Articles | Volume 19, issue 12
https://doi.org/10.5194/nhess-19-2745-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-19-2745-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Dec 2019
Research article |
| 04 Dec 2019
| 04 Dec 2019
Three-dimensional rockfall shape back analysis: methods and implications
David A. Bonneau
CORRESPONDING AUTHOR
Department of Geological Sciences and Geological Engineering –
Queen's University, Kingston, Ontario, Canada, K7L 3N6
D. Jean Hutchinson
Department of Geological Sciences and Geological Engineering –
Queen's University, Kingston, Ontario, Canada, K7L 3N6
Paul-Mark DiFrancesco
Department of Geological Sciences and Geological Engineering –
Queen's University, Kingston, Ontario, Canada, K7L 3N6
Melanie Coombs
Department of Geological Sciences and Geological Engineering –
Queen's University, Kingston, Ontario, Canada, K7L 3N6
Zac Sala
Department of Geological Sciences and Geological Engineering –
Queen's University, Kingston, Ontario, Canada, K7L 3N6
BGC Engineering Inc., Vancouver, British Columbia, Canada, V6Z 0C8
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Rockfalls present a hazard to railways in mountainous terrain. 3-D remote monitoring data can be used to identify events that occurred between data collections. Using a case study from British Columbia, we present a method combining 3-D rockfall event data with spatial rockfall simulations to provide a refined estimate of the frequency of rockfalls presenting a direct hazard to passing trains and railway infrastructure, which is often less than the total number of rockfalls that occurred.
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The work carried out for this study is part of a collaborative research program studying the impact of ground hazards on transportation infrastructure in Canada. The focus of the paper is the testing and application of a new simulation technique which can model the movement of falling rock material. These initial tests show that our simulation technique is capable of reproducing material accumulations from rockfall events which occurred above a section of railway in British Columbia, Canada.
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Jiale Qian, Yunyan Du, Jiawei Yi, Fuyuan Liang, Nan Wang, Ting Ma, and Tao Pei
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Seok Bum Hong, Hong Sik Yun, Sang Guk Yum, Seung Yeop Ryu, In Seong Jeong, and Jisung Kim
Nat. Hazards Earth Syst. Sci., 22, 3435–3459, https://doi.org/10.5194/nhess-22-3435-2022, https://doi.org/10.5194/nhess-22-3435-2022, 2022
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This study advances previous models through machine learning and multi-sensor-verified results. Using spatial and meteorological data from the study area (Suncheon–Wanju Highway in Gurye-gun), the amount and location of black ice were modelled based on system dynamics to predict black ice and then simulated with the geographic information system (m2). Based on the model results, multiple sensors were buried at four selected points in the study area, and the model was compared with sensor data.
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The devastating effects of recurring drought conditions are mostly felt by pastoralists that rely on grass and shrubs as fodder for their animals. Using historical information from precipitation, soil moisture, and vegetation health data, we developed a model that can forecast vegetation condition and the probability of drought occurrence up till a 10-week lead time with an accuracy of 74 %. Our model can be adopted by policymakers and relief agencies for drought early warning and early action.
Edward E. Salakpi, Peter D. Hurley, James M. Muthoka, Andrew Bowell, Seb Oliver, and Pedram Rowhani
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agro-ecological zones.
Weijie Zou, Yi Zhou, Shixin Wang, Futao Wang, Litao Wang, Qing Zhao, Wenliang Liu, Jinfeng Zhu, Yibing Xiong, Zhenqing Wang, and Gang Qin
Nat. Hazards Earth Syst. Sci., 22, 2081–2097, https://doi.org/10.5194/nhess-22-2081-2022, https://doi.org/10.5194/nhess-22-2081-2022, 2022
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Landslide dams are secondary disasters caused by landslides, which can cause great damage to mountains. We have proposed a procedure to calculate the key parameters of these dams that uses only a single remote-sensing image and a pre-landslide DEM combined with landslide theory. The core of this study is a modeling problem. We have found the bridge between the theory of landslide dams and the requirements of disaster relief.
C. Scott Watson, John R. Elliott, Susanna K. Ebmeier, María Antonieta Vásquez, Camilo Zapata, Santiago Bonilla-Bedoya, Paulina Cubillo, Diego Francisco Orbe, Marco Córdova, Jonathan Menoscal, and Elisa Sevilla
Nat. Hazards Earth Syst. Sci., 22, 1699–1721, https://doi.org/10.5194/nhess-22-1699-2022, https://doi.org/10.5194/nhess-22-1699-2022, 2022
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We assess how greenspaces could guide risk-informed planning and reduce disaster risk for the urbanising city of Quito, Ecuador, which experiences earthquake, volcano, landslide, and flood hazards. We use satellite data to evaluate the use of greenspaces as safe spaces following an earthquake. We find disparities regarding access to and availability of greenspaces. The availability of greenspaces that could contribute to community resilience is high; however, many require official designation.
Seth Bryant, Heather McGrath, and Mathieu Boudreault
Nat. Hazards Earth Syst. Sci., 22, 1437–1450, https://doi.org/10.5194/nhess-22-1437-2022, https://doi.org/10.5194/nhess-22-1437-2022, 2022
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The advent of new satellite technologies improves our ability to study floods. While the depth of water at flooded buildings is generally the most important variable for flood researchers, extracting this accurately from satellite data is challenging. The software tool presented here accomplishes this, and tests show the tool is more accurate than competing tools. This achievement unlocks more detailed studies of past floods and improves our ability to plan for and mitigate disasters.
Tadas Nikonovas, Allan Spessa, Stefan H. Doerr, Gareth D. Clay, and Symon Mezbahuddin
Nat. Hazards Earth Syst. Sci., 22, 303–322, https://doi.org/10.5194/nhess-22-303-2022, https://doi.org/10.5194/nhess-22-303-2022, 2022
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Extreme fire episodes in Indonesia emit large amounts of greenhouse gasses and have negative effects on human health in the region. In this study we show that such burning events can be predicted several months in advance in large parts of Indonesia using existing seasonal climate forecasts and forest cover change datasets. A reliable early fire warning system would enable local agencies to prepare and mitigate the worst of the effects.
Yahong Liu and Jin Zhang
Nat. Hazards Earth Syst. Sci., 22, 227–244, https://doi.org/10.5194/nhess-22-227-2022, https://doi.org/10.5194/nhess-22-227-2022, 2022
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Through a comprehensive analysis of the current remote sensing technology resources, this paper establishes the database to realize the unified management of heterogeneous sensor resources and proposes a capability evaluation method of remote sensing cooperative technology in geohazard emergencies, providing a decision-making basis for the establishment of remote sensing cooperative observations in geohazard emergencies.
Diego Guenzi, Danilo Godone, Paolo Allasia, Nunzio Luciano Fazio, Michele Perrotti, and Piernicola Lollino
Nat. Hazards Earth Syst. Sci., 22, 207–212, https://doi.org/10.5194/nhess-22-207-2022, https://doi.org/10.5194/nhess-22-207-2022, 2022
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In the Apulia region (southeastern Italy) we are monitoring a soft-rock coastal cliff using webcams and strain sensors. In this urban and touristic area, coastal recession is extremely rapid and rockfalls are very frequent. In our work we are using low-cost and open-source hardware and software, trying to correlate both meteorological information with measures obtained from crack meters and webcams, aiming to recognize potential precursor signals that could be triggered by instability phenomena.
Natalie Brožová, Tommaso Baggio, Vincenzo D'Agostino, Yves Bühler, and Peter Bebi
Nat. Hazards Earth Syst. Sci., 21, 3539–3562, https://doi.org/10.5194/nhess-21-3539-2021, https://doi.org/10.5194/nhess-21-3539-2021, 2021
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Surface roughness plays a great role in natural hazard processes but is not always well implemented in natural hazard modelling. The results of our study show how surface roughness can be useful in representing vegetation and ground structures, which are currently underrated. By including surface roughness in natural hazard modelling, we could better illustrate the processes and thus improve hazard mapping, which is crucial for infrastructure and settlement planning in mountainous areas.
Hugues Brenot, Nicolas Theys, Lieven Clarisse, Jeroen van Gent, Daniel R. Hurtmans, Sophie Vandenbussche, Nikolaos Papagiannopoulos, Lucia Mona, Timo Virtanen, Andreas Uppstu, Mikhail Sofiev, Luca Bugliaro, Margarita Vázquez-Navarro, Pascal Hedelt, Michelle Maree Parks, Sara Barsotti, Mauro Coltelli, William Moreland, Simona Scollo, Giuseppe Salerno, Delia Arnold-Arias, Marcus Hirtl, Tuomas Peltonen, Juhani Lahtinen, Klaus Sievers, Florian Lipok, Rolf Rüfenacht, Alexander Haefele, Maxime Hervo, Saskia Wagenaar, Wim Som de Cerff, Jos de Laat, Arnoud Apituley, Piet Stammes, Quentin Laffineur, Andy Delcloo, Robertson Lennart, Carl-Herbert Rokitansky, Arturo Vargas, Markus Kerschbaum, Christian Resch, Raimund Zopp, Matthieu Plu, Vincent-Henri Peuch, Michel Van Roozendael, and Gerhard Wotawa
Nat. Hazards Earth Syst. Sci., 21, 3367–3405, https://doi.org/10.5194/nhess-21-3367-2021, https://doi.org/10.5194/nhess-21-3367-2021, 2021
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The purpose of the EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation) prototype early warning system (EWS) is to develop the combined use of harmonised data products from satellite, ground-based and in situ instruments to produce alerts of airborne hazards (volcanic, dust, smoke and radionuclide clouds), satisfying the requirement of aviation air traffic management (ATM) stakeholders (https://cordis.europa.eu/project/id/723986).
Johnny Douvinet, Anna Serra-Llobet, Esteban Bopp, and G. Mathias Kondolf
Nat. Hazards Earth Syst. Sci., 21, 2899–2920, https://doi.org/10.5194/nhess-21-2899-2021, https://doi.org/10.5194/nhess-21-2899-2021, 2021
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This study proposes to combine results of research regarding the spatial inequalities due to the siren coverage, the political dilemma of siren activation, and the social problem of siren awareness and trust for people in France. Surveys were conducted using a range of complementary methods (GIS analysis, statistical analysis, questionnaires, interviews) through different scales. Results show that siren coverage in France is often determined by population density but not risks or disasters.
