GEDI meets the Sentinels: Exploration of the Mutual Benefits from Joint Use of GEDI and Sentinel-1 / Sentinel-2 data

Short Description

Starting point / motivation

The Return of the (J)GEDI: By the end of 2019, the first data sets of the GEDI (Global Ecosystem Dynamics Investigation) space-based LiDAR system have become available. The GEDI instrument, positioned on the International Space Station (ISS), provides sampling LiDAR waveforms. GEDI produces point-wise high resolution laser ranging observations of the 3D structure of the Earth.

GEDI’s precise measurements of forest canopy height, canopy vertical structure and surface elevation are said to "greatly advance our ability to characterize important carbon and water cycling processes, biodiversity, and habitat".

This information is also important for the derivation of indicators to monitor the United Nations Sustainable Development Goals (SDGs). Previous studies suggest a great potential of these LiDAR waveform data sets, particularly when used in combination with wall-to-wall optical or SAR data.

Contents and goals

In this project, we will investigate the suitability of GEDI data in combination with Sentinel-1 (S-1) and Sentinel-2 (S-2) for various forestry applications in Austrian and Tropical forests. Once successfully implemented, this knowledge should be transferred to industrial research and application projects in the frame of Copernicus or Horizon Europe.


At the current stage of knowledge, proposing to use GEDI within such a project would be too risky. GEDI data are thematically very detailed, but only point-wise available. Therefore, the combination with less detailed, but wall-to-wall remote sensing data is promising. Previous combination attempts with Landsat and TerraSAR-X/TanDEM-X (TDX) support this assumption. To our current knowledge, the combination of GEDI with Sentinel data sets has not been done yet. To achieve this, the first step will be an analysis of the accuracy of the GEDI estimates. This will be realized by comparing GEDI canopy cover, height values, vertical structure and above ground biomass (AGB) to the output of airborne laser scanning campaigns carried out in the Tropics and in Austria. The second step will be to assess the potential of the synergetic use of Sentinel data (backscatter from S-1 and reflectance from S-2) and various GEDI L2 and L4 products (e.g. canopy cover fraction, LAI and AGBD).

Based on these findings GEDI-Sens will investigate three different possibilities of synergetic usage:

  • Assessment of the GEDI usability for automated training data sampling to be used in classification of forest properties and disturbances in European and Tropical forests.
  • Investigation of the potential of Sentinel-1 and Sentinel-2 for improving GEDI L3 and L4B gridded products.
  • Evaluation of the potential to generate new products based on the fusion of GEDI and Sentinel data, e.g. wall-to-wall vertical forest structure.

The results will be quantitative assessments of the benefits resulting from the integrated use of both systems. The investigations will take place in two different test sites where airborne laser scanner data are already or will be available in near future. The first test site is a tropical rainforest either in Suriname, where laser scanning and in-situ biomass data is available from 2016, or in Uganda, where in the frame of another project, new laser scanning data will be acquired in 2021, if the pandemic allows. The second test site is located in Austria with LiDAR data acquired in 2020.

Expected results

Although the GEDI missions’ operating time is limited, the improved reference data and models generated from the combination of GEDI and Sentinel data will continue to be used for the classification of calibrated Sentinel data. All results will be published in international open access journal articles.

Project Partners


JOANNEUM RESEARCH Forschungsgesellschaft mbH

Project partner

Universität Graz


Contact Address

JOANNEUM RESEARCH Forschungsgesellschaft mbH
Carina Sobe, MSc
Steyrergasse 17
A-8010 Graz