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.
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).
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.
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.
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.
Spatial models are an effective tool for determining potential rockfall source, transit and deposit areas. The reliability of the final rockfall modelling results depends on the quality of the input ...data, which is mostly based on the digital elevation model (DEM). The spatial resolution of the DEM holds key information about the main morphological properties of the surface, which is crucially important when modelling this kind of geomorphological phenomenon. Therefore, this article studies the influence of DEM spatial resolution on the modelling of rockfall source, transit and deposit areas. Modelling was carried out at five different DEM spatial resolutions available for Slovenia (1 m, 5 m, 12.5 m, 25 m and 100 m). Rockfall source areas were identified using a geomorphometric approach based on a high resolution DEM and a geographical information system. Rockfall transit and deposit areas were modelled using the Conefall computer program, which is designed to estimate potential rockfall risk areas. The area of study was the municipality of Vipava (107.4 km2) in Slovenia, EU. A spatial resolution of 1 m was chosen as a reference layer to which all modelling results of the other spatial resolutions were compared. Validation of modelling included rockfall source area comparison with orthorectified aerial images and location collection of silent witnesses (rock deposits) in the field for estimating maximum runout zones. The modelling results indicate that a spatial resolution of 1 m is the most suitable for modelling on a local scale; resolutions of 5, 12.5 and 25 m can be used for modelling on a regional scale (depending on the purpose of the modelling results); and a resolution of 100 m should not be used for rockfall modelling. Major differences between spatial resolutions can be observed when modelling rockfall source areas, i.e. in areas with the most diverse topography, while in deposit areas the observed differences are smaller due to the less rugged surface.
•The influence of the spatial resolution of the digital elevation model was observed at five different spatial resolutions.•Deviations between modelling results are greater for rockfall source areas than for rockfall runout zones.•High spatial resolutions (1 m) should be used for modelling on a local scale.•Lower spatial resolutions (5 m, 12.5 m and 25 m) can be used for modelling on a regional scale.•Spatial resolution 100 m should not be used for modelling rockfalls.
Provider: - Institution: - Data provided by Europeana Collections- Pišece Castle, photographed in 2006- All metadata published by Europeana are available free of restriction under the Creative ...Commons CC0 1.0 Universal Public Domain Dedication. However, Europeana requests that you actively acknowledge and give attribution to all metadata sources including Europeana
Provider: - Institution: - Data provided by Europeana Collections- Ruins of the Gamberk Castle, photographed in 2008- All metadata published by Europeana are available free of restriction under the ...Creative Commons CC0 1.0 Universal Public Domain Dedication. However, Europeana requests that you actively acknowledge and give attribution to all metadata sources including Europeana
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