at all for some algorithms that fail on data sets this large).

Overall, this was an excellent conference, dominated by leading edge research in the area of geomorphic processing of digital elevation data that is of direct relevance and interest to the GlobalSoilMap.net project. We have much to learn from these researchers and much to benefit from maintaining contacts and working relationships with them.”

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DEMIX reveals which DEMs perform best

First round of the DEMIX exercise published final report

Global digital elevation models (DEMs) have become routine operational inputs across mapping, environmental monitoring, modelling and Earth-observation workflows. Their broad coverage and global availability have made them data that many practitioners simply take for granted. But knowledge of the terrain and topography of Earth’s surface is fundamental for monitoring and understanding terrestrial ecosystems and the planet’s habitability. For that reason, the CEOS Working Group on Calibration and Validation (WGCV) maintains a subgroup dedicated to digital topography and the quality of DEMs, the ‘Terrain Mapping Sub-Group (TMSG).

DEMs are representations of elevation in the form of a georectified grid, at global scale commonly derived from space-based interferometric synthetic aperture radar (InSAR) or stereoscopic optical observations, while regionally and locally airborne Laser induced detection and ranging (LIDAR) has become the primary source. DEMs can be classified as digital surface models (DSMs) when depicting the lower surface of the atmosphere or digital terrain models (DTMs) when depicting the top of the lithosphere (the Earth’s crust).

A wide variety of DEM products exist – each having different characteristics which suit different applications. It can be challenging to understand which of the available DEM products are fit for purpose for certain applications or regions. That is the practical gap addressed by the Digital Elevation Model Intercomparison Exercise (DEMIX) undertaken by TMSG. By exposing where widely used global DEMs agree, where they differ and how those differences affect rankings, the exercise delivered evidence to users for selecting a DEM rather than defaulting to one by habit.

DEM products were compared through a ‘wine contest,’ which identified requirements of openness, reproducibility, adaptability, and statistical rigour. The characteristics, evaluations, and ranking for each DEM were collected in a GIS database with over 50,000 entries. A quantitative assessment was carried out for each global DEM based on pixel-by-pixel differences of geomorphometric parameters against finer spatial resolution (1-5 m resolution) reference DEMs.

The study incorporates an unprecedented amount of high quality reference data covering a broad range of landforms and surface types, comparing their characteristics without resampling or interpolation. Users are invited to consult the results of DEMIX in order to make informed choices when needing to use a DEM, or in some cases a combination of the most relevant DEMs for their applications.

The final rankings of the wine contest, presented below, compared the six DEMs based on land cover (forest, urban, or barren), slope (cliff, steep, gentle, or flat), differences in elevation, slope and roughness, and statistical metrics.

Led by the European Commission’s Joint Research Centre (JRC), the CEOS Working Group on Calibration and Validation (WGCV) Terrain Mapping Subgroup (TMSG) established DEMIX in partnership with the International Society for Geomorphometry. Several members of the International Society of the Geomorphometry contributed significantly and we hosted various secssions at our latest conference. The exercise was performed over a three-year period starting in 2020, with community-wide calls for participation and an assembly of experts producing a number of peer-reviewed publications, culminating with a JRC reference report published in July 2026.

The objective of DEMIX was to propose a procedure to rank the available free and open global DEMs, taking into consideration user needs while promoting the implementation of FAIR (Findable, Accessible, Interoperable and Reusable) principles. The exercise compared DEMs based on criteria for land cover and terrain slope categories, representative testing, and a statistically sound ranking approach. The report outputs tailored recommendations regarding available DEM products that are not limited to one domain, geographic area, or landscape type, with flexibility for different user needs and applications.

A major challenge in the comparison of the global DEMs were the varying formats, data, and metadata contents. The adoption of a common set of standards would enhance the quality and interoperability of global DEMs and streamline the exchange and utilisation of DEM data for both providers and users. DEMIX makes the following recommendations for data providers:

● Adopt a standardised grid layout, with complete grid definitions and encodings following ISO/OGC rules.

● Include vertical datum information as part of raster DEM files.

● Clearly indicate the product version in the file names.

