When planning forestry operations, AI can assist in paying attention to things like risks caused by climate change, biodiversity and forest carbon storages. Photo: Finnish Forest Association and Sitowise
In the forest sector, artificial intelligence means improved forest planning and decision-making, says Sanna Härkönen, Product Business Lead at the consulting company Sitowise.
When planning forestry operations, AI can assist in paying attention to things like risks caused by climate change, biodiversity and forest carbon storages,
’According to forest experts, AI makes it easier to focus field visits on spots which are actually the most important,’ said Sanna Härkönen, Product Business Lead at the consulting company Sitowise, speaking during the forestry event Lapin metsätalouspäivät in Rovaniemi in April.
AI can also be used in education and training, sales and marketing, and in monitoring forest growth and carbon storages. The resources used to teach AI include, among others, open-access forest resource data, laser scanning and satellite images. Some of these resources are free of charge, while others are not.
Forest.fi requested Härkönen to illustrate the potential of AI, and she did this with these six images.
Image 1
Using a time series, AI shows the changes in the basal area of a stand. The image enables the estimation of felling volumes. The Finnish Forest Centre makes use of this data in, for example, law enforcement: has the forest owner complied with the notification of forest use submitted previously? Photo: Sitowise
Image 2
The image shows the health risks in the forest. The more red there is in the image, the higher the risk of damage by insects, drought or any other factor. The AI model does not specify the nature of the problem, but only shows where a visit on the ground should be made. Photo: Sitowise
Image 3
AI has detected dead trees in an aerial image; in other words, it has mapped an area of suspected forest damage. Photo: Sitowise
Image 4
The image shows the biodiversity of each forest compartment. AI can help in determining such things as the amount of decayed wood, which is an important indicator of good forest biodiversity. Photo: Sitowise
Image 5
AI generates data on changes in the forest carbon balance. The carbon balance concerns the processes in which carbon is bound by a growing forest and, conversely, removed by fellings and decay. The difference between binding and removal equals the net sink, or the carbon balance, of the forest. Photo: Sitowise
Image 6
AI indicates the areas where the forest is too dense, where saplings or young stands should be thinned. Photo: Sitowise
This website uses cookies so that we can provide you with the best user experience possible. You can change the cookie settings below.
Strictly Necessary Cookies
Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.
If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.
User count and analytics
This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.
Keeping this cookie enabled helps us to improve our website.
Please enable Strictly Necessary Cookies first so that we can save your preferences!
