Geomorphometry Newsletter September 2011

Published: Sep 15, 2011 by ISG Board

The 4th international conference + workshops on Geomorphometry / Digital terrain modelling and analysis will be held next year in Nanjing, China. If you have not done already, put this date in your agenda: October 16-20, 2013 (Wednesday to Sunday). We expect again an exciting programme with several workshops and training sessions. This edition of Geomorphometry is kindly sponsored by the Geographical Society of China, National Natural Science Foundation of China, Key Laboratory of Virtual Geographical Environment, Ministry of Education, and Nanjing Normal University. For all other info please refer to www.geomorphometry.org/meetings/nanjing-2013/

Colleagues from ESRI are actively producing geomorphometry tools and data sets for public use. This is an example of a multiscale slope map built using the ArcGIS JavaScript API. The ESRI’s World Elevation Services is expected to become fully operational in mid 2012. It will contain image services, data download services, and analysis task services available, as well as sample applications.

Google has recently released a Google Elevation service. The Elevation service provides SRTM/bathymetry elevation data for locations on the surface of the earth, including depth locations on the ocean floor (negative values). It can be used to produce elevation paths and get elevations for any point on Earth’s surface (maximum of 2,500 requests per day).

Have you missed the Geomorphometry 2011 conference? No problem. All presentations from Geomorphometry 2011 are available via the ESRI proceedings website. All papers and attached datasets can also be accessed freely from the Geomorphometry homepage.

TanDEM-X is the new generation satellite (owned by the German Aerospace Center) that aims at producing new generation radar-based DEMs with a horizontal detail of 12 meters) and a height accuracy of better than 2 m. The data will likely not be publicly available, but the new global DEM will completely change the world of geomorphometry. http://www.dlr.de/hr/en/desktopdefault.aspx/tabid-2317

A recent geography Master’s thesis by Jason Goetz from the University of Waterloo, Canada utilizes terrain analysis tools implemented in open-source software (SAGA GIS, R) for exploring the regional controls of landslide initiation on Vancouver Island, British Columbia. A nonparametric regression technique, the generalized additive model (GAM), was used to model the relationship of topography, climate, forest harvesting activities and geology to landslide initiation, underlining the importance of the impacts of logging roads. Based on the model predictions, the most susceptible 4% of the study area had 29 times higher density of landslide initiation points than the least susceptible 73% of the study area,

newsletter

Share

Latest Posts

Whitebox Workflows Next Gen released

Whitebox Workflows Next Gen, a complete rewrite of the Whitebox geospatial analysis platform, is now publicly available for Python, R, and QGIS.

Built from the ground up in pure Rust, Whitebox Next Gen provides more than 700 geospatial analysis tools for geomorphometry, terrain analysis, spatial hydrology, LiDAR processing, remote sensing, vector GIS, and spatial statistics. All three interfaces run on the same high-performance backend, allowing users to work in scripts, notebooks, statistical workflows, or a familiar desktop GIS environment.

Whitebox Next Gen is not an incremental update to the previous Whitebox architecture. It replaces the earlier monolithic system with a modular, full-stack geospatial platform. Core capabilities for raster and vector I/O, coordinate systems and reprojection, vector topology, spatial indexing, LiDAR processing, and other foundational operations are implemented directly within the Whitebox codebase rather than delegated to external C or C++ GIS libraries. This approach provides consistent cross-platform behaviour, fewer system-level dependencies, tighter control over performance and correctness, and greater flexibility for continued research and development

Highlights

  • More than 700 tools for geomorphometry, hydrology, LiDAR, remote sensing, vector analysis, spatial statistics, and general geospatial processing
  • Publicly available interfaces for Python, R, and QGIS
  • A modular, high-performance backend written entirely in Rust, including wbprojection, wbraster, wbvector, wblidar, wbspatialstats, and wbtopology open-source (MIT/Apache licensed) backend libraries
  • Most of the 80+ tools that existed within the previous extension product have been migrated to the new Whitebox open core, including the tools for advanced surface curvature analysis and DEM processing
  • Native coordinate-reference-system handling and reprojection workflows via wbprojection
  • Expanded raster support (19 formats), including GeoTIFF, Cloud-Optimized GeoTIFF (COGs), GeoPackage Raster, and JPEG2000
  • Expanded vector support (12 formats), including Shapefile, GeoPackage, FlatGeobuf, GeoParquet, GeoJSON, TopoJSON, and GML
  • Modern point-cloud support, including LAS, LAZ, COPC, E57, and PLY
  • A dedicated topology engine supporting robust vector analysis, network analysis, route-event workflows, and linear referencing
  • Local-first processing on Windows, macOS, and Linux
  • A consistent analysis platform across Python scripts and R workflows
  • A newly updated and more advanced QGIS Processing toolbox

Whitebox has particular strengths in terrain analysis, geomorphometry, spatial hydrology, and LiDAR processing. Whitebox Next Gen carries these areas forward while substantially expanding the project’s capabilities for vector analysis, remote sensing, modern spatial data formats, and reproducible geospatial workflows.

Get started

The geomorphometry community is invited to explore Whitebox Next Gen, test its tools and workflows, report issues, and contribute to the continued development of the project.

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.