Search Results (9)

Deep gravitational slope deformations (DsGSDs) are a geological and engineering challenge with important implications for slope stability, the reliability of existing infrastructures, land use and, above all, the safety of settlements. This paper focuses on the DsGSD phenomenon that affects a large part of the Borrano hamlet, located in the municipality of Civitella del Tronto (Abruzzo Region, Central Italy). This instability is characterized by slow movements of large volumes of material. The main factors initiating deformations are a combination of geological and hydrogeological aspects. These factors include the complex local stratigraphy, composed of pelitic and arenaceous facies at high slope dip angles, and extreme natural events such as heavy rainfall and earthquakes. This study employs a multidisciplinary approach integrating in field activities such as remote-controlled surface monitoring (clinometers and strain gauges), in-depth monitoring (inclinometers and piezometers), aero-photogrammetric analysis and numerical modelling. These techniques permitted us to characterize the evolution of the slope and to identify both the critical sliding surfaces and the mechanisms governing the ground movements. Soil deformations were mainly observed in the central zone of the hamlet. Significant deformations were recorded along planes of weakness at depth between arenaceous and pelitic materials. These planes represent contact zones between the clayey–marly facies, characterized by low strength, and the arenaceous facies, characterized by higher stiffness, creating a mechanical contrast that favours the development of large deformations. The numerical analyses confirmed good correlation with the monitoring data, revealing in detail the instability of both local and territorial processes. The 3D numerical analysis showed how the movements are controlled by planes of weakness, highlighting the key rule of geological discontinuities. Full article

Forest attributes, such as standing stock, diameter at breast height (DBH), tree height, and basal area, are critical for effective forest management; yet, traditional estimation methods remain labor-intensive and often lack the spatial detail required for contemporary decision-making. This study addresses these challenges by integrating machine learning algorithms with high-resolution remotely sensed data and rigorously collected ground truth measurements to produce accurate, national-scale maps of forest attributes in Romania. To ensure the reliability of the model predictions, extensive field campaigns were conducted across representative Romanian forests. During these campaigns, detailed measurements were recorded for every tree within selected plots. For each tree, DBH was measured directly, and tree heights were obtained either by direct measurement—using hypsometers or clinometers—or, when direct measurements were not feasible, by applying well-established DBH—height allometric relationships that have been calibrated for the local forest types. This comprehensive approach to ground data collection, supplemented by an independent dataset from Brasov County collected using the same protocols, allowed for robust training and validation of the machine learning models. This study evaluates the performance of three machine learning algorithms—Random Forest (RF), Classification and Regression Trees (CART), and the Gradient Boosting Tree Algorithm (GBTA)—in predicting the forest attributes from Sentinel-2 satellite imagery. While Random Forest consistently delivered high R² values and low root mean square errors (RMSE) across all attributes, GBTA showed particular strength in predicting standing stock, and CART excelled in basal area estimation but was less reliable for other attributes. A sensitivity analysis across multiple spatial resolutions revealed that the performance of all algorithms varied significantly with changes in resolution, emphasizing the importance of selecting an appropriate scale for accurate forest mapping. By focusing on both the methodological advancements in machine learning applications and the rigorous, detailed empirical forest data collection, this study provides a clear solution to the problem of obtaining reliable, spatially detailed forest attribute maps. Full article

