The forest contains a lot of natural variation, and with new digital technology we can capture all the richness of detail that we previously could only get by physically being there. This high-resolution data includes collection by laser scanning from the air and the ground. It can then be supplemented with reference data from the ground, for example harvester data on each felled tree.
Mistra Digital Forest’s work package Forest Facts develops methods for transforming all this data into valuable information. Information that gives us the right conditions for managing and using the forest resource efficiently and sustainably.
The Forest Facts work package focuses on six divisions:
Estimation of tree species and tree growth for large areas
Satellite images and laser scanning, together with reference measurements in the field, provide the conditions for solving the holy grail of forestry: to get reliable information about volume and growth per tree species. The door to gaining detailed knowledge, even about large forest areas has been opened.
Measurement of individual trees and terrain conditions using laser scanning from the air and the ground
High-resolution laser scanning from the ground provides information about the tree trunks while from the air it reveals the size and shape of the tree crowns. In this project, the researchers combine the information, so that we get a good picture of the timber properties. The benefits? That time-consuming manual measurements are automated, and forest planning becomes more accurate.
Use of harvester data for data capture
The harvester data allows increased resource efficiency and innovative ways of doing business. Based on it, we can understand where specific tree species thrive best, and where the trees with the “right” dimensions for the customer are located. Accurately positioned harvester data can also be valuable reference data for remote sensing. This project explores how we get there, and what challenges there are along the way.
Indicators of biodiversity based on laser data
One hot topic is how we protect and develop biodiversity whilst carrying out active forestry. In this project, researchers use remote sensing with laser data – which provides a detailed picture of soil and vegetation at landscape level – and examining this data can help to evaluate biodiversity. This knowledge can be used in forest planning, for example it is possible to see what effects different measures in forestry have on biodiversity.
Strategic and tactical planning with high-resolution data
Good decision-support for forestry planning lays the foundation for large-scale, sustainable forestry. In this project, the planning system of tomorrow takes shape – and thanks to new digital technology, the modelling of different planning outcomes can be made comprehensive. This is information that contributes to resource efficiency, whilst also taking into account important natural values.
Methods for managing increased risks in a changing climate
One urgent issue is how we handle insect infestations and storm damage, in the wake of climate change. It affects resource efficiency in forestry and is something needing consideration when making strategic decisions. In this project, methods are being developed to add climate perspectives into forestry planning, by using risk assessment models that include the perspective of time. This results in an important tool for managing the risks and uncertainties that the forest of the future will face.
Estimation of stem attributes with multi-phase laser scanning
The project aims to estimate tree stem properties of individual trees over large areas, in order to improve the industrial value chain. This is done using a combination of data sources with different levels of detail: (1) ground-based laser scanning of sample plots, (2) laser scanning of trees from helicopters with > 500 measurements / m2 in sample flight strips, and (3) laser scanning from an aeroplane for the entire test site at Laxsjö (50 000 ha). In this way, it will be possible to use the sample flight strips, instead of traditional field samples, as reference for remote sensing estimations of the entire test site.