● Participate in future DEMIX rounds, which serve as a neutral platform for independently evaluating products before their release.

● Provide high quality, finer resolution, accurate, and multi-temporal elevation data to be used as a reference alongside DEM products.

Global DEMs are indispensable operational geospatial datasets, but they should not be treated as error-free or interchangeable. DEMIX delivered to the global community a systematic and transparent method to help choose elevation products more intelligently and help define what better elevation measurements should look like in the future.

Further Reading:

Read more in the DEMIX Final Report, or see other DEMIX publications below - mainly by our ISG members:

  • Benchmarking Elevation Plus Land Surface Parameters Finds FathomDEM and Copernicus DEM Win as Best Global DEMs (2025) and subsequent discussion (2026a, 2026b)
  • Ranking of 10 Global One-Arc-Second DEMs Reveals Limitations in Terrain Morphology Representation 2025
  • Novel Approach for Ranking DEMs: Copernicus DEM Improves One Arc Second Open Global Topography (2024)
  • Digital Elevation Models: Terminology and Definitions (2021)
  • The Digital Elevation Model Intercomparison eXperiment DEMIX, a community-based approach at global DEM benchmarking (2021)

Coffee Talk - GeoNadir

Building the world’s largest repository of FAIR drone mapping data

Paul Mead GeoNadir

September 2nd, 2026
11:30 (UTC)

Bio: Paul Mead is Co-founder and Head of Business & Strategy at GeoNadir, a platform building the world’s largest repository of FAIR drone mapping data to support environmental decision-making. A non-technical co-founder, Paul focuses on strategy, commercial development, and building high-performing teams — a discipline shaped by 11 years in the New Zealand Army, including leading a bomb disposal team in Lebanon and service in Afghanistan and the Asia-Pacific region. Since 2013 he has built and led several small businesses and start-ups, with drones as a central technology since 2016. Alongside GeoNadir, Paul co-founded She Maps, an internationally recognised drone and geospatial STEM education organisation, and has helped raise over $7M in equity and non-equity funding across his ventures. He holds a Master of Philosophy from the University of Queensland and is a Chartered Manager.

Abstract: GeoNadir set out to build the world’s largest repository of FAIR drone mapping data, and ended up building something more powerful. Drones have democratised data capture, but the same democratised ability to generate decision-grade insights from the data is lacking. I’ll walk through how we’re closing that gap: the data infrastructure behind hosting large volumes of UAV imagery and derived products, and how we’re moving from manual analysis toward automated, repeatable geospatial analytics.

Coffee Talk - Geomorphometry with GRASS

Geomorphometry with GRASS

Dr. Corey T. White Center for Geospatial Analytics at NCSU, USA

April 1st, 2026
14:00 (UTC)

Recording available in our YouTube channel

Bio: Corey White is a geospatial research software engineer with the Center for Geospatial Analytics at North Carolina State University and a maintainer of the open-source GRASS project. He is also the founder of OpenPlains Inc., an open-source web-based platform for interactive geospatial modeling. His work sits at the intersection of geomorphometry, environmental modeling, UAS mapping, and open-source software development, with a focus on making interactive terrain analysis accessible and reproducible. He has applied GRASS to problems ranging from post-disaster topographic change detection following Hurricane Helene to designing a participatory geospatial modeling platform to address ‘wicked’ socio-environmental problems. Corey is an active member of the OSGeo community and an advocate for open geospatial science.

Abstract: GRASS is a modern, actively developed, and extensible geospatial processing engine for geomorphometry. This session draws on post-Hurricane Helene landscape change analysis and ongoing addon development for DEM data fusion, terrain uncertainty modeling, and overland flow simulation to showcase what GRASS does well and where it fits in contemporary geomorphometric practice. Beyond its core analytical capabilities, GRASS’s Python, R, and Jupyter integration make it straightforward to build reproducible, scriptable terrain workflows that move easily from exploration to publication. Join this informal discussion to explore how GRASS serves not only as a research tool but as a community platform where geomorphometric methods can be developed, shared, and reused through its open addon ecosystem.