The BioMassters

Help conservationists make use of satellite imagery to estimate the aboveground biomass of Finnish forests. #climate

$10,000 in prizes
jan 2023
976 joined

About the data

Finland is Europe’s most forested country, with 75% of its land area covered in forest. Unlike many other forested regions, two-thirds of Finnish forests are privately owned. The Finland Forest Centre’s database on these private forests is one of the world’s most extensive. Their free and open LiDAR data, provided through the Creative Commons CC BY 4.0 license, allows for the calculation of above ground biomass (AGBM), an essential measure for policy makers and researchers. This makes Finland one of the world’s best test labs for developing powerful satellite biomass algorithms.

Various stakeholders from private and public forest owners to scientists, policymakers, and corporations use Aboveground Biomass (ABGM) to better understand a forest's carbon stock and sequestration. Measuring the power of forests as carbon sinks provides incentive to consider the environmental value of forests and contribute to the global goal of halting deforestation.

After the challenge, the best biomass predictions will be used to model carbon metrics on Avoin Map to aid transparent decision making and biodiversity restoration. The challenge-winning biomass algorithm will be adjusted and scaled globally using ground truth measurements from forests around the world. The algorithm could be extended to many different types of forest biomass, from boreal to temperate, and from tropical to arid.

“I believe that we are just at the beginning of the Earth Observation big data revolution. Joint effort and open science are the fundamental bricks to build new models and services for addressing societal challenges.”

More information on satellite data

Sentinel-1 SAR

The Sentinel-1 mission uses two polar-orbiting satellites that circle the globe along opposite trajectories, one ascending across the poles, one descending. Unlike many other remote sensing missions (including Sentinel-2), Sentinel-1 conducts remote imaging using Synthetic Aperture Radar (SAR). SAR operates by emitting energy from a sensor and recording the amount of that energy that is reflected back after interacting with the Earth. This energy can be transmitted and received using either vertical or horizontal polarizations, which correspond to different bands. The figure below illustrates how radars transmit and receive polarized energy by applying specific filters.

An diagram of how SAR uses polarization

The first symbol indicates the direction of transmission and the second indicates the direction of reception. Image Credit: Remote Sensing of the Environment.

The signal strength of these different polarizations can give scientists clues about the surface of the area being sensed — for example, whether it is bare soil or water, forest canopy, or buildings, among others. For more information about different bands and surfaces, NASA Earthdata can be a useful resource.

Sentinel-2 MSI

Sentinel-2 is a European wide-swath, high-resolution, multi-spectral imaging mission. Sentinel-2 includes twin satellites flying in the same orbit but phased at 180°, which is designed to give a high revisit frequency of 5 days at the equator.

SENTINEL-2 carries an optical instrument payload that samples 13 spectral bands: four bands at 10 m, six bands at 20 m, and three bands at 60 m spatial resolution. The orbital swath width is 290 km.

For more information, refer to the Copernicus Sentinel-2 information page.

Cloud Probability Layer

The cloud probability layer (CLP band) provided in the Sentinel-2 data was generated using the Sentinel Hub Cloud Detector for Sentinel-2 images. This model is publicly available under the CC-BY-SA-4.0 license.

About our data partners

The idea to prepare this dataset was developed within the two Geomatics groups of KU Leuven University and the University of Liège in scientific collaboration with the Finnish company Avoin Map.

The main aim of this challenge is to investigate the potential of multi-modal and multi-resolution Sentinel satellite data to estimate biomass at a large scale, using data from the Finnish Forest Centre's open forest and nature data as reference data. While field measurements and airborne LiDAR techniques are effectively used to retrieve information about the forest biomass, it’s challenging and expensive to use these techniques at a large scale. The utilization of satellite data to measure biomass would dramatically reduce the cost and resources required for forest monitoring and carbon estimation. In turn, such information allows landowners and policy makers to make better decisions for the conservation of forests.

You can learn more here:

An image of the University of Liège logo          An image of KU Leuven logo