Estimating the conservation value of boreal forests using airborne laser scanning. (March 2023)

• Record Type: Journal Article
• Authors: Huo, Langning; Strengbom, Joachim; Lundmark, Tomas; Westerfelt, Per; Lindberg, Eva
• Is Part Of: Ecological indicators. Volume 147(2023)
• Publication Date: 2023-03
• Subjects: Conservation value -- Biodiversity potential -- Remote sensing -- Airborne laser scanning -- Deadwood -- Connectivity; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2023.109946
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Airborne laser scanning data (ALS) helped assess forest conservation value. ALS-detected deadwood can indicate forest conservation value. Trees considered particularly important for conserving biodiversity can be detected. Wall-to-wall maps of forest conservation value can be generated using ALS. Abstract: In sustainable forest resource management, establishing forest conservation areas is important to maintain forest biodiversity. However, assessing the conservation value of forests is challenging because the target areas are often both large and remote. We explored using dense airborne laser scanning (ALS) data to estimate conservation values. Field data were collected at sites in Sweden for standing deadwood (S trees), laying deadwood (L trees), and trees considered particularly important for conserving biodiversity (N trees), and forest conservation values were determined using a commonly employed method in the field. A template matching method was then used to detect L, S and N trees from ALS data. L trees were identified from linear features in the point cloud above the ground, with a 52 % detection error rate. S and N trees were identified from unusually small or large crown diameters, with 71 % and 83 % error rates, respectively. We also tested the relationships between the three types of indicator tree, their summed values and the field inventory-assessed conservation values. Regressions between the assessed conservation values and ALS indicators were most robust comparing the three test sites when using the summed number of L, S, and N trees. A wall-to-wall map covering a 3 km × 4 km area was generated using Kernel density estimation of the summed number of ALS-derived indicators, to represent relative conservation values. The map was validated using 10 1-ha plots, and yielded an R 2 value of 0.6 for predicted conservation values at the plot level. We conclude that ALS data can be used to map forest conservation values and inform decisions about which forests should be used for timber production and which should be set aside as conservation areas. The maps could also be used as a data source for habitat analysis.