NEW OPPORTUNITIES FOR MAPPING CARBON CAPTURED IN FORESTS WITH SATELLITE DATA
Forest owner can now get a real-time report on carbon captured in biomass
Local level actors such as cities and municipalities have been defining carbon sinks of the forests on their area as a part of their carbon neutrality objectives already for years. This requires the ability to verify sinks and ensure the permanence of carbon storages, which, in its part, requires exact, versatile, and up-to-date information on forest growth and cover.
Many of the cities use forest systems in their work. Therefore, it is a clear continuum that the future needs also regarding carbon balance calculation are considered in system design. When combined with a forest planning software such as Foresta by Bitcomp, the method offers helpful tools not only for environmental politics but also for making decisions during forest planning.
Balance, storage, sink or a source?
The calculations depicting carbon sequestration have caused confusion with both the terminology and the vast dispersion of the results. The predictions by different parties on how much wood can be cut in Finland without endangering the carbon sink effect can vary significantly. The difference in results can be partly explained with calculation models that differ slightly from each other. Additionally, even when discussing basically the same topic, slightly differing terms are used. Let’s take a quick glance at the topic:
Carbon storage: Forest carbon storage consists of the carbon storages of tree cover (biomass), vegetation, and forestland. Somewhat established and reliable models exist for counting carbon storage, which depicts the status of a forest right now. Wood-based products can also be carbon storages.
Carbon sink: Carbon sink is a growing carbon storage that consists of the carbon storages of tree cover (biomass) and forestland.
Carbon source: Carbon source is a waning carbon storage. The carbon captured in forest and soil due to a cutting, soil processing, dead tree cover, or forest damage is released back to the atmosphere.
Carbon balance: Carbon balance means the balance between the carbon captured in (sinks) and released from (sources) the ecosystem, as well as the change in carbon storage in a unit of time, for example as t/ha/a. Carbon balance considers tree cover growth, total loss, as well as the carbon captured in and released from wood and soil.
In all the models, the carbon amount calculation is based on soil carbon, wood products carbon, and the carbon in living biomass. The biomass calculation is affected by the main tree species, the height and the amount of tree cover, as well as by how covered in vegetation the area is.
The predictability of carbon storages is a significant factor in calculating the carbon balance. So that carbon balance could help in forestry decision-making, it is necessary that the development of carbon balance can be monitored and estimated for decades to come.
Satellite data talks about biomass now
What then causes the dispersion in results? Mainly it is due to that the growth estimations on tree cover development and forest carbon sinks differ significantly from each other in different models. The challenges of predictability are especially related to climate change. The change scenarios of growth conditions are related to for example precipitation, nitrogen deposit, nutrients, and temperature. The exact impacts of climate change on forest carbon sequestration remain beyond our ability to define them. In one hand, global warming can accelerate and enhance forest growth, increasing the amount of carbon captured in biomass. In the other, with the global warming more disturbances affecting forests are expected. These can include nutrient impoverishment, new pests, and a significant increase in forest fires, dissolution on forestland, and forest damages. All of these release carbon dioxide from detritus and soil more than is currently released.
Even without the uncertainties brought by climate change, the first issue with growth estimations is simply the timeliness of the initial data. In her blog text Tarja Tuomainen relates that the carbon balance calculation of Finnish tree cover biomass is based on the National Forest Inventory (NFI) data, inventory interval of which is currently 5 years. In the report by climate panel both NFI10 and NFI11 data was used. The field work for NFI11 data was done through years 2009–2013. When calculating the growth of biomass, recent years become an issue. Even though the publicly available biomass maps based on NFI data (by the Natural Resources Institute Finland) are updated every couple of years, by the time of update the data is no longer current but rather based on the situation several years ago. The same issue is also known in Sweden and Norway, where the carbon balance calculation of forestland tree cover is based on a sampling based national forest inventory. (For Tarja Tuomainen’s blog text in Finnish, see here.)
So, in case the initial data is faulty or outdated, the results produced by models take a wrong turn already early on. Luckily, this issue can be addressed with satellite data without massive extra work. With satellite data, the timeliness of forest information used for carbon balance calculation can be enhanced. At the same time, information on land use changes such as cuttings or other deforestation can be gained. Satellite monitoring does not aim to replace other mapping methods but rather advance the availability of as up-to-date forest resources information as possible. When the current state of carbon storages and thus carbon balance can be estimated on certainly correct initial data, for example cities’ forest experts can reliably report the true amount of carbon captured in their forest areas.
Can satellites be used to improve growth estimations?
The size of carbon storages can be presented for example by stands in theme maps.
As stated in the beginning of this text as well, the ability of forests to capture carbon is a big part of cities’ carbon neutrality objectives. Reaching of these goals require reliable estimations on forest growth and on with what kind of carbon storages the objectives can be achieved.
Climate change affects different areas in different ways, so it is impossible to create a 100% reliable growth estimation. Already for this reason, including satellite data in the means used can be seen important. By comparing images taken at different times, artificial intelligence connected to satellite data can deduce what kind of changes will occur in the biomass volume.
When the user has up-to-date information on carbon storages and the current amount of biomass of forest, they can examine and, if necessary, correct the estimation for example annually. The EnviNavigator artificial intelligence developed by Bitcomp was created exactly for this type of cases. Thanks to machine learning, the accuracy of calculation can be developed over time as the amount of information increases.
Real-time carbon reporting already available for forest systems
Satellite data and artificial intelligence as part of forest management are not future fantasies but very much a thing of the present. Within the EnviNavigator project, Bitcomp is currently developing satellite data and artificial intelligence based analyses for predicting the risks of climate change and for observing its impacts. Thanks to the new satellite surveying system, carbon balance can be presented as digital maps with 10 m resolution. Information can then be utilized for example to plan forest use, to optimize carbon capturing, and to estimate climate impacts.
Both the public and private sector have put resources on developing carbon calculation, and the development will be fast in the coming years. Bitcomp will continue to do its part to develop the carbon balance calculation into a more reliable direction. Naturally, it is best to do so in the fields where we are the strongest: in utilizing satellite data and artificial intelligence as well as in software development. Thus, we can provide forest professionals an access to better initial data and to a self-learning analysis. At the same time, we want to be able to serve the diverse values of forest owners. In addition to economic values, biodiversity as well as carbon balance calculation and optimization can be can be considered in a modern forest system.
The users of the forest system Foresta will have carbon reports of forest resources in their use already this year. In the future, system user will be able to use calculation service to estimate the impacts forest management in practice has on forest carbon balances and, if they so wish, to test optimal forest management options for carbon sinks. Thanks to the up-to-date information available, different users will also be able to examine how well they have achieved their carbon capturing objectives and how well the growth estimations have come to pass.
Bitcomp is developing carbon reporting as a part of the EnviNavigator project co-funded by the European Space Agency ESA’s funding program. The objective of the project is to develop analysis services to detect changes in the state of environment from satellite data with artificial intelligence and machine learning.
