News from the 3D-ABC project

Discussing the 3D-ABC Foundation Model at Conferences in Austria and Italy

by Tillmann Lübker, Samy Hashim, and Guido Grosse

[May 2025] Despite still being in its foundational stage, the 3D-ABC Foundation Model has made significant progress. Accordingly, members of the 3D-ABC team started presenting and discussing first project details at international conferences and workshops. In April and May, there was the opportunity to attend the large EGU conference and an ESA-NASA workshop on Foundation Models in Earth Observation.

In late April this year, almost 19,000 earth scientists found their way to Vienna, Austria, for the annual general assembly of the European Geosciences Union (EGU). The program made clear that there is growing interest in multimodal approaches for geospatial analytics as well as in more refined estimates of global carbon stocks. On early Monday morning, the project’s lead PI provided an overview on the 3D-ABC Foundation Model in an oral session dedicated to recent advancements in the development of foundation models. Regardless of the early morning timing, the session room was packed with listeners who even lined up at the edges of the room, confirming the very high interest in Foundation Models. Throughout the week, there were various opportunities to network with other projects and to discuss approaches.

In the second week of May, 3D-ABC team members from FJZ attended and presented 3D-ABC at the ESA-NASA International Workshop on AI Foundation Models for Earth Observation at ESA in Frascati, Italy. The workshop brought together researchers from across the globe to discuss how large AI models can be applied to satellite data to address pressing Earth science challenges – from deforestation and land use change to long-term climate monitoring. The workshop was a great opportunity to connect with researchers from both academia and space agencies and to see how open collaboration is shaping the future of geospatial AI. One key takeaway was how rapidly the field is moving toward open, reusable models and datasets, which aligns well with our project goals. It was particularly motivating to engage with others working at the intersection of AI and the space industry.

With their presentations at conferences and workshops, the 3D-ABC team reaches out to the broader international science community to share their latest research and foster collaborative opportunities. Before summer ends, you can catch up with team members at the Helmholtz AI Conference in Karlsruhe (3-5 June), the Helmholtz Imaging Conference in Potsdam (25-27 June), the ESA Living Planet Symposium in Vienna, Austria (23-27 June), and the IEEE International Geoscience and Remote Sensing Symposium (IGARSS) in Brisbane, Australia (3-8 August).

See the Publications section for more information.

Introducing gediDB: A Scalable Framework for GEDI LiDAR Data Analysis

by Simon Besnard (GFZ Potsdam), Felix Dombrowski and Amelia Holcomb

[May 2025] The Global Ecosystem Dynamics Investigation (GEDI) mission provides unprecedented LiDAR measurements of forest structure globally, offering new opportunities to study forest dynamics, carbon cycling, and ecosystem change. However, working with GEDI data is challenging due to the complexity of its raw formats and the scale of data involved. GEDI provides key input data on the 3D structure of global vegetation in the 3D-ABC Foundation Model project, which aims at using multi-modal Earth Observation, elevation, and climate data in a new foundation model to capture and track the stocks and dynamics of global vegetation and soils.

As part of the 3D-ABC project within the Helmholtz Foundation Model Initiative, the gediDB (https://pypi.org/project/gedidb/) has just been openly released by GFZ Potsdam. It is a Python package that addresses these challenges by offering a scalable, high-performance solution for accessing, querying, and analysing GEDI Level 2A, 2B, 4A, and 4C products. Built on TileDB, gediDB enables efficient spatial and temporal subsetting, supports parallel processing, and integrates seamlessly with Python’s geospatial data ecosystem (e.g., xarray, geopandas). The tool offers a publicly accessible global GEDI database (Fig. 1), eliminating the need for local downloads, and complete documentation is available online at https://gedidb.readthedocs.io.

Within 3D-ABC, gediDB plays a key role in building scalable software infrastructure for rapidly extracting large subsets of GEDI data for tasks such as analysing biomass and canopy cover dynamics, retrieving vertical canopy structure metrics (e.g., RH₅₀, RH₉₈), and performing spatiotemporal aggregation. By providing efficient access to global GEDI LiDAR data, gediDB facilitates ingesting vertical structure information into geospatial foundation models aimed at quantifying terrestrial carbon stocks. Fig. 2 illustrates how these capabilities enable regional-scale assessments of forest change and structure–biomass relationships.