Ice storms are common disturbance agents in temperate forests, often causing complex damage by partially destroying tree crowns. These irregular damage patterns pose challenges in production forests. Post-disturbance management decisions, such as salvage logging, are typically based on hastily collected field data, which is costly, time-consuming, and often fails to capture damage heterogeneity. Remote sensing offers a practical alternative. In 2014, a severe ice storm damaged mixed forests across the northern Dinaric Mountains. We used multitemporal high-density Airborne Laser Scanning data to validate a procedure for quantifying ice storm damage in stands dominated by Norway spruce, silver fir and European beech, using field data as a reference. LiDAR-derived leaf area density profiles and voxel-based biomass loss estimates effectively reflected field-observed patterns. Methods based on individual-tree segmentation underestimated post-disturbance tree density reductions, but basal area and volume loss estimates aligned closely with field measurements, even at low point densities. These methods offer a scalable approach to damage assessment and improve understanding of the spatial variability of ice storm impacts. They also hold considerable promise for land managers with access to regional bitemporal LiDAR datasets.

Understanding competition between trees is essential for sustainable forest management as interactions between trees in uneven-aged mixed forests play a key role in growth dynamics. This study investigated nine competition indices (CIs) for their suitability to model the effects of neighboring trees on silver fir (Abies alba) growth in Dinaric silver fir-European beech (Fagus sylvatica) forests. Although numerous competition indices have been developed, there is still limited consensus on their applicability in different forest types, especially in mature, structurally complex forest stands. The indices were evaluated using the adjusted coefficient of determination in a linear model wherein the volume growth of the last five years for 60 dominant silver fir trees was modeled as a function of tree volume and competition index. The results demonstrated that distance-dependent indices (e.g., the Hegyi height-distance competition and Rouvinen-Kuuluvainen diameter-distance competition indices), which consider the distance to competitors and their size, perform better than distance-independent indices. Using the optimization procedure in calculating the competition indices, only neighboring trees at a distance of up to 26-fold the diameter at breast height (DBH) of the selected tree (optimal search radius) and with a DBH of at least 20% of that of the target tree (optimal DBH) were considered competitors. Therefore, competition significantly influences the growth of dominant silver firs even in older age classes. The model based solely on tree volume explained 32.5% of the variability in volume growth, while the model that accounted for competition explained 64%. Optimizing the optimal search radius had a greater impact on model performance than optimizing the DBH threshold. This emphasizes the importance of balancing stand density and competition in silvicultural practice.

Rockfalls present a significant hazard to human activities; therefore, their identification and knowledge about potential spatial impacts are important in planning protection measures to reduce rockfall risk. Remote sensing with unmanned aerial vehicles (UAVs) has allowed for the accurate observation of slopes that are susceptible to rockfall activity via various methods and sensors with which it is possible to digitally collect information about the rockfall activity and spatial distributions. In this work, a three-dimensional (3D) reconstruction of rock deposits (width, length, and height) and their volumes are addressed, and the results are used in a rockfall trajectory simulation. Due to the availability of different sensors on the UAV, the aim was also to observe the possible differences in the dimension estimations between photogrammetric and LiDAR (light detection and ranging) point clouds, besides the most traditional method where rock deposit dimensions are measured on the field using a measuring tape. The motivation for reconstructing rock dimensions and volumes was solely for obtaining input parameters into a rockfall model. In order to study the differences between rock-measuring methods, rock dimensions were used as input parameters in a rockfall model, and additionally, modeling results such as propagation probability, maximum kinetic energies, and maximum passing heights were compared. The results show that there are no statistically significant differences between the measurement method with respect to rock dimensions and volumes and when modeling the propagation probability and maximum passing heights. On the other hand, large differences are present with maximum kinetic energies where LiDAR point cloud measurements achieved statistically significantly different results from the other two measurements. With this approach, an automated collection and measurement process of rock deposits is possible without the need for exposure to a risk of rockfall during fieldwork.

