Mapping of debris flows by the morphometric analysis of DTM: a case study of the Vrátna dolina Valley, Slovakia

Abstract

Mapping of debris flows by the morphometric analysis of DTM: a case study of the Vrátna dolina Valley, Slovakia The main objective of this contribution is to detect the morphogenetic processes by the numerical method of the differential geometry technique and compare the results with field surveying. The area of interest, the Vrátna dolina Valley, is located in the Malá Fatra Mountains in the northern part of Slovakia. Extensive mass movement deformations occurred in the surveyed area in 2014 induced by extreme precipitation events caused considerable damage. The Proxima software technology has been used to identify terrain elements using a precise digital terrain model (DTM) for the localisation of the debris flows head scarps. Precise DTM was derived from the airborne laser scanning (ALS) data. The morphometric analysis of landslide area was carried out on four selected locations. Verification of numerical mapping was performed by comparing results to the field survey data through visual comparison and area computation. Supplementary data was used in the form of orthophoto mosaics. The used spatial analysis applied on ALS data shows a high coincidence with the detection of the head scarps by field surveying, particularly in the hard to access and afforested areas. The main advantage of this approach lies in the reduction of field surveying and in the possible detection of the terrain changes not found during field surveying.

TLS and SfM Approach for Bulk Density Determination of Excavated Heterogeneous Raw Materials

“…In TLS and photogrammetry, these also depend on the distance of the sensor to the measured object. Large-scale photogrammetry or lidar surveying of the ground surface is characterized by RMSE of more than 10 mm [11,20,21,36]. For small-scale surveying, the measurement accuracy of a few mm and high density of points can be expected.…”

“…Generally, in the field of geosciences and mining industry, many studies deal with the issue of surface modeling. For example, Blistan et al successfully used UAV photogrammetry to model rock outcrops in the surface quarry also used in this research [17]; Gallay et al used the combination of TLS technology and digital 3D modeling for surface reconstruction to derive geomorphic properties of underground cave spaces [18]; Hofierka et al defined a workflow to process massive data from terrestrial and airborne laser scanning to derive accurate digital models representing surface and subsurface geomorphological features [19]; airborne laser scanning was also used to map and model slope deformations in a badly accessible terrain by Fraštia et al [20]; digital terrain models derived from LiDAR and UAV data were successfully used for safety, remediation, and ecological problems by Moudrý et al [21].…”

Spatial Analysis of Point Clouds Obtained by SfM Photogrammetry and the TLS Method—Study in Quarry Environment

“…These indications have made UAS photogrammetry a competitive and efficient substitute for traditional geodetic techniques in terms of both quality and efficiency. In many different fields and disciplines, including mining [1,2], real estate cadastre [3,4], industry [5,6], geology [7,8], archeology [9,10], architecture [11,12], agriculture [13,14], and monitoring natural processes in the landscape [15,16], geohazards [17,18], or landslides [19,20], measurement using unmanned aerial system (UAS) technology is used.…”

Filtering Green Vegetation Out from Colored Point Clouds of Rocky Terrains Based on Various Vegetation Indices: Comparison of Simple Statistical Methods, Support Vector Machine, and Neural Network

“…It is worth noting that although mass data collection methods are currently very popular in many fields of research involving complex terrain [26], such as coastal monitoring [27][28][29], volcano exploration [30], underground research [31,32], tree detection [33,34], the evolution of rock glaciers [35], monitoring of rock masses [36][37][38], or their geological analysis [39], vegetation filtering in such cases is typically handled by human operators as the performance of automated algorithms proposed for this purpose, so far, is generally poor as confirmed by Blanco et al [6]. Specifically, they usually have problems when encountering highly rugged and/or sloped terrain [15].…”