Abstract
Abstract. Airborne laser scanning (ALS) remote sensing data are now available for entire countries such as Switzerland. Methods for the estimation of forest parameters from ALS have been intensively investigated in the past years. However, the implementation of a forest mapping workflow based on available data at a regional level still remains challenging. A case study was implemented in the Canton of Valais (Switzerland). The national ALS dataset and field data of the Swiss National Forest Inventory were used to calibrate estimation models for mean and maximum height, basal area, stem density, mean diameter and stem volume. When stratification was performed based on ALS acquisition settings and geographical criteria, satisfactory prediction models were obtained for volume (R2 = 0.61 with a root mean square error of 47 %) and basal area (respectively 0.51 and 45 %) while height variables had an error lower than 19%. This case study shows that the use of nationwide ALS and field datasets for forest resources mapping is cost efficient, but additional investigations are required to handle the limitations of the input data and optimize the accuracy.
Highlights
In the past decade, many studies have demonstrated the potential of airborne laser scanning (ALS) for forest parameter mapping
418 National Forest Inventory (NFI) plots were used for model calibration of height variables, and 582 for the other variables
Existing methodology for the calibration of prediction models with airborne laser scanning was successfully implemented in the case of a wide-area mapping of forest variables
Summary
Many studies have demonstrated the potential of airborne laser scanning (ALS) for forest parameter mapping. The area-based approach combines the 3D description of vegetation by the ALS point cloud with field plot data in order to provide statistically calibrated, continuous maps of forest parameters (Naesset, 2002). This method has been tested in different forest contexts and with various acquisitions settings. Nationwide ALS acquisitions have been performed, mainly for topographic purposes, and field forest plot are routinely acquired for national or regional statistical monitoring of forest resources These data can be used in a cost-effective way as inputs for the ALS-based mapping workflow (Hollaus et al 2009, Nilsson et al 2015) but have limitations as their acquisition is not designed for this purpose. In this case-study, we used nationwide ALS data and National Forest Inventory (NFI) data to derive forest parameters maps and identify the main limitations due to the input data
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