The spatial variability of precipitation in Slovenia was evaluated using correlation decay distance analysis (CDD). CDD analysis essentially explores how the correlation between neighbouring stations varies according to distance. We analysed CDD for the period December 2009-November 2019 using only those meteorological stations (n = 160) with no missing values and operating at same location for the whole analysed period. For each meteorological station, we calculated the threshold distance at which the correlation between series is higher than 0.707 (r2 = 0.5). The results indicate that the highest spatial variability in precipitation is during summer (CDD = 50 km), followed by spring (CDD = 76 km), autumn (CDD = 120 km) and winter (CDD = 141 km), when the spatial variability is the lowest. The spatial variability of precipitation is similar in spring and autumn (with the lowest variability of precipitation in E and SE Slovenia), and it is lowest in S Slovenia in summer and in NW Slovenia in winter. The variogram map indicates anisotropy in the correlation decay distance for spring precipitation. Higher values of semivariance are evident in the NE-SW direction, while semivariance values in the SE-NW direction are much lower.

In this paper, we present an identification of rockfall-injured trees based on multiband images obtained by an unmanned aerial vehicle (UAV). A survey with a multispectral camera was performed on three rockfall sites with versatile tree species (Fagus sylvatica L., Larix decidua Mill., Pinus sylvestris L., Picea abies (L.) Karsten, and Abies alba Mill.) and with different characterizations of rockfalls and rockfall-induced injuries. At one site, rockfall injuries were induced in the same year as the survey. At the second site, they were induced one year after the initial injuries, and at the third site, they were induced six years after the first injuries. At one site, surveys were performed three years in a row. Multiband images were used to extract different vegetation indices (VIs) at the tree crown level and were further studied to see which VIs can identify the injured trees and how successfully. A total of 14 VIs were considered, including individual multispectral bands (green, red, red edge, and near-infrared) by using regression models to differentiate between the injured and uninjured groups for a single year and for three consecutive years. The same model was also used for VI differentiations among the recorded injury groups and size of the injuries. The identification of injured trees based on VIs was possible at the sites where rockfall injuries were induced at least one year before the UAV survey, and they could still be identifiable six years after the initial injuries. At the site where injuries were induced only four months before the UAV survey, the identification of injured trees was not possible. VIs that could explain the largest variability (R2 > 0.3) between injured and uninjured trees were: inverse ratio index (IRVI), green–red vegetation index (GRVI), normalized difference vegetation index (NDVI), normalized ratio index (NRVI), and ratio vegetation index (RVI). RVI was the most successful, explaining 40% of the variance at two sites. R2 values only increased by a few percentages (up to 10%) when the VIs of injured trees were observed over a period of three years and mostly did not change significantly, thus not indicating if the vitality of the trees increased or decreased. Differentiation among the injured groups did not show promising results, while, on the other hand, there was a strong correlation between the VI values (RVI) and the size of the injury according to the basal area of the trees (so-called injury index). Both in the case of broadleaves and conifers at two sites, the R2 achieved a value of 0.82. The presented results indicate that the UAV-acquired multiband images at the tree crown level can be used for surveying rockfall protection forests in order to monitor their vitality, which is crucial for maintaining the protective effect through time and space.

Forests play a central role in the management of the Earth’s climate. Airborne laser scanning (ALS) technologies facilitate the monitoring of large and impassable areas and can be used to monitor the 3D structure of forests. While the ALS-based forest measures have been studied in depth, 3D change detection in forests is still a subject of little attention in the literature due to the challenges introduced by comparing point cloud pairs. In this study, we propose an innovative methodology to (i) automatically perform a 3D change detection of forests on an individual tree level; (ii) estimate tree parameters with allometric equations; and (iii) perform an assessment of the aboveground biomass (AGB) variation over time. The area in which the tests were carried out was hit by an ice storm that occurred in the time interval between the two LiDAR acquisitions; furthermore, field measurements were carried out and used to validate the results. The single-tree segmentation of the point clouds was automatically performed with a local maxima algorithm to detect the treetop, and a decision tree method to define the individual crowns around the local maxima. The multitemporal comparison of the point clouds was based on the identification of single trees, which were matched when there was a correlation between the position of the treetops. For each tree, the DBH (diameter at breast height) and the AGB were also estimated using allometric equations. The results are promising and allowed us to identify the uprooted trees and estimate that about 40% of the AGB of the area under examination had been destroyed, with an RMSE over the estimation ranging between 4% and 21% in four scenarios.

