Remote sensing well-suited for tree species detection

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Researchers from the Department of Geographical and Historical Studies at the University of Eastern Finland, and from the Finnish Environment Institute, are collaborating in the IBC-Carbon project to develop novel remote sensing methods that can be used explore forest biodiversity and carbon sequestration.

Led by Professor of Environmental Geoinformatics Timo Kumpula and Leading Scientist Petteri Vihervaara (Finnish Environment Institute), the group has tested various remote sensing methods to detect different tree species in the Evo research area, among other places. In Evo, very high-resolution remote sensing data have been collected from an area of 83 square kilometres, which constitutes a diverse research environment that comprises conserved old forests, commercial forests and a popular camping area.

The researchers have been particularly interested in detecting the European aspen from among other tree species. The European aspen is an ecologically valuable tree species because it is associated with a rich and versatile selection of flora and fauna that maintain forest biodiversity.

Different remote sensing methods yield versatile data

To detect different tree species, the IBC-Carbon research group has conducted hyperspectral and laser scanning measurements from an aircraft, as well as multi-spectral measurements by using drones.

Unlike conventional aerial images, hyperspectral measurement yields data from hundreds of different wavelength ranges, which makes it possible to observe reflection differences between different tree species in the terrain. Laser scanning, on the other hand, enables three-dimensional measurement of objects, providing information on, for example, tree height and crown structure.

The accuracy achieved by the research group in the detection of the European aspen varied between 84% and 92% in the hyperspectral and laser scanning data; in the data collected by drones, the accuracy was 86%.

“This means that the methods used in the study are well-suited for the detection of different tree species. By combining reflection data from different wavelength ranges and laser scanning data on tree height and crown structure, we are able to perform more detailed mapping of trees,” Researcher Arto Viinikka says.

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