Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps

Arbanas, Snježana Mihalić; Gazibara, Sanja Bernat; Krkač, Martin; Sinčić, Marko; Lukačić, Hrvoje; Jagodnik, Petra; Arbanas, Željko

doi:10.1007/978-3-031-18471-0_16

Cited by 4 publications

(2 citation statements)

References 55 publications

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“…Additionally, slopes could also be pre-emptively cleared of unstable rocks that carry the danger of collapse [2]. Localization of hazardous zones is a primary task for slope management, as it reduces expenses of pedestrian surveys and observations in the field [14]. In addition, pedestrian surveys of such areas are unsafe, and therefore the development of methods for assessing the risks of rockfalls using Earth remote sensing technologies is a very urgent task.…”

Section: Introductionmentioning

confidence: 99%

Combined Methodology for Rockfall Susceptibility Mapping Using UAV Imagery Data

Gantimurova,

Parshin

2023

Remote Sensing

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Gravitational processes on cut slopes located close to infrastructure are a high concern in mountainous regions. There are many techniques for survey, assessment, and prognosis of hazardous exogenous geological processes. The given research describes using UAV data and GIS morphometric analysis for delineation of hazardous rockfall zones and 3D modelling to obtain an enhanced, detailed evaluation of slope characteristics. Besides the slope geomorphometric data, we integrated discontinuity layers, including rock plains orientation and fracture network density. Cloud Compare software 2.12 was utilised for facet extraction. Fracture discontinuity analysis was performed in QGIS using the Network GT plugin. The presented research uses an Analytical Hierarchy Process (AHP) to determine the weight of each contributing factor. GIS overlay of weighted factors is applied for rockfall susceptibility mapping. This integrated approach allows for a more comprehensive GIS-based rockfall susceptibility mapping by considering both the structural characteristics of the outcrop and the geomorphological features of the slope. By combining UAV data, GIS-based morphometric analysis, and discontinuity analysis, we are able to delineate hazardous rockfall zones effectively.

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Section: Introductionmentioning

confidence: 99%

Combined Methodology for Rockfall Susceptibility Mapping Using UAV Imagery Data

Gantimurova,

Parshin

2023

Remote Sensing

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“…Moreover, researching the application of LSMs in spatial planning (Mihalić Arbanas et al, 2023), we qualitatively present derived LSMs in close up views and high resolution to measure the applicability of the used zonation method, i.e. determine visually susceptibility class area distribution.…”

mentioning

confidence: 99%

Comparison of conditioning factors classification criteria in large scale statistically based landslide susceptibility models

Sinčić,

Bernat Gazibara,

Rossi

et al. 2024

Preprint

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Abstract. The large scale landslide susceptibility assessment (LSA) is an important tool for reducing landslide risk through the application of resulting maps in spatial and urban planning. The existing literature more often deals with LSA modelling techniques and the scientific research very rarely focuses on acquiring relevant thematic and landslide data, necessary to achieve reliable results. Therefore, the paper focuses on the crucial step of classifying continuous landslide conditioning factors for susceptibility modelling by presenting an innovative comprehensive analysis that resulted in 54 landslide susceptibility models to test 11 classification criteria (scenarios which vary from stretched values, partially stretched classes, heuristic approach, classification based on studentized contrast and landslide presence, and commonly used classification criteria, such as Natural Neighbor, Quantiles and Geometrical intervals) in combination with five statistical methods. The large scale landslide susceptibility models were derived for small and shallow landslides in the pilot area (21 km2) located in the City of Zagreb (Croatia), which occur mainly in soils and soft rocks. Some of the novelties in LSA are the following: scenarios using stretched landslide conditioning factor values or classification with more than 10 classes prove more reliable; certain statistical methods are more sensitive to the landslide conditioning factor classification criteria than others; all the tested machine learning methods give the best landslide susceptibility model performance using continuously stretched landslide conditioning factors derived from high-resolution input data. The research highlights the importance of qualitative assessments, alongside commonly used quantitative metrics, to verify spatial accuracy and to test the applicability of derived landslide susceptibility maps for spatial planning purposes.

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Application of LAND-SUITE for Landslide Susceptibility Modelling Using Different Mapping Units: A Case Study in Croatia

Bernat Gazibara,

Sinčić,

Rossi

et al. 2023

Progress in Landslide Research and Technology

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LAND-SUITE software was applied to local-scale landslide susceptibility zonation in a study area (20 km2) located in NW Croatia, which is characterised by small and shallow landslides in engineering soils and hard soils-soft rocks. Landslide susceptibility models were prepared using a LiDAR-based landslide inventory, and causal factors derived and/or modified using high-resolution remote sensing data. The landslide susceptibility analysis was carried out using different statistical methods and mapping units. As a result, we obtained ten susceptibility maps, classified into five zones based on modelled landslide probability. The main objective of this paper is to analyse the use of LAND-SUITE for deriving susceptibility zonations, useful to support applications in a spatial planning system on a local scale. One of the most valuable advantage of LAND-SUITE is that the selection of the appropriate causal factor maps can be performed using simple decisions based on multiple analyses, including multicollinearity tables and correlograms. The evaluation of the susceptibility models allowed to conclude that the pixel-based map represents the best option for application in a local-level spatial planning system, although it requires “post-processing” of the susceptibility zones to produce clustered and homogeneous information. LAND-SUITE has proven to be a valuable tool for testing numerous landslide susceptibility hypotheses.

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Landslide Detection and Spatial Prediction: Application of Data and Information from Landslide Maps

Cited by 4 publications

References 55 publications

Combined Methodology for Rockfall Susceptibility Mapping Using UAV Imagery Data

Combined Methodology for Rockfall Susceptibility Mapping Using UAV Imagery Data

Comparison of conditioning factors classification criteria in large scale statistically based landslide susceptibility models

Application of LAND-SUITE for Landslide Susceptibility Modelling Using Different Mapping Units: A Case Study in Croatia

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