Exploration of Space-borne LiDAR data for supporting Sentinel-1 forest parameter retrieval

Short Description

Starting point / motivation

Forests provide a variety of functions such as being habitat for animals and plants, recreation area, source for renewable resources and offer protection and environmental functions.

The objective of preserving and improving the efficiency of forests is in the public interest and can only be guaranteed, if planning and implementation of all respective measures are based on objective and reliable information on forest resources and condition.

In general, forest can be described by properties that are stable over years (e.g. tree species) and highly dynamic properties, mainly caused by short-term events such as droughts, storm, snow damages or best infestations. To quantify these dynamic properties the temporal resolution of the available forest inventories (e.g. 6 years in Austria) is insufficient in terms of both, spatial and temporal resolution.

Since the launch of the Sentinel-1 (S1) and Sentinel-2 (S2) satellites, several studies have confirmed that approaches exploiting the high spatial and temporal resolution of S1 and S2 have great potential to provide the required dynamic forest information.

For the extraction of these forest parameters, up-to-date reference data sets are required to train algorithms and to validate the results. Until now appropriate reference data, coinciding with the acquisition date of the satellite data and covering the entire variety of the investigated forest parameters are missing.

Contents and goals

The key idea of SBL-S1-PR is to explore the potential of space-based Lidar (SBL) sensors for characterizing Alpine forests as found in Austria and to use the derived forest metrics as reference to calibrate forest canopy models based on Sentinel-1 data.

To achieve this overall goal the quantity and quality of SBL data available over Austria will be assessed against airborne laser scanning data. It is known, that sloped terrain limits the achievable accuracy of SBL derived canopy heights, because the backscatter from terrain and vegetation merge. Thus, the differentiation between these two scattering objects in the reflected waveform is challenging.


SBL-S1-PR will explore the consideration of terrain height from detailed ALS DTMs within the Lidar signal analysis (e.g. Gaussian decomposition) for retrieving 3D canopy information.

To derive area-wise canopy height maps with high temporal resolution, SBL will be used to calibrate state of-the-art machine learning models based on S1 time series data. While S1 has been shown to correlate with vegetation parameters, a key advantage of S1 data is the high temporal resolution, independent of weather.

The explanatory variables investigated will include backscatter images with different polarizations, texture measures, cross-polarization ratios, temporal aggregated parameters (e.g. seasonal), time series parameters such as slope and correlation, and interferometric coherence.

Investigations will be performed for different forest types (coniferous/deciduous) and topographic conditions for Austrian test sites for which simultaneous ALS, SBL and S1 data are available. Potential study sites are the western part of Tyrol and the Vienna Woods.

Demonstrating the feasibility of such a novel combination will promote the exploitations of the Copernicus S1 and SBL data in an operational context in a challenging environment.

Expected results

SBL-S1-PR will lead to an improved understanding of potential SBL+S1 applications and will therefore open new research sectors such as large-scale change detection of forests with respect to 3D structure and biomass.

The importance of such applications is reflected by the inclusion of forest biomass in the Global Stocktake, which is an integral part of the Paris agreement. Further applications arise from the relevance of forest structure for biodiversity. Biodiversity monitoring is set to be a priority field of action in the coming years at the national and international levels.

Project Partners


Technical University of Vienna - Department of Geodesy and Geoinformation

Contact Address

Technical University of Vienna
Department of Geodesy and Geoinformation
Univ.Prof. Dipl.Ing. Dr.techn. Norbert Pfeifer
Wiedner Hauptstraße 8-10/E120.7
1040 Vienna