In this article we introduce a new method for forest management inventories especially suitable for highly-valued timber where the precise estimation of stem parameters (diameter, form, and tapper) plays the key role for market purposes. The unmanned aerial system (UAS)-based photogrammetry is combined with terrestrial photogrammetry executed by walking inside the stand and the individual tree parameters are estimated. We compare two automatic methods for processing of the point clouds and the delineation of stem circumference at breast height. The error of the diameter estimation was observed to be under 1 cm root mean square error (RMSE) and the height estimation error was 1 m. Apart from the mentioned accuracy, the main advantage of the proposed work is shorter time demand for field measurement; we could complete both inventories of 1 hectare forest stand in less than 2 h of field work.

Currently, a large part of forest roads with a bituminous surface course constructed in the Czech Republic in the second half of the last century has been worn out. The aim of the study is to verify the possibility and the accuracy of the road wearing course damage detected by four different remote sensing methods: close range photogrammetry, terrestrial laser scanning, mobile laser scanning and airborne laser scanning. At the beginning of verification, cross sections of the road surface were surveyed geodetically and then compared with the cross sections created in the DTMs which were acquired using the four methods mentioned above. The differences calculated between particular models and geodetic measurements show that close range photogrammetry achieved an RMSE of 0.0110 m and the RMSE of terrestrial laser scanning was 0.0243 m. Based on these results, we can conclude that these two methods are sufficient for the monitoring of the asphalt wearing course of forest roads. These methods allow precise and objective localization, size and quantification of the road damage. By contrast, mobile laser scanning with an RMSE of 0.3167 m does not reach the required precision for the damage detection of forest roads due to the vegetation that affects the precision of the measurements. Similar results are achieved by airborne laser scanning, with an RMSE of 0.1392 m. As regards the time needed, close range photogrammetry appears to be the most appropriate method for damage detection of forest roads.

Forests make up 34.1% of the Czech Republic total area and forest roads account for nearly the same length (47,465 km) as all other roads administered by the state and its regions (55,738 km). Forest roads are not as intensively used as other roads. On the other hand, as logging trucks carry the maximum permitted load on roads and forests create a specific microclimate, forest roads are subject to rapid wear. A road wearing course is generally designed for 20 years of service and for a maximum damage level of 25% before they are supposed to be reconstructed. To ensure this life cycle is adhered to, more efficient, faster, and more flexible surface damage detection adaptable for forest environment is needed. As smartphones and their optical devices, i.e., new iPhones with LiDAR sensors, become more advanced, the option arises to perform laser scanning on road surfaces using smartphones applications. This work aimed to test this technology and its precision applicability to assessing damage to a forest wearing course and compare it with another hand-held personal laser scanner (PLS_hh), represented in this study by GeoSLAM ZEB Horizon scanner, and more precise terrestrial laser scanning (TLS) technology, represented in this study by Faro Focus 3D laser scanner, which have started to replace tacheometric wearing course damage surveying thanks to their greater precision. So, this study involved a comparison of three alternative laser scanning methods focused especially on these, which are implemented in new iPhones for tacheometric surveying. First, a Faro Focus 3D laser scanner was used for the TLS method. Second, the PLS_hh method was tested on a GeoSLAM ZEB Horizon scanner. Third, another PLS_hh method using an iPhone 13 Pro with applications 3D Scanner and Polycam was evaluated. If we are comparing positional height accuracy of PLS_hh to tacheometric surveying on reference cross position height coordinates, ZEB Horizon achieved devXY and devZ RMSE 0.108 m; 0.025 m; iPhone 13 Pro with 3D Scanner app devXY and devZ RMSE 0.185 m; 0.021 m, and with Polycam app devXY and devZ RMSE 0.31 m; 0.045. TLS achieved the best results with devXY RMSE 0.049 and devZ RMSE 0.0077. The results confirm that only the TLS scanner achieves precision values in height differences applicable for an assessment of forest road wearing course damage measurement comparable with tacheometric surveying. Surprisingly, comparing the PLS_hh scanners to the TLS technology, they achieved interesting results, comparing their transverse profiles and 3D objects as digital surface models (DSM) of the road to TLS in height position. In transverse profiles, ZEB Horizon achieved devZ RMSE 0.032 m; iPhone 13 Pro with 3D Scanner app devZ RMSE 0.017 m, and with Polycam app devZ RMSE 0.041 m compared to the TLS method measured using a Faro Focus 3D static laser scanner. Comparing forest road DSM to Faro Focus 3D, ZEB Horizon achieved devZ RMSE 0.028 m; iPhone 13 Pro with 3D Scanner app devZ RMSE 0.018 m and with Polycam devZ RMSE 0.041 m. These results in height differences show that the height accuracy of PLS_hh achieves precision, which is applicable to determining the current shape of forest road wearing course compared to the required roof shape gradient. However, further testing provided the insight that such a kind of PLS_hh measurement is still only possible to use for the identification of a transverse profile shape, as in length measurement the length error increases. All PLS_hh are able to capture the current shape of forest road cross profile, but still they cannot be used for any design or calculation of material measurement needed for wearing course repair.

Topographic Exposure and its Practical Applications: Topographic exposure is a topographic characteristic representing a degree of protection by a surrounding topography of a certain site. Detailed knowledge of topographic exposure has broad use in a number of applications ranging from studying forest wind damage through research on snow storage dynamics to optimisation in positioning wind power stations. This paper describes a method for creation of topographic exposure on the basis of a digital elevation model (DEM) using GIS. In combination with other climatic data on wind direction and speed, this factor is used to define the degree of terrain ventilation. Low terrain ventilation has, among other things, a significant influence on the creation of valley inversions and related vegetation zoning inversions. By combining the degree of terrain ventilation with DEM and forest vegetation zones in the area of the Training Forest Enterprise Křtiny, a clear relationship between the influence of topographic exposure, or terrain ventilation, and the creation of the vegetation zoning inversion was determined.

This paper reviews the use of modern 3D image-based and Light Detection and Ranging (LiDAR) methods of surface reconstruction techniques for high fidelity surveys of small rock outcrops to highlight their potential within structural geology and landscape protection. LiDAR and Structure from Motion (SfM) software provide useful opportunities for rock outcrops mapping and 3D model creation. The accuracy of these surface reconstructions is crucial for quantitative structural analysis. However, these technologies require either a costly data acquisition device (Terrestrial LiDAR) or specialized image processing software (SfM). Recent developments in augmented reality and smartphone technologies, such as increased processing capacity and higher resolution of cameras, may offer a simple and inexpensive alternative for 3D surface reconstruction. Therefore, the aim of the paper is to show the possibilities of using smartphone applications for model creation and to determine their accuracy for rock outcrop mapping.