Landslide inventory and characteristics, based on LiDAR scanning and optimised field investigations in the Kutina area, Croatia

Abstract

This paper presents the preliminary results of analyses of landsliding processes derived from detailed LiDAR (Light Detection and Ranging) scans supported by field prospection on the south-western slopes of Mt. Moslavačka gora, in the wider Kutina area. This area is known for frequent landslides, but dedicated regional landslide research has not been previously undertaken. High resolution LiDAR scanning and orthophoto imaging enabled the production of a reliable landslide inventory, but also enabled research on landslide properties and the morphology of the area. Field mapping and prospection, sampling and borehole coring assisted in the collection of information about the material characteristics and specific features of typical landslides. In the research area, which covers more than 71 km2, more than 1200 very small landslides were detected. The majority of landslides were discovered in just several geological units indicating their high susceptibility: Pleistocene silts and sands with clayey interlayers, followed by M2 silty sands and gravels, and M7 sands. Nearly half of the landslides are estimated to be of recent and younger age, while other landslides may be considered as being historical implying a “long tradition” of landslide events in the research area. Preliminary terrain surface roughness analysis also supported the conclusion that the inventory contains landslides of several historical generations which are still detectable. In addition to slides (1123), this research also discovered numerous earthflow processes (143), which are more frequent in the predominantly sandy units. The landslides in this area are largely located on the banks of the gullies and are directly related to the action of water. Regarding that situation and the engineering properties of the encountered geological units, four types of bank instabilities can be differentiated: slides on top of rock masses; slides in firm soil mixtures; landslides in sands; landslides in predominantly coherent soil complexes.

Automatic Extraction Method of Landslide Based on Digital Elevation Model and Digital Orthophoto Map Data Combined in Complex Terrain

“…Optical images are commonly used to identify spatial, spectral, and temporal changes evident on the Earth's surface, such as vegetation clearance, cracks, and inconsistencies in material distribution [29,30]. This method may result in noisy and spectrally heterogeneous images, which causes difficulty in accurately distinguishing landslide areas from the surrounding environment and precisely comparing images across multiple time periods.…”

“…This complexity may impede the analysis in capturing complex or subtle clues related to landslides [31]. Ultimately, optical images cannot acquire information about subsurface deformations, whereas subsurface deformations can indicate the severity of slope failures [30]. Compared with traditional methods, this approach preserves effective spectral and texture information in high-resolution DOMs.…”

“…However, it is more suitable for identifying and extracting disasters in large areas without the need for the weight distribution of influence factors in the case of insufficient training labels [32][33][34]. This procedure considers the significance and representativeness of the samples in relation to terrain and geomorphology knowledge [30,32]. The aim is to reduce labeling costs and enhance training performance.…”

Investigation and Slope Improvement of Landslides on Bodor River Slopes

“…However, it is unstable in moist soil conditions or high water content, making it susceptible to erosion [29]. The silty sandy soil in the river is highly susceptible to landslides [30]. In addition, a slope angle of 50° increases the vulnerability to landslides, referring to Table 2 as previous research states that silty sandy soil with slope angles of 45° and 63.5° has an FS < 1.…”

Remote Sensing and GIS in Landslide Management: An Example from the Kravarsko Area, Croatia

“…One of the first steps in landslide research in a specific area is the development of a reliable landslide inventory [17][18][19]. A reliable landslide inventory of the area of the interest (at the local, regional, or state level) is a basis for successful landslide mitigation processes and assessments of susceptibility, hazards, and risk (which also depend on the other available data) [20][21][22]. On landslide inventory maps, the spatial distribution of landslides is presented with additional information [17,19,23] while, on landslide susceptibility maps, zones prone to landslides are distinguished [17,21,24,25].…”