Fabio Brighenti, Francesco Carnemolla, Danilo Messina, and Giorgio De Guidi
Nat. Hazards Earth Syst. Sci., 21, 2881–2898, https://doi.org/10.5194/nhess-21-2881-2021, https://doi.org/10.5194/nhess-21-2881-2021, 2021
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In this paper we propose a methodology to mitigate hazard in a natural environment in an urbanized context. The deformation of the ground is a precursor of paroxysms in mud volcanoes. Therefore, through the analysis of the deformation supported by a statistical approach, this methodology was tested to reduce the hazard around the mud volcano. In the future, the goal is that this dangerous area will become both a naturalistic heritage and a source of development for the community of the area.
Doris Hermle, Markus Keuschnig, Ingo Hartmeyer, Robert Delleske, and Michael Krautblatter
Nat. Hazards Earth Syst. Sci., 21, 2753–2772, https://doi.org/10.5194/nhess-21-2753-2021, https://doi.org/10.5194/nhess-21-2753-2021, 2021
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Multispectral remote sensing imagery enables landslide detection and monitoring, but its applicability to time-critical early warning is rarely studied. We present a concept to operationalise its use for landslide early warning, aiming to extend lead time. We tested PlanetScope and unmanned aerial system images on a complex mass movement and compared processing times to historic benchmarks. Acquired data are within the forecasting window, indicating the feasibility for landslide early warning.
Michal Bíl, Pavel Raška, Lukáš Dolák, and Jan Kubeček
Nat. Hazards Earth Syst. Sci., 21, 2581–2596, https://doi.org/10.5194/nhess-21-2581-2021, https://doi.org/10.5194/nhess-21-2581-2021, 2021
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The online landslide database CHILDA (Czech Historical Landslide Database) summarises information about landslides which occurred in the area of Czechia (the Czech Republic). The database is freely accessible via the https://childa.cz/ website. It includes 699 records (spanning the period of 1132–1989). Overall, 55 % of all recorded landslide events occurred only within 15 years of the extreme landslide incidence.
Anna Kruspe, Jens Kersten, and Friederike Klan
Nat. Hazards Earth Syst. Sci., 21, 1825–1845, https://doi.org/10.5194/nhess-21-1825-2021, https://doi.org/10.5194/nhess-21-1825-2021, 2021
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Messages on social media can be an important source of information during crisis situations. This article reviews approaches for the reliable detection of informative messages in a flood of data. We demonstrate the varying goals of these approaches and present existing data sets. We then compare approaches based (1) on keyword and location filtering, (2) on crowdsourcing, and (3) on machine learning. We also point out challenges and suggest future research.
Enrique Guillermo Cordaro, Patricio Venegas-Aravena, and David Laroze
Nat. Hazards Earth Syst. Sci., 21, 1785–1806, https://doi.org/10.5194/nhess-21-1785-2021, https://doi.org/10.5194/nhess-21-1785-2021, 2021
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We developed a methodology that generates free externally disturbed magnetic variations in ground magnetometers close to the Chilean convergent margin. Spectral analysis (~ mHz) and magnetic anomalies increased prior to large Chilean earthquakes (Maule 2010, Mw 8.8; Iquique 2014, Mw 8.2; Illapel 2015, Mw 8.3). These findings relate to microcracks within the lithosphere due to stress state changes. This physical evidence should be thought of as a last stage of the earthquake preparation process.
Corey M. Scheip and Karl W. Wegmann
Nat. Hazards Earth Syst. Sci., 21, 1495–1511, https://doi.org/10.5194/nhess-21-1495-2021, https://doi.org/10.5194/nhess-21-1495-2021, 2021
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For many decades, natural disasters have been monitored by trained analysts using multiple satellite images to observe landscape change. This approach is incredibly useful, but our new tool, HazMapper, offers researchers and the scientifically curious public a web-accessible
cloud-based tool to perform similar analysis. We intend for the tool to both be used in scientific research and provide rapid response to global natural disasters like landslides, wildfires, and volcanic eruptions.
Matti Wiegmann, Jens Kersten, Hansi Senaratne, Martin Potthast, Friederike Klan, and Benno Stein
Nat. Hazards Earth Syst. Sci., 21, 1431–1444, https://doi.org/10.5194/nhess-21-1431-2021, https://doi.org/10.5194/nhess-21-1431-2021, 2021
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In this paper, we study when social media is an adequate source to find metadata about incidents that cannot be acquired by traditional means. We identify six major use cases: impact assessment and verification of model predictions, narrative generation, recruiting citizen volunteers, supporting weakly institutionalized areas, narrowing surveillance areas, and reporting triggers for periodical surveillance.
Hui Liu, Ya Hao, Wenhao Zhang, Hanyue Zhang, Fei Gao, and Jinping Tong
Nat. Hazards Earth Syst. Sci., 21, 1179–1194, https://doi.org/10.5194/nhess-21-1179-2021, https://doi.org/10.5194/nhess-21-1179-2021, 2021
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We trained a recurrent neural network model to classify microblogging posts related to urban waterlogging and establish an online monitoring system of urban waterlogging caused by flood disasters. We manually curated more than 4400 waterlogging posts to train the RNN model so that it can precisely identify waterlogging-related posts of Sina Weibo to timely determine urban waterlogging.
Roope Tervo, Ilona Láng, Alexander Jung, and Antti Mäkelä
Nat. Hazards Earth Syst. Sci., 21, 607–627, https://doi.org/10.5194/nhess-21-607-2021, https://doi.org/10.5194/nhess-21-607-2021, 2021
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Predicting the number of power outages caused by extratropical storms is a key challenge for power grid operators. We introduce a novel method to predict the storm severity for the power grid employing ERA5 reanalysis data combined with a forest inventory. The storms are first identified from the data and then classified using several machine-learning methods. While there is plenty of room to improve, the results are already usable, with support vector classifier providing the best performance.
Michaela Wenner, Clément Hibert, Alec van Herwijnen, Lorenz Meier, and Fabian Walter
Nat. Hazards Earth Syst. Sci., 21, 339–361, https://doi.org/10.5194/nhess-21-339-2021, https://doi.org/10.5194/nhess-21-339-2021, 2021
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Mass movements constitute a risk to property and human life. In this study we use machine learning to automatically detect and classify slope failure events using ground vibrations. We explore the influence of non-ideal though commonly encountered conditions: poor network coverage, small number of events, and low signal-to-noise ratios. Our approach enables us to detect the occurrence of rare events of high interest in a large data set of more than a million windowed seismic signals.
Luiz Felipe Galizia, Thomas Curt, Renaud Barbero, and Marcos Rodrigues
Nat. Hazards Earth Syst. Sci., 21, 73–86, https://doi.org/10.5194/nhess-21-73-2021, https://doi.org/10.5194/nhess-21-73-2021, 2021
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This paper aims to provide a quantitative evaluation of three remotely sensed fire datasets which have recently emerged as an important resource to improve our understanding of fire regimes. Our findings suggest that remotely sensed fire datasets can be used to proxy variations in fire activity on monthly and annual timescales; however, caution is advised when drawing information from smaller fires (< 100 ha) across the Mediterranean region.
Philippe Weyrich, Anna Scolobig, Florian Walther, and Anthony Patt
Nat. Hazards Earth Syst. Sci., 20, 2811–2821, https://doi.org/10.5194/nhess-20-2811-2020, https://doi.org/10.5194/nhess-20-2811-2020, 2020
Patric Kellermann, Kai Schröter, Annegret H. Thieken, Sören-Nils Haubrock, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 20, 2503–2519, https://doi.org/10.5194/nhess-20-2503-2020, https://doi.org/10.5194/nhess-20-2503-2020, 2020
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The flood damage database HOWAS 21 contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding. The datasets incorporate various variables of flood hazard, exposure, vulnerability and direct tangible damage at properties from several economic sectors. This paper presents HOWAS 21 and highlights exemplary analyses to demonstrate the use of HOWAS 21 flood damage data.
Giuseppe Esposito, Ivan Marchesini, Alessandro Cesare Mondini, Paola Reichenbach, Mauro Rossi, and Simone Sterlacchini
Nat. Hazards Earth Syst. Sci., 20, 2379–2395, https://doi.org/10.5194/nhess-20-2379-2020, https://doi.org/10.5194/nhess-20-2379-2020, 2020
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In this article, we present an automatic processing chain aimed to support the detection of landslides that induce sharp land cover changes. The chain exploits free software and spaceborne SAR data, allowing the systematic monitoring of wide mountainous regions exposed to mass movements. In the test site, we verified a general accordance between the spatial distribution of seismically induced landslides and the detected land cover changes, demonstrating its potential use in emergency management.
Mohammad Malakootian and Majid Nozari
Nat. Hazards Earth Syst. Sci., 20, 2351–2363, https://doi.org/10.5194/nhess-20-2351-2020, https://doi.org/10.5194/nhess-20-2351-2020, 2020
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The present study estimated the Kerman–Baghin aquifer vulnerability using DRASTIC and composite DRASTIC (CDRASTIC) indices with the aid of geographic information system (GIS) techniques. The aquifer vulnerability maps indicated very similar results, identifying the north-west parts of the aquifer as areas with high to very high vulnerability. According to the results, parts of the studied aquifer have a high vulnerability and require protective measures.
Diana Contreras, Alondra Chamorro, and Sean Wilkinson
Nat. Hazards Earth Syst. Sci., 20, 1663–1687, https://doi.org/10.5194/nhess-20-1663-2020, https://doi.org/10.5194/nhess-20-1663-2020, 2020
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The socio-economic condition of the population determines their vulnerability to earthquakes, tsunamis, volcanic eruptions, landslides, soil erosion and land degradation. This condition is estimated mainly from population censuses. The lack to access to basic services, proximity to hazard zones, poverty and population density highly influence the vulnerability of communities. Mapping the location of this vulnerable population makes it possible to prevent and mitigate their risk.
Simona Colombelli, Francesco Carotenuto, Luca Elia, and Aldo Zollo
Nat. Hazards Earth Syst. Sci., 20, 921–931, https://doi.org/10.5194/nhess-20-921-2020, https://doi.org/10.5194/nhess-20-921-2020, 2020
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We developed a mobile app for Android devices which receives the alerts generated by a network-based early warning system, predicts the expected ground-shaking intensity and the available lead time at the user position, and provides customized messages to inform the user about the proper reaction to the alert. The app represents a powerful tool for informing in real time a wide audience of end users and stakeholders about the potential damaging shaking in the occurrence of an earthquake.
Richard Styron, Julio García-Pelaez, and Marco Pagani
Nat. Hazards Earth Syst. Sci., 20, 831–857, https://doi.org/10.5194/nhess-20-831-2020, https://doi.org/10.5194/nhess-20-831-2020, 2020
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The Caribbean and Central American region is both tectonically active and densely populated, leading to a large population that is exposed to earthquake hazards. Until now, no comprehensive fault data covering the region have been available. We present a new public fault database for Central America and the Caribbean that synthesizes published studies with new mapping from remote sensing to provide fault sources for the CCARA seismic hazard and risk analysis project and to aid future research.
María del Pilar Jiménez-Donaire, Ana Tarquis, and Juan Vicente Giráldez
Nat. Hazards Earth Syst. Sci., 20, 21–33, https://doi.org/10.5194/nhess-20-21-2020, https://doi.org/10.5194/nhess-20-21-2020, 2020
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A new combined drought indicator (CDI) is proposed that integrates rainfall, soil moisture and vegetation dynamics. The performance of this indicator was evaluated against crop damage data from agricultural insurance schemes in five different areas in SW Spain. Results show that this indicator was able to predict important droughts in 2004–2005 and 2011–2012, marked by crop damage of between 70 % and 95 % of the total insured area. This opens important applications for improving insurance schemes.
Quancai Xie, Qiang Ma, Jingfa Zhang, and Haiying Yu
Nat. Hazards Earth Syst. Sci., 19, 2827–2839, https://doi.org/10.5194/nhess-19-2827-2019, https://doi.org/10.5194/nhess-19-2827-2019, 2019
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This paper evaluates a new method for modeling the site amplification factor. Through implementing this method and making simulations for different cases, we find that this method shows better performance than the previous method and JMA report. We better understand the advantages and disadvantages of this method, although there are some problems that need to be considered carefully and solved; it shows good potential to be used in future earthquake early warning systems.
Kwonmin Lee, Hye-Sil Kim, and Yong-Sang Choi
Nat. Hazards Earth Syst. Sci., 19, 2241–2248, https://doi.org/10.5194/nhess-19-2241-2019, https://doi.org/10.5194/nhess-19-2241-2019, 2019
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This study examined the advances in the predictability of thunderstorms using geostationary satellite imageries. Our present results show that by using the latest geostationary satellite data (with a resolution of 2 km and 10 min), thunderstorms can be predicted 90–180 min ahead of their mature state. These data can capture the rapidly growing cloud tops before the cloud moisture falls as precipitation and enable prompt preparation and the mitigation of hazards.
Qingyun Zhang, Yongsheng Li, Jingfa Zhang, and Yi Luo
Nat. Hazards Earth Syst. Sci., 19, 2229–2240, https://doi.org/10.5194/nhess-19-2229-2019, https://doi.org/10.5194/nhess-19-2229-2019, 2019
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Before the opening of the railway, the deformation of the Qinghai–Tibet Railway was very small and considered stable. After opening, the overall stability of the railway section was good. The main deformation areas are concentrated in the areas where railway lines turn and geological disasters are concentrated. In order to ensure the safety of railway operation, it is necessary to carry out long-term time series observation along the Qinghai–Tibet Railway.
Xiao Huang, Cuizhen Wang, and Junyu Lu
Nat. Hazards Earth Syst. Sci., 19, 2141–2155, https://doi.org/10.5194/nhess-19-2141-2019, https://doi.org/10.5194/nhess-19-2141-2019, 2019
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This study examined the spatiotemporal dynamics of nighttime satellite-derived human settlement in response to different levels of hurricane proneness in a period from 1992 to 2013. It confirms the
Snow Belt-to-Sun BeltUS population shift trend. The results also suggest that hurricane-exposed human settlement has grown in extent and area, as more hurricane exposure has experienced a larger increase rate in settlement intensity.
Cited articles
Abbott, B., Bruce, I., Savigny, W., Keegan, T., and Oboni, F.: A Methodology
for the Assessment of Rockfall Hazard Risk along Linear Transportation
Corridors, 8th International Association of Engineering Geology Conference,
A Global View from the Pacific Rim, 21– 25 September 1998, Vancouver, BC, Canada, 1998.
Abellán, A., Oppikofer, T., Jaboyedoff, M., Rosser, N. J., Lim, M., and
Lato, M. J.: Terrestrial laser scanning of rock slope instabilities, Earth
Surf. Proc. Land., 39, 80–97, https://doi.org/10.1002/esp.3493, 2014.
Agisoft LLC: Agisoft PhotoScan User Manual, St. Petersburg, Russia, available at: https://www.agisoft.com/, last access: 29 May 2018.
Benjamin, J.: Regional-scale controls on rockfall occurrence, PhD Thesis,
Durham University, Durham, UK, 2018.
Besl, P. and McKay, N.: A Method for Registration of 3-D Shapes, IEEE T.
Pattern Anal., 14, 239–256, https://doi.org/10.1109/34.121791, 1992.
Blender: Blender – a 3D modelling and rendering package, available
at: http://www.blender.org, last access: 12 July 2018.
Blott, S. J. and Pye, K.: Particle shape: A review and new methods of characterization and classification, Sedimentology, 55, 31–63, https://doi.org/10.1111/j.1365-3091.2007.00892.x, 2008.
Bonneau, D. A. and Hutchinson, D. J.: Applications of Remote Sensing for
Characterizing Debris Channel Processes, in: Landslides: Putting Experience,
Knowledge and Emerging Technologies into Practice., edited by: De Graff, J. V. and Shakoor, A., Association of Environmental & Engineering
Geologists (AEG), Roanoke, USA, 748–759, 2017.
Bonneau, D. A. and Hutchinson, D. J.: The Use of Multi-Scale Dimensionality
Analysis for the Characterization of Debris Distribution Patterns, in:
Geohazards 7 – Engineering Resiliency in a Changing Climate, p. 8, Canmore,
Alberta, Canada, 2018.
Bonneau, D. A. and Hutchinson, D. J.: The use of terrestrial laser scanning
for the characterization of a cliff-talus system in the Thompson River
Valley, British Columbia, Canada, Geomorphology, 327, 598–609,
https://doi.org/10.1016/j.geomorph.2018.11.022, 2019.
Brown, D. A.: Geology of the Lytton Area, British Columbia, BSc Thesis,
Carleton University, Ottawa, Canada, 1981.
Carrea, D., Abellan, A., Derron, M. H., and Jaboyedoff, M.: Automatic
Rockfalls Volume Estimation Based on Terrestrial Laser Scanning Data, in:
Engineering Geology for Society and Territory – Volume 2: Landslide
Processes, edited by: Lollino, G., Giordan, D., Crosta, G. B., Corominas, J., Azzam, R., Wasowski, J., and Sciarra, N., Springer International
Publishing, Cham, Switzerland, 1–2177, 2015.
Cloutier, C., Locat, J., Geertsema, M., Jakob, M., and Schnorbus, M.:
Potential impacts of climate change on landslides occurrence in Canada, in: Slope Safety Preparedness for Impact of Climate Change, edited by: Ho, K., Lacasse, S., and Picarelli, L., CRC Press, CRC Press/Balkema, Leiden, the Netherlands, 71–104, https://doi.org/10.1201/9781315387789-3, 2016.
Dorren, L. K. A.: Rockyfor3D (v5.2) Revealed – Transparent Description of
the Complete 3D Rockfall Model, Geneva, Switzerland, available
at: http://www.ecorisq.org (last access: 27 July 2018), 2016.
Dussauge, C., Grasso, J.-R., and Helmstetter, A.: Statistical analysis of
rockfall volume distributions: Implications for rockfall dynamics, J.
Geophys. Res.-Sol. Ea., 108, 2286, https://doi.org/10.1029/2001JB000650, 2003.
Ester, M., Kriegel, H.-P., Sander, J., and Xu, X.: A Density-Based Algorithm
for Discovering Clusters in Large Spatial Databases with Noise, in: Knowledge
Discovery and Data Mining 1996, Elsevier, Portland, Oregon, USA, 226–231, 1996.
Froude, M. J. and Petley, D. N.: Global fatal landslide occurrence from 2004 to 2016, Nat. Hazards Earth Syst. Sci., 18, 2161–2181, https://doi.org/10.5194/nhess-18-2161-2018, 2018.
Glover, J.: Rock-shape and its role in rockfall dynamics, PhD Thesis, Durham
University, Durham, UK, 2015.
Golub, G. H. and Loan, C. F. V: Matrix Computations, 3rd edn., The John Hopkins University Press, Baltimore, Maryland, USA, 1996.
Guerin, A., Hantz, D., Rossetti, J.-P., and Jaboyedoff, M.: Brief communication “Estimating rockfall frequency in a mountain limestone cliff using terrestrial laser scanner”, Nat. Hazards Earth Syst. Sci. Discuss., 2, 123–135, https://doi.org/10.5194/nhessd-2-123-2014, 2014.
Guzzetti, F., Reichenbach, P., and Ghigi, S.: Rockfall hazard and risk
assessment along a transportation corridor in the Nera valley, central
Italy, Environ. Manage., 34, 191–208, https://doi.org/10.1007/s00267-003-0021-6,
2004.
Harrap, R., Hutchinson, D. J., Sala, Z., Ondercin, M., and DiFrancesco, P. M.: Our
GIS is a Game Engine: Bringing Unity to Spatial Simulation of Rockfalls, in:
GeoComputation 2019, 18–21 September 2019, Queenstown, New Zealand, p. 14, 2019.
Hungr, O., Evans, S. G., and Hazzard, J.: Magnitude and frequency of rock
falls and rock slides along the main transportation corridors of
southwestern British Columbia, Can. Geotech. J., 36, 224–238,
https://doi.org/10.1139/t98-106, 1999.
Hungr, O., Leroueil, S., and Picarelli, L.: The Varnes classification of
landslide types, an update, Landslides, 11, 167–194,
https://doi.org/10.1007/s10346-013-0436-y, 2014.
Jaboyedoff, M., Oppikofer, T., Abellán, A., Derron, M. H., Loye, A.,
Metzger, R., and Pedrazzini, A.: Use of LIDAR in landslide investigations: A
review, Nat. Hazards, 61, 5–28, https://doi.org/10.1007/s11069-010-9634-2, 2012.
Janeras, M., Jara, J. A., Royán, M. J., Vilaplana, J. M., Aguasca, A.,
Fàbregas, X., Gili, J. A., and Buxó, P.: Multi-technique approach to
rockfall monitoring in the Montserrat massif (Catalonia, NE Spain), Eng.
Geol., 219, 4–20, https://doi.org/10.1016/j.enggeo.2016.12.010, 2017.
Jolivet, D., MacGowan, T., McFadden, R. and Steel, M.: Slope Hazard
Assessment using Remote Sensing in White Canyon, Lytton, BC, Kingston, ON, Canada,
2015.
Kobayashi, Y., Harp, E. L., and Kagawa, T.: Simulation of rockfalls triggered by earthquakes, Rock Mech. Rock Eng., 23, 1–20, https://doi.org/10.1007/BF01020418, 1990.
Kromer, R. A., Hutchinson, D. J., Lato, M. J., Gauthier, D., and Edwards, T.:
Identifying rock slope failure precursors using LiDAR for transportation
corridor hazard management, Eng. Geol., 195, 93–103,
https://doi.org/10.1016/j.enggeo.2015.05.012, 2015.
Kromer, R. A., Abellán, A., Hutchinson, D. J., Lato, M., Chanut, M.-A., Dubois, L., and Jaboyedoff, M.: Automated terrestrial laser scanning with near-real-time change detection – monitoring of the Séchilienne landslide, Earth Surf. Dynam., 5, 293–310, https://doi.org/10.5194/esurf-5-293-2017, 2017.
Lague, D., Brodu, N., and Leroux, J.: Accurate 3D comparison of complex
topography with terrestrial laser scanner: Application to the Rangitikei
canyon (N-Z), ISPRS J. Photogramm. Remote Sens., 82, 10–26,
https://doi.org/10.1016/j.isprsjprs.2013.04.009, 2013.
Lato, M., Diederichs, M. S., Hutchinson, D. J., and Harrap, R.: Optimization
of LiDAR scanning and processing for automated structural evaluation of
discontinuities in rockmasses, Int. J. Rock Mech. Min. Sci., 46,
194–199, https://doi.org/10.1016/j.ijrmms.2008.04.007, 2009.
Lato, M. J., Diederichs, M. S., Hutchinson, D. J., and Harrap, R.: Evaluating
roadside rockmasses for rockfall hazards using LiDAR data: Optimizing data
collection and processing protocols, Nat. Hazards, 60, 831–864,
https://doi.org/10.1007/s11069-011-9872-y, 2012.
Lato, M. J., Hutchinson, D. J., Gauthier, D., Edwards, T., and Ondercin, M.:
Comparison of airborne laser scanning, terrestrial laser scanning, and
terrestrial photogrammetry for mapping differential slope change in
mountainous terrain, Can. Geotech. J., 52, 129–140,
https://doi.org/10.1139/cgj-2014-0051, 2015.
Li, Q. and Griffiths, J. G.: Least squares ellipsoid specific fitting, in:
Geometric Modeling and Processing, 2004, 13–15 April 2004, Beijing, China, ISBN 0-7695-2078-2, 335–340,
2004.
Malamud, B. D., Turcotte, D. L., Guzzetti, F., and Reichenbach, P.: Landslide
inventories and their statistical properties, Earth Surf. Proc.
Land., 29, 687–711, https://doi.org/10.1002/esp.1064, 2004.
Mathworks: Matlab, available at: https://www.mathworks.com, last access: 10 April 2018.
Monger, J. W. H.: Structural evolution of the southwestern Intermontane
belt, Ashcroft and Hope map areas, British Columbia, in: Current Research,
Part A, Geological Survey of Canada, Ottawa, Ontario, Canada, 349–358, 1985.
Optech: ILLRIS Summary Specification Sheet, available at: http://www.optech.com/wp-content/uploads/specification_ilris.pdf, last access: 20 May 2014.
Pesci, A., Teza, G., and Bonali, E.: Terrestrial laser scanner resolution:
Numerical simulations and experiments on spatial sampling optimization,
Remote Sens., 3, 167–184, https://doi.org/10.3390/rs3010167, 2011.
Pfeiffer, T. J. and Bowen, T. D.: Computer Simulation of Rockfalls, Environ. Eng. Geosci., xxvi, 135–146, https://doi.org/10.2113/gseegeosci.xxvi.1.135, 1989.
Powers, M. C.: A New Roundness Scale for Sedimentary Particles, SEPM J.
Sediment. Res., 23, 117–119,
https://doi.org/10.1306/D4269567-2B26-11D7-8648000102C1865D, 1953.
Rosser, N., Lim, M., Petley, D., Dunning, S., and Allison, R.: Patterns of
precursory rockfall prior to slope failure, J. Geophys. Res.-Earth,
112, F04014, https://doi.org/10.1029/2006JF000642, 2007.
Sala, Z.: Game-Engine Based Rockfall Modelling: Testing and Application of a
New Rockfall Simulation Tool, MSc Thesis, Queen's University, Kingston, Ontario, Canada, 2018.
Santana, D., Corominas, J., Mavrouli, O., and Garcia-Sellés, D.:
Magnitude-frequency relation for rockfall scars using a Terrestrial Laser
Scanner, Eng. Geol., 144–145, 50–64, https://doi.org/10.1016/j.enggeo.2012.07.001,
2012.
Schneider, P. and Eberly, D.: Geometric Tools for Computer Graphics,
Elsevier, San Francisco, California, USA, 2003.
Smith, M. W., Carrivick, J. L., and Quincey, D. J.: Structure from motion
photogrammetry in physical geography, Prog. Phys. Geogr., 40, 247–275,
https://doi.org/10.1177/0309133315615805, 2016.
Sneed, E. D. and Folk, R. L.: Pebbles in the Lower Colorado River , Texas a
Study in Particle Morphogenesis, J. Geol., 66, 114–150, 1958.
Sturzenegger, M., Stead, D., and Elmo, D.: Terrestrial remote sensing-based
estimation of mean trace length, trace intensity and block size/shape, Eng.
Geol., 119, 96–111, https://doi.org/10.1016/j.enggeo.2011.02.005, 2011.
Telling, J., Lyda, A., Hartzell, P., and Glennie, C.: Review of Earth science
research using terrestrial laser scanning, Earth-Sci. Rev., 169,
35–68, https://doi.org/10.1016/j.earscirev.2017.04.007, 2017.
Teza, G., Atzeni, C., Balzani, M., Galgaro, A., Galvani, G., Genevois, R.,
Luzi, G., Mecatti, D., Noferini, L., Pieraccini, M., Silvano, S., Uccelli,
F., and Zaltron, N.: Ground-based monitoring of high-risk landslides through
joint use of laser scanner and interferometric radar, Int. J. Remote Sens.,
29, 4735–4756, https://doi.org/10.1080/01431160801942227, 2008.
Tonini, M. and Abellán, A.: Rockfall detection from terrestrial LiDAR point
clouds: A clustering approach using R, J. Spat. Inf. Sci., 8, 95–110,
https://doi.org/10.5311/JOSIS.2014.8.123, 2014.
van Veen, M., Hutchinson, D. J., Kromer, R., Lato, M., and Edwards, T.:
Effects of sampling interval on the frequency – magnitude relationship of
rockfalls detected from terrestrial laser scanning using semi-automated
methods, Landslides, 14, 1579–1592, https://doi.org/10.1007/s10346-017-0801-3, 2017.
Volkwein, A., Schellenberg, K., Labiouse, V., Agliardi, F., Berger, F., Bourrier, F., Dorren, L. K. A., Gerber, W., and Jaboyedoff, M.: Rockfall characterisation and structural protection – a review, Nat. Hazards Earth Syst. Sci., 11, 2617–2651, https://doi.org/10.5194/nhess-11-2617-2011, 2011.
Welzl, E.: Smallest enclosing disks (balls and ellipsoids), in: New Results
and New Trends in Computer Science, edited by: Maurer, H., Springer-Verlag, Berlin/Heidelberg, Germany, vol. 555,
359–370, 1991.
Westoby, M. J., Brasington, J., Glasser, N. F., Hambrey, M. J., and Reynolds,
J. M.: “Structure-from-Motion” photogrammetry: A low-cost, effective tool
for geoscience applications, Geomorphology, 179, 300–314,
https://doi.org/10.1016/j.geomorph.2012.08.021, 2012.
Wieczorek, G. F. and Jäger, S.: Triggering mechanisms and depositional
rates of postglacial slope-movement processes in the Yosemite Valley,
California, Geomorphology, 15, 17–31, https://doi.org/10.1016/0169-555X(95)00112-I,
1996.
William, J: Insights into Rockfall from Constant 4D Monitoring, PhD Thesis, Durham University, Durham, UK, 2017.
Williams, J. G., Rosser, N. J., Hardy, R. J., Brain, M. J., and Afana, A. A.: Optimising 4-D surface change detection: an approach for capturing rockfall magnitude–frequency, Earth Surf. Dynam., 6, 101–119, https://doi.org/10.5194/esurf-6-101-2018, 2018.
Short summary
In mountainous regions around the world rockfalls pose a hazard to infrastructure and society. To aid in our understanding and management of these complex hazards, an inventory can be compiled. Three-dimensional remote sensing data can be used to locate the source zones of these events and generate models of areas which detached. We address the way in which the shape of a rockfall object can be measured. The shape of a rockfall has implications for forward modelling of potential runout zones.
In mountainous regions around the world rockfalls pose a hazard to infrastructure and society....
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