Airborne laser scanning supported identification of snow damaged trees, and the risk of cascading insect damage

Forests are being hit by various biotic and abiotic damage agents each year. When measured in terms of damaged area, snow is the single-most significant “pest” of Finnish forests, especially for pine and spruce. Coniferous trees weakened by snow damage are also known to be utilized by bark beetles such as Ips sp. and Pityogenes sp., resulting in increased local risk for cascading insect damage. To know the accurate location of snow damage is, therefore, of vital importance for forest health monitoring.

The ‘LumiLaser’ project aims to achieve this by using the new airborne laser scanning (ALS) data collected by the National Land Survey of Finland. The new data has considerably higher pulse density, which allows to detect the structural anomaly caused by snow. The assumption is that this anomaly (cut tree top, bent stem) is severe enough to be recognized from the 3D ALS point cloud data. After successful detection, the damage areas can then be mapped and the results integrated into existing web-services. The aim is that the newly collected ALS data from spring is used to detect snow damage from the preceding winter, and in a fast enough time to allow the removal of excess downed wood, which in Finland is mandated by law in order to halt the cascading insect damage. Field work section of the project will focus partly on validating the ALS-based damage sites, but especially on detailed assessment of the additional insect damage that snow damage may cause. This will include assessment on the number of species that are utilizing the damaged trees as well as measurement of their effects in the surrounding trees. The project is coordinated by Natural Resources Institute Finland. Other involved institutes are University of Eastern Finland (School of Forest Sciences) and Finnish Forest Centre.