Articles | Volume 18, issue 6
https://doi.org/10.5194/nhess-18-1567-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-18-1567-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
07 Jun 2018
Research article |
| 07 Jun 2018
Using kites for 3-D mapping of gullies at decimetre-resolution over several square kilometres: a case study on the Kamech catchment, Tunisia
Denis Feurer
CORRESPONDING AUTHOR
LISAH, Univ Montpellier, INRA, IRD, Montpellier SupAgro, Montpellier, France
Olivier Planchon
LISAH, Univ Montpellier, INRA, IRD, Montpellier SupAgro, Montpellier, France
Mohamed Amine El Maaoui
El Manar University, National Engineering School of Tunis, LTSIRS, B.P 37,
1002 Tunis-Belvédère, Tunis, Tunisia
Abir Ben Slimane
Rural Engineering Laboratory, National Research Institute of Rural Engineering,
Water and Forests, INRGREF, Rue Hédi Karray El Menzah IV – B.P 10, Ariana 2080, Tunisia
Mohamed Rached Boussema
El Manar University, National Engineering School of Tunis, LTSIRS, B.P 37,
1002 Tunis-Belvédère, Tunis, Tunisia
Marc Pierrot-Deseilligny
Université Paris-Est, IGN/SR, LOEMI, 73 avenue de Paris, 94165 Saint-Mandé,
France
Damien Raclot
LISAH, Univ Montpellier, INRA, IRD, Montpellier SupAgro, Montpellier, France
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ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 127–134, https://doi.org/10.5194/isprs-annals-V-2-2020-127-2020, https://doi.org/10.5194/isprs-annals-V-2-2020-127-2020, 2020
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2, 185–191, https://doi.org/10.5194/isprs-archives-XLII-2-185-2018, https://doi.org/10.5194/isprs-archives-XLII-2-185-2018, 2018
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Nathalie Rombeek, Jussi Leinonen, and Ulrich Hamann
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Weijie Zou, Yi Zhou, Shixin Wang, Futao Wang, Litao Wang, Qing Zhao, Wenliang Liu, Jinfeng Zhu, Yibing Xiong, Zhenqing Wang, and Gang Qin
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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
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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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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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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.
David A. Bonneau, D. Jean Hutchinson, Paul-Mark DiFrancesco, Melanie Coombs, and Zac Sala
Nat. Hazards Earth Syst. Sci., 19, 2745–2765, https://doi.org/10.5194/nhess-19-2745-2019, https://doi.org/10.5194/nhess-19-2745-2019, 2019
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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.
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.
Maja Kucharczyk and Chris H. Hugenholtz
Nat. Hazards Earth Syst. Sci., 19, 2039–2051, https://doi.org/10.5194/nhess-19-2039-2019, https://doi.org/10.5194/nhess-19-2039-2019, 2019
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We performed pre-disaster 3-D mapping with a drone in downtown Victoria, BC, Canada. This was the first drone mapping mission over a Canadian city approved by Canada’s aviation authority. We were legally constrained to using a specific drone. The goal was to assess the quality of the 3-D map. Results indicate that the spatial accuracies achieved with this drone would allow for sub-meter building collapse detection, but the non-tilting camera was insufficient for mapping buildings in 3-D.
Reza Hassanzadeh, Mehdi Honarmand, Mahdieh Hossienjani Zadeh, and Farzin Naseri
Nat. Hazards Earth Syst. Sci., 19, 1989–2009, https://doi.org/10.5194/nhess-19-1989-2019, https://doi.org/10.5194/nhess-19-1989-2019, 2019
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This paper proposes a new model for evaluating local seismic amplification susceptibility by considering direct characteristics of influencing criteria and dealing with uncertainty of modelling through production of fuzzy membership functions and GIS. This model helps planners and decision makers easily produce local seismic amplification susceptibility to be incorporated in designing development plans of urban areas and to evaluate safety measures of existing infrastructure.
Cited articles
Ben Slimane, A.: Rôle de l'érosion ravinaire dans l'envasement des
retenues collinaires dans la Dorsale tunisienne et le Cap Bon, Phd thesis,
Montpellier SupAgro & INAT, 2013. a
Bults, P.: What's my line?, The Aerial Eye, 4, 6–7, 1998. a
Carrivick, J. L., Smith, M. W., and Quincey, D. J.: Structure from Motion in
the Geosciences, John Wiley & Sons, 2016. a
Colomina, I. and Molina, P.: Unmanned aerial systems for photogrammetry and
remote sensing: A review, ISPRS J. Photogramm., 92, 79–97, 2014. a
Currier, K.: Mapping with strings attached: Kite aerial photography of Durai
Island, Anambas Islands, Indonesia, J. Maps, 11, 589–597, 2015. a
Dandois, J. P. and Ellis, E. C.: Remote sensing of vegetation structure using
computer vision, Remote Sens., 2, 1157–1176, 2010. a
Duffy, J. P. and Anderson, K.: A 21st-century renaissance of kites as platforms
for proximal sensing, Prog. Phys. Geog., 40, 352–361, 2016. a
Eltner, A., Kaiser, A., Castillo, C., Rock, G., Neugirg, F., and Abellán, A.: Image-based
surface reconstruction in geomorphometry – merits, limits and developments, Earth Surf. Dynam.,
4, 359–389, https://doi.org/10.5194/esurf-4-359-2016, 2016. a
Inoubli, N., Raclot, D., Mekki, I., Moussa, R., and Le Bissonnais, Y.: A
spatio-temporal multiscale analysis of runoff and erosion in a Mediterranean
marly catchment, Vadose Zone Journal, 2017. a
Jaud, M., Passot, S., Le Bivic, R., Delacourt, C., Grandjean, P., and
Le Dantec, N.: Assessing the accuracy of high resolution digital surface
models computed by PhotoScan® and MicMac® in
sub-optimal survey conditions, Remote Sens., 8, 465, https://doi.org/10.3390/rs8060465, 2016. a
Jinze, M. and Qingmei, M.: Sediment delivery ratio as used in the computation
of watershed sediment yield, J. Hydrol. (New Zealand), 20, 27–38,
1981. a
Khalili, A. E., Raclot, D., Habaeib, H., and Lamachére, J. M.: Factors and
processes of permanent gully evolution in a Mediterranean marly environment
(Cape Bon, Tunisia), Hydrol. Sci. J., 58, 1519–1531, 2013. a
Lowe, D. G.: Distinctive image features from scale-invariant keypoints,
Int. J. Comput. Vision, 60, 91–110, 2004. a
Marzolff, I., Ries, J. B., and Poesen, J.: Short-term versus medium-term
monitoring for detecting gully-erosion variability in a Mediterranean
environment, Earth Surf. Proc. Land., 36, 1604–1623, 2011. a
Mekki, I.: Analyse et modélisation de la variabilité des flux hydriques
à l'échelle d'un bassin versant cultivé alimentant un lac
collinaire du domaine semi-aride méditerranéen (Oued Kamech, Cap Bon,
Tunisie), Phd thesis, Université des Sciences et Techniques du Languedoc,
2003. a
Mekki, I., Albergel, J., Mechlia, N. B., and Voltz, M.: Assessment of overland
flow variation and blue water production in a farmed semi-arid water
harvesting catchment, Phys. Chem. Earth, 31,
1048–1061, 2006. a
Mosbrucker, A. R., Major, J. J., Spicer, K. R., and Pitlick, J.: Camera system
considerations for geomorphic applications of SfM photogrammetry, Earth
Surf. Proc. Land., 42, 969–986, https://doi.org/10.1002/esp.4066, 2017. a
Murray, J. C., Neal, M. J., and Labrosse, F.: Development and deployment of an
intelligent Kite Aerial Photography Platform (iKAPP) for site surveying and
image acquisition, J. Field Robot., 30, 288–307, 2013. a
Nachtergaele, J. and Poesen, J.: Assessment of soil losses by ephemeral gully
erosion using high-altitude (stereo) aerial photographs, Earth Surf. Proc. Land., 24, 693–706, 1999. a
Oh, P. Y. and Green, B.: A kite and teleoperated vision system for acquiring
aerial images, in: IEEE International Conference on Robotics and Automation,
1, 1404–1409, 2003. a
Orlandini, S., Tarolli, P., Moretti, G., and Dalla Fontana, G.: On the
prediction of channel heads in a complex alpine terrain using gridded
elevation data, Water Resour. Res., 47, W02538, https://doi.org/10.1029/2010WR009648, 2011. a
Passalacqua, P., Do Trung, T., Foufoula-Georgiou, E., Sapiro, G., and Dietrich,
W. E.: A geometric framework for channel network extraction from lidar:
Nonlinear diffusion and geodesic paths, J. Geophys. Res.-Earth, 115, F01002, https://doi.org/10.1029/2009JF001254, 2010. a
Passalacqua, P., Belmont, P., Staley, D. M., Simley, J. D., Arrowsmith, J. R.,
Bode, C. A., Crosby, C., DeLong, S. B., Glenn, N. F., Kelly, S. A., Lague,
D., Sangireddy, H., Schaffrath, K., Tarboton, D. G., Wasklewicz, T., and
Wheaton, J. M.: Analyzing high resolution topography for advancing the
understanding of mass and energy transfer through landscapes: A review,
Earth-Sci. Rev., 148, 174–193, 2015. a
Pierrot-Deseilligny, M. and Paparoditis, N.: A multiresolution and
optimization-based image matching approach: An application to surface
reconstruction from SPOT5-HRS stereo imagery, Archives of Photogrammetry,
Remote Sensing and Spatial Information Sciences, 36, 1/W41, 73–77, 2006. a
Raclot, D. and Albergel, J.: Runoff and water erosion modelling using WEPP on a
Mediterranean cultivated catchment, Phys. Chem. Earth, 31, 1038–1047, 2006. a
Radjou, N. and Prabhu, J.: Frugal Innovation: How to do more with less,
The Economist, 2015. a
Rengers, F. K. and Tucker, G.: Analysis and modeling of gully headcut dynamics,
North American high plains, J. Geophys. Res.-Earth,
119, 983–1003, 2014. a
Smith, M. W., Carrivick, J. L., and Quincey, D. J.: Structure from motion
photogrammetry in physical geography, Prog. Phys. Geogr.,
40, 247–275, 2016. a
Snavely, N., Seitz, S. M., and Szeliski, R.: Photo tourism: exploring photo
collections in 3D, in: ACM transactions on graphics, 25, 835–846,
2006. a
Snavely, N., Seitz, S. M., and Szeliski, R.: Modeling the world from internet
photo collections, Int. J. Comp. Vision, 80, 189–210,
2008. a
Stumpf, A., Malet, J.-P., Allemand, P., Pierