The importance of forests with protective functions has increased in thel ast decades due to sttlement pressure and high vulnerability of society in Alpine regions. In this context, information on the spatial distribution of protective forests and monitoring its effect to prevent natural hazards becomes essential. However, indicators that describe their protective effect e.g. against avalanches and rockfall do not exist. The project ProAlp aimed to develop science-based indicators and estimation procedures for forests with protective functions for the entire alpine region. Traditionally, national forest inventories (NFIs) deliver ground data on a national grid which serve the data and information needs on a regional basis. These needs are reflected by the plot density and the statistical design that correspond to the smallest possible information unit. However, concerning natural hazard processes, a statistical plot-based approach is not sufficient. Remote sensing techniques are an indispensable supplement of information and the applicability of remote sensing and geospatial interpolation techniques must be investigated. In this study, new indicators were developed and applied in three regions using three different approaches: a statistical and two remote sensing approaches including coarse and fine scale (satellite imagery and Airborne Laserscanning (ALS)-data). Forest maps derived with remote sensing provided a basis for the investigations within this project. The harmonised indicators and their respective thresholds were first defined based on an intensive literature review and guidelines used in different Alpine countries. then, hazardous processes and damage potential were modelled accordingly by geospatial models. The intersection of forest maps with the resulting damage and hazard potential maps indicated forested areas with protective function. Finally, the protective effect within these areas was determined using classic forest parameters like gaps, tree density, age or diameter depending on the scale. The project ProAlp developed harmonized indicators and a methodology for estimation of forests with protective functions against natural hazards. this methodology included the mapping of hazard focusing on avalanche and rockfall and damage potentials for infrastructure like buildings, roads or railroads. Integration of NFI field data in remote sensing applications for up-scaling NFI point information proved to be a useful tool for the identification of protective effect on a large area. When using NFI data only (statistical approach) useful results are limited to small regions. For large areas the use of remote sensing data is preferable but also restricted. In this study only a coarse digital elevation model (DEM) was available for large areas which introduced uncertainty in the hazard modelling. Also, the upscaling of forest parameters with medium resolution data (Landsat data) resulted in lower accuracy. Higher accuracy was found for forest parameters and hazard maps derived from ALS data with the disadvantage of their high costs. Idelly, a full coverage of a high resolution digital elevation model and very high resolution data like ALS data would improve the application of the developed indicators and need to be tested in a future study. Results and maps concerning the three system parts, hazard potential, damage potential and protective effect developed within ProAlp, must not be interpreted as concrete natural hazard indication mapping or risk zone planning. The intention of ProAlp was to develop was to develop indicators and procedures to derive the area of forest with protective function and to evaluate their protective effect in a scientific context. Delivered maps and figures are examples for the capability of the developed methods.