In Slovenia, torrent areas and forest roads are being regulated and built mostly in steep, erosion-prone areas. In addition to the geometry of extrapolated works, calculating bulk factors is key for estimating haulage masses. We have determined bulk factors for compact carbonate rock, mixed soil, and carbonate deposits. Each construction site was recorded with an unmanned aerial vehicle (UAV) before the excavation and after every 4±2 m3 of excavated material. The average point cloud density was 9535 points/m2. We processed the point clouds from each construction site and determined the difference in volume between the volume of excavated area and the volume of deposited material. The average bulk factor for compact carbonate rock is 1.42, 1.20 for mixed soil and 1.15 for carbonate deposits (calculated for fully loaded eight-wheeled truck). The calculated bulk factors for soils and carbonate deposits match with the already established values, while the factor for compact rock is 20% lower than the factor currently in use by the Slovenian forest engineers.

The spatial variability of precipitation in Slovenia was evaluated using correlation decay distance analysis (CDD). CDD analysis essentially explores how the correlation between neighbouring stations varies according to distance. We analysed CDD for the period December 2009–November 2019 using only those meteorological stations (n = 160) with no missing values and operating at same location for the whole analysed period. For each meteorological station, we calculated the threshold distance at which the correlation between series is higher than 0.707 (r2 = 0.5). The results indicate that the highest spatial variability in precipitation is during summer (CDD = 50 km), followed by spring (CDD = 76 km), autumn (CDD = 120 km) and winter (CDD = 141 km), when the spatial variability is the lowest. The spatial variability of precipitation is similar in spring and autumn (with the lowest variability of precipitation in E and SE Slovenia), and it is lowest in S Slovenia in summer and in NW Slovenia in winter. The variogram map indicates anisotropy in the correlation decay distance for spring precipitation. Higher values of semivariance are evident in the NE-SW direction, while semivariance values in the SE-NW direction are much lower.

Based on the laser point clouds of 240 individual trees that were also identified in the field, we developed decision trees to distinguish deciduous and coniferous trees and individual tree species: Picea abies, Larix decidua, Pinus sylvestris, Fagus sylvatica, Acer pseudoplatanus, Fraxinus excelsior. The volume of the upper part of the tree crown (height of 3 m) and the average intensity of the laser reflections were used as explanatory variables. There were four aerial laser datasets: May 2012, September 2012, March 2013 and July 2015. We found that the combination of the volume and the average intensity of the first three laser datasets was the most reliable for predicting the selected tree species (60% model performance). A slightly poorer model performance was obtained if only the average intensity of the first three datasets was used (54% model performance). The worst model performance was given by the intensities (31 % model performance) or the volumes (21 % model performance) of dataset 4, which represents the national laser scanning of Slovenia (LSS). The best performing was the deciduous and coniferous separation, which achieved 75% and 95% success based on the test data (combination of volume and average intensity of the first three laser datasets). Using only the LSS intensities, deciduous and coniferous trees could be separated with 81% success.

This article examines how digital terrain model (DTM) grid cell size influences rockfall modelling using a probabilistic process-based model, Rockyfor3D, while taking into account the effect of forest on rockfall propagation and runout area. Two rockfall sites in the Trenta valley, NW Slovenia, were chosen as a case study. The analysis included DTM square grid cell sizes of 1, 2, 5, and 10 m, which were extracted from LiDAR data. In the paper, we compared results of rockfall propagation and runout areas, maximum kinetic energy, and maximum passing height between different grid cell sizes and forest/no forest scenario, namely by using goodness-of-fit indices (average index, success index, distance to the perfect classification, true skill statistics). The results show that the accuracy of the modelled shape of rockfall propagation and runout area decreases with larger DTM grid cell sizes. The forest has the important effect of reducing the rockfall propagation only at DTM1 and DTM2 and only if the distance between the source area and forest is large enough. Higher deviations of the maximum kinetic energy are present at DTMs with larger grid cell size, while differences are smaller at more DTMs with smaller grid cell sizes. Maximum passing height varies the most at DTM1 in the forest scenario, while at other DTMs, it does not experience larger deviations in the two scenarios.

The concepts of ecotopes and forest sites are used to describe the correlative complexes defined by landform, vegetation structure, forest stand characteristics and the relationship between soil and physiography. Physically heterogeneous landscapes such as karst, which is characterized by abundant sinkholes and outcrops, exhibit diverse microtopography. Understanding the variation in the growth of trees in a heterogeneous topography is important for sustainable forest management. An R script for detailed stem analysis was used to reconstruct the height growth histories of individual trees (steam analysis). The results of this study reveal that the topographic factors influencing the height growth of silver fir trees can be detected within forest stands. Using topography modelling, we classified silver fir trees into groups with significant differences in height growth. This study provides a sound basis for the comparison of forest site differences and may be useful in the calibration of models for various tree species.

Debris flows can transport large amounts of material and therefore present a significant threat to infrastructure and human life. In this research, we used tree-ring width analyses to quantify the response of trees to three debris flow events in NW Slovenia (Javoršček, Srpenica) and W Slovenia (Nikova) for which we know the time of origin. We attempted to date these and similar tree responses in the past and compared the patterns between different tree species. Altogether, we sampled 147 trees across a range of tree species (Fagus sylvatica, Pinus sylvestris, Fraxinus excelsior, Fraxinus ornus, Acer pseudoplatanus, Picea abies, Juglans regia, Acer campestre, Tilia cordata and Ostrya carpinifolia), including reference trees that were outside the debris flow fan. For 91 trees, we constructed tree-ring chronologies and used pointer-year analysis to identify years that had abnormal growth. For the remaining trees (mostly Ostrya carpinifolia, Tilia cordata and Acer pseudoplatanus), we either could not accurately distinguish tree rings or two samples from a single tree showed significantly different growth patterns. The growth patterns of Fagus sylvatica and Picea abies following debris flow events showed a weak response at the Javoršček site and no clear responses at the other two sites. Tree species responded similarly at the same locations. Due to the lack of a clear response pattern, we were not able to reconstruct past debris flows.

Unmanned aerial photogrammetric surveys are increasingly being used for mapping and studying natural hazards, such as rockfalls. Surveys using unmanned aerial vehicles (UAVs) can be performed in remote, hardly accessible, and dangerous areas, while the photogrammetric-derived products, with high spatial and temporal accuracy, can provide us with detailed information about phenomena under consideration. However, as photogrammetry commonly uses indirect georeferencing through bundle block adjustment (BBA) with ground control points (GCPs), data acquisition in the field is not only time-consuming and labor-intensive, but also extremely dangerous. Therefore, the main goal of this study was to investigate how accurate photogrammetric products can be produced by using BBA without GCPs and auxiliary data, namely using the coordinates X0, Y0 and Z0 of the camera perspective centers computed with PPK (Post-Processing Kinematic). To this end, orthomosaics and digital surface models (DSMs) were produced for three rockfall sites by using images acquired with a DJI Phantom 4 RTK and the two different BBA methods mentioned above (hereafter referred to as BBA_traditional and BBA_PPK). The accuracy of the products, in terms of the Root Mean Square Error (RMSE), was computed by using verification points (VPs). The accuracy of both BBA methods was also assessed. To test the differences between the georeferencing methods, two statistical test were used, namely a paired Student’s t-test, and a non-parametric Wilcoxon signed-rank. The results show that the accuracy of the BBA_PPK is inferior to that of BBA_traditional, with the total RMSE values for the three sites being 0.056, 0.066, and 0.305 m, respectively, compared to 0.019, 0.036 and 0.014 m obtained with BBA_traditional. The accuracies of the BBA methods are reflected in the accuracy of the orthomosaics, whose values for the BBA_PPK are 0.039, 0.043 and 0.157 m, respectively, against 0.029, 0.036 and 0.020 m obtained with the BBA_traditional. Concerning the DSM, those produced with the BBA_PPK method present accuracy values of 0.065, 0.072 and 0.261 m, respectively, against 0.038, 0.060 and 0.030 m obtained with the BBA_traditional. Even though that there are statistically significant differences between the georeferencing methods, one can state that the BBA_PPK presents a viable solution to map dangerous and exposed areas, such as rockfall transit and deposit areas, especially for applications at a regional level.

Heat islands (HI) are a common anthropogenic phenomenon and are defined as artificial surfaces (urban areas) that have a higher average temperature than their surroundings (rural areas). The aim of this work was to determine the influence of land use on the spatial distribution and intensity (HIi ) of HI in Slovenia. The MODIS Land Surface Temperature (LST) and Corine Land Cover (CLC) databases were used to perform the analysis. Within the identified HI, two HI levels were determined based on temperature difference. The results revealed a statistically significant negative correlation between HIi and both forest co%ver and forest fragmentation (forest edge density and ratio of mean forest patch size to HI size). Artificial surface was positively correlated with HIi . The results contribute to the understanding of the spatial distribution of HI and HIi and provide informati%on for spatial planning and policy-making to reduce the negative impact of HI.

The present study addresses the short-term effects of different harvest intensities under close-to-nature selective management on the upper soil layers in Slovenian and Bosnian Dinaric karst fir-beech forests. The different harvest intensities coincided with the single-tree and irregular shelterwood management, common in the region. The effect of harvesting intensity on the upper soil layers (Ol, Of, Ol and 0–10 cm mineral soil) was investigated by a repeated measurements experiment in Slovenia on 27 research plots in close-to nature managed forests. The properties of the upper layers (concentration of SOC and TN, C/N ratio, weights, BD and SOC stocks) were analyzed twice, before (2011) and after (2014) treatment of 50% and 100% harvest intensity in relation to the total standing growing stock of trees. As a control, we used no-treatment <20% harvesting intensity plots. To extend this experiment, we added three comparable plots from the Bosnian site: one in an old-growth forest with 0% harvest intensity and two in the managed forest with <20% harvest intensity. The results of the assessment of mean differences indicated a significant influence of harvesting intensity on the decrease in SOC, TN concentrations, weights and SOC stocks in the organic layers and the increase in BD and SOC stocks in the 0–10 cm mineral soil. The highest relative decreases in Ol, Of and Oh SOC stocks occurred in 50% (−10 and −38%) and 100% (−16 and −49%) harvest intensities. Negligible relative differences in both organic and 0–10 cm mineral layers were found for the <20% harvest intensity in the region. The change in forest light conditions resulting from differences in canopy openness as a function of applied harvest intensity explained the significant difference in the properties of the upper soil layers. The impact of the short-term losses in SOC stocks, in terms of overall soil productivity, may depend on the regeneration dynamics and melioration methods.

Abiotic and biotic disturbances in alpine forests can reduce forest cover or change the structure of the forest and consequently reduce the protective effect of forest against natural hazards such as avalanches and rockfalls. In this review article, the effect of the main abiotic (forest fire, windthrow, ice break, snow break, avalanche and rockfall) and biotic (insects and pathogens) disturbances in protection forests are presented along with their potential influence on the protective effect of forest against avalanches and rockfalls. In general, natural disturbances negatively affect the protective effect of forest, especially in the case of large-scale and severe events, which in alpine areas are mostly caused by storms, bark beetle outbreaks, avalanches and forest fires. Climate change induced interactions between disturbances are expected to present challenges in the management of protection forests in the future.

Among the functions provided by forests, protection has always been considered one of the preeminent in mountain areas. In order to fulfil, maximize, and sustain this function, specific forest structures should be obtained and maintained through properly designed forest management. A specific management goal should be defined with a well-defined forest target against each natural hazard, based on the protection potentially provided by the forest stands, in either an active (e.g. against avalanches) or passive way (e.g. against rockfall). Climate change is forecast to affect both disturbance regimes and forest ecosystems, leading to new challenging issues concerning protection forest management. This paper describes how a forest stand exerts its protective role against rockfalls and the target profile to be reached for sustaining this function. Potential consequences of climate change on forest ecosystems that management will have to face in the near future are also addressed. New perspectives are provided taking into account the knowledge coming from recent research studies and specifically the results obtained in the RockTheAlps project (ASP462), dealing with the assessment of protection forests against rockfall in the Alps.

Rockfalls are one of the most common natural hazards in mountainous areas that pose high risk to people and their activities. Rockfall risk assessment is commonly performed with the use of models that can simulate the potential rockfall source, propagation and runout areas. The quality of the models can be improved by collecting data on past rockfall events. Mobile crowdsourcing is becoming a common approach for collecting field data by using smartphones, the main advantages of which are the use of a harmonised protocol, and the possibility of creating large datasets due to the simultaneous use by multiple users. This paper presents a new methodology for collecting past rockfall events with a mobile application, where the locations and attributes of rockfall source areas and rockfall deposits are collected, and the data are stored in an online database which can be accessed via the WebGIS platform. The methodology also presents an approach for calculating an actual source location based on viewshed analysis which greatly reduces the problem of field mapping of inaccessible source areas. Additionally, we present a rockfall database in the Alpine Space that has been created by the presented methodology, and an application of collected data for the calibration and validation of two rockfall models (CONEFALL and Rockyfor3D).