Tropical forests provide habitats for diverse flora and fauna, in addition to playing a crucial role in climate regulation. They are being recognized for their roles as nature-based solutions to many sustainable development challenges, as shown by increased political commitment and global promises to reduce the rates of deforestation and boost the restoration of degraded forest ecosystems. Understanding tropical forest dynamics and their conservation status is therefore important. This study analysed the forest stand structure, the tree species composition and the regeneration status of Londiani Forest. In the three blocks of Londiani Forest, which are Kedowa, Chebewor and Londiani, belt transects that were 25 m wide and 1 km long were established. At every 200 m along the transects, 25 m × 25 m quadrats were set up in which an inventory of all the tree species was determined. Diameter tape was used to measure the diameter at breast height (DBH) 1.3 m above the ground. With the use of a Suunto angular clinometer, the tree height was measured. A nested 5 m × 5 m quadrat within the 25 m × 25 m quadrat was used to sample the saplings, while a 1m × 1 m quadrat was used to sample the seedlings. The quantities of seedlings and saplings were used to determine the state of regeneration. The data were entered into Microsoft Excel. The total stem density, species density, basal area, species basal area, relative density and species diversity were determined and extrapolated per hectare. A total of 1308 distinct trees from 34 different species and 24 families were counted. Kedowa recorded the highest (27) species richness, followed by Chebewor (19) and then Londiani (14). There was a statistically significant difference in the species richness among the three forest blocks (p < 0.05). Within the three forest blocks, there were no statistically significant variations in the basal area distribution (p > 0.005) or in the mean DBH (F = 0.560; p = 0.729) or height class distribution (F = 0.821; p = 0.558). There was a statistically significant difference in the stem density (F = 12.22; p = 0.005) and woody species diversity (F = 0.32; p = 0.001) within the three forests blocks. The similarity index ranged from 0.34–0.47. The presence of substantial numbers of seedlings and saplings in all forest blocks was an indication that there was regeneration. Full article

The stability of many shallow caves and rock shelters relies heavily on understanding rock discontinuities, such as stratification, faults, and joints. Analyzing these discontinuities and determining their orientations and dispersion are crucial for assessing the overall stability of the cave or shelter. Traditionally, this analysis has been conducted manually using a compass with a clinometer, but it has certain limitations, as only fractures located in accessible areas like the lower part of cave walls and entrances are visible and can be assessed. Over the past decade, remote sensing techniques like LiDAR and photogrammetry have gained popularity in characterizing rocky massifs. These techniques provide 3D point clouds and high-resolution images of the cave or shelter walls and ceilings. With these data, it becomes possible to perform a three-dimensional reconstruction of the cavity and obtain important parameters of the discontinuities, such as orientation, spacing, persistence, or roughness. This paper presents a comparison between the geomechanical data obtained using the traditional manual procedures (compass readings in accessible zones) and a photogrammetric technique called Structure from Motion (SfM). The study was conducted in two caves, namely, the Reguerillo Cave (Madrid) and the Cova dos Mouros (Lugo), along with two rock shelters named Abrigo de San Lázaro and Abrigo del Molino (Segovia). The results of the study demonstrate an excellent correlation between the geomechanical parameters obtained from both methods. Indeed, the combination of traditional manual techniques and photogrammetry (SfM) offers significant advantages in developing a more comprehensive and realistic discontinuity census. Full article

In this work, a high-resolution survey of the coseismic ground ruptures due to the 2016 Central Italy seismic sequence, performed through a dedicated software installed on a digital device, is strengthened by the analysis of a set of drone-acquired images. We applied this integrated approach to two active sections of the Mt Vettore active fault segment which, in the Castelluccio di Norcia plain (central Italy), were affected by surface faulting after the most energetic events of the sequence: the 24 August, Mw 6.0, Amatrice and 30 October, Mw 6.5, Norcia earthquakes. The main aim is to establish the range in which the results obtained measuring the same structures using different tools vary. An operating procedure, which can be helpful to map extensive sets of coseismic ground ruptures especially where the latter affects wide, poorly accessible, or dangerous areas, is also proposed. We compared datasets collected through different technologies, including faults attitude, dip-angles, coseismic displacements, and slip vectors. After assessing the accuracy of the results, even at centimetric resolutions, we conclude that the structural dataset obtained through remote sensing techniques shows a high degree of reliability. Full article

Marble quarries are quite dangerous environments in which rock falls may occur. As many workers operate in these sites, it is necessary to deal with the matter of safety at work, checking and monitoring the stability conditions of the rock mass. In this paper, some results of an innovative analysis method are shown. It is based on the combination of Distributed Optical Fiber Sensors (DOFS), digital photogrammetry through Unmanned Aerial Vehicle (UAV), topographic, and geotechnical monitoring systems. Although DOFS are currently widely used for studying infrastructures, buildings and landslides, their use in rock marble quarries represents an element of peculiarity. The complex morphologies and the intense temperature range that characterize this environment make this application original. The selected test site is the Lorano open pit which is located in the Apuan Alps (Italy); here, a monitoring system consisting of extensometers, crackmeters, clinometers and a Robotic Total Station has been operating since 2012. From DOFS measurements, strain and temperature values were obtained and validated with displacement data from topographic and geotechnical instruments. These results may provide useful fundamental indications about the rock mass stability for the safety at work and the long-term planning of mining activities. Full article

We contribute to a better understanding of different remote sensing techniques for tree height estimation by comparing several techniques to both direct and indirect field measurements. From these comparisons, factors influencing the accuracy of reliable tree height measurements were identified. Different remote sensing methods were applied on the same test site, varying the factors sensor type, platform, and flight parameters. We implemented light detection and ranging (LiDAR) and photogrammetric aerial images received from unmanned aerial vehicles (UAV), gyrocopter, and aircraft. Field measurements were carried out indirectly using a Vertex clinometer and directly after felling using a tape measure on tree trunks. Indirect measurements resulted in an RMSE of 1.02 m and tend to underestimate tree height with a systematic error of −0.66 m. For the derivation of tree height, the results varied from an RMSE of 0.36 m for UAV-LiDAR data to 2.89 m for photogrammetric data acquired by an aircraft. Measurements derived from LiDAR data resulted in higher tree heights, while measurements from photogrammetric data tended to be lower than field measurements. When absolute orientation was appropriate, measurements from UAV-Camera were as reliable as those from UAV-LiDAR. With low flight altitudes, small camera lens angles, and an accurate orientation, higher accuracies for the estimation of individual tree heights could be achieved. The study showed that remote sensing measurements of tree height can be more accurate than traditional triangulation techniques if the aforementioned conditions are fulfilled. Full article

Forest resource information has a hierarchical structure: individual tree attributes are summed at the plot level and then in turn, plot-level estimates are used to derive stand or large-area estimates of forest resources. Due to this hierarchy, it is imperative that individual tree attributes are measured with accuracy and precision. With the widespread use of different measurement tools, it is also important to understand the expected degree of precision associated with these measurements. The most prevalent tree attributes measured in the field are tree species, stem diameter-at-breast-height (dbh), and tree height. For dbh and height, the most commonly used measuring devices are calipers and clinometers, respectively. The aim of our study was to characterize the precision of individual tree dbh and height measurements in boreal forest conditions when using calipers and clinometers. The data consisted of 319 sample trees at a study area in Evo, southern Finland. The sample trees were measured independently by four trained mensurationists. The standard deviation in tree dbh and height measurements was 0.3 cm (1.5%) and 0.5 m (2.9%), respectively. Precision was also assessed by tree species and tree size classes; however, there were no statistically significant differences between the mensurationists for dbh or height measurements. Our study offers insights into the expected precision of tree dbh and height as measured with the most commonly used devices. These results are important when using sample plot data in forest inventory applications, especially now, at a time when new tree attribute measurement techniques based on remote sensing are being developed and compared to the conventional caliper and clinometer measurements. Full article

Studies estimating canopy volume are mostly based on laborious and time-consuming field measurements; hence, there is a need for easier and convenient means of estimation. Accordingly, this study investigated the use of remotely sensed data (WorldView-2 and LiDAR) for estimating tree height, canopy height and crown diameter, which were then used to infer the canopy volume of remnant eucalypt trees at the Newholme/Kirby ‘SMART’ farm in north-east New South Wales. A regression model was developed with field measurements, which was then applied to remote-sensing-based measurements. LiDAR estimates of tree dimensions were generally lower than the field measurements (e.g., 6.5% for tree height) although some of the parameters (such as tree height) may also be overestimated by the clinometer/rangefinder protocols used. The WorldView-2 results showed both crown projected area and crown diameter to be strongly correlated to canopy volume, and that crown diameter yielded better results (Root Mean Square Error RMSE 31%) than crown projected area (RMSE 42%). Although the better performance of LiDAR in the vertical dimension cannot be dismissed, as suggested by results obtained from this study and also similar studies conducted with LiDAR data for tree parameter measurements, the high price and complexity associated with the acquisition and processing of LiDAR datasets mean that the technology is beyond the reach of many applications. Therefore, given the need for easier and convenient means of tree parameters estimation, this study filled a gap and successfully used 2D multispectral WorldView-2 data for 3D canopy volume estimation with satisfactory results compared to LiDAR-based estimation. The result obtained from this study highlights the usefulness of high resolution data for canopy volume estimations at different locations as a possible alternative to existing methods. Full article