More about Forest Remote Sensing

Last changed: 25 August 2024
Point cloud of a pine forest. Image.

In our research group, we develop and validate remote sensing methods for use in forest management planning and terrestrial environmental analysis and assessment.

We are a group of 25 people working with research and development of remote sensing of forest and other terrestrial vegetation. Our primary sensors include lidar, electro-optical sensors (including digital cameras), and imaging radar. Traditionally, the sensors platforms have been satellites, aircraft, or drones. Increasingly, we also use sensors positioned on the ground or mounted on vehicles to capture side-view images of trees. Remote sensing methods can provide detailed geographical data for forest planning, ranging from measurements of individual trees and stand variation to national-scale assessments. The collected information on vegetation is also valuable for nature conservation and ecological research.

A common approach involves processing remote sensing data with various image analysis methods, followed by estimating vegetation type and quantity using reference data from filed surveys. Information on changes over time is obtained by analysing data from multiple time points. Methods that combine projections of existing data with new sensor data are expected to gain increased significance.

We also carry out assignments at request of government agencies and organizations. Examples of assignments are needs-oriented specific mapping, environmental monitoring with remote sensing. The subject area also maintains expertise in geographic information systems (GIS).