Abstract

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).

Highlights

  • Rockfall is a fragmented rock or a block that has detached from a surface slope or cliff by falling, sliding, toppling, bouncing or rolling [1]

  • 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 collected features were synchronised with the existing online database, and the data were directly transferred to the WebGIS

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Summary

Introduction

Rockfall is a fragmented rock or a block that has detached from a surface slope or cliff by falling, sliding, toppling, bouncing or rolling [1]. Rockfall models are useful tools for assessing rockfall risk, as well as the planning of rockfall protection measures in high-risk areas since they can be used to predict rockfall trajectories, distribution and intensity of impacts, and magnitude of rockfall events [4,5,6]. The quality of rockfall risk assessment is directly linked to the available databases of past rockfall events since this information allows for the analysis of spatial distribution of the process, its frequency and magnitude. The most important features that are needed for the determination of spatial distribution, frequency and magnitude of a rockfall event, are the location of the rockfall source (release) area and locations of the corresponding deposits (rock blocks and their volumes) [7,8,9,10,11]. It is crucial to have truthful, accurate and detailed information about past rockfall events

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