Skog där många granar dödats av granbarkborre. Foto: Mikael Johansson

Geodata for Forest Damage - a project

Geodata for forest damage is a project that handles geodata and map data to help the forest owner find forest damage. So far there is, for example, a risk index map for the spruce bark beetle and a demo app to find changes via satellite images.

Problems related to forest damage have increased in recent years and this trend can be expected to continue in the coming decades due to the impacts of climate change. The Swedish Forest Agency has received funds from the government specifically to address the issue of forest damage. There is a need to create an infrastructure of data and technical support to strengthen Sweden's long-term ability to prevent, detect, monitor, counteract, and document forest damage. The development of remote analysis methods and digital data is one of several areas where the Swedish Forest Agency needs to increase its capacity during the period 2020–2024, in order to build up our ability to deal with forest damage.

Try to find Forest Damages with geodata Products

The Geodata for Forest Damage project is concerned with the use of geodata and map data. As much of the work carried out in the project is of an exploratory nature, with a focus on developing a knowledge base and experience, the milestones in the project consist of investigations, evaluative material, and proposals for development.

Selection of deliverables so far

A selection of the current project's deliverables includes a risk index map for the spruce bark beetle, manual change analysis in satellite images, a platform for training AI models, a forest fire application, as well as a map of clustered areas with dead spruce produced using an AI model.

Satellite images that indicates dead trees

There are extensive problems with the spruce bark beetle in the southern part of Sweden, and it is difficult to identify new infestations in sufficient time to save timber value and contain the spread. In order to assist landowners, the project is therefore working with training AI models that can identify changes in the best satellite images. There are still many challenges to creating a fully functioning system, but we have succeeded in creating a working demo application.

  • Last Updated: 5/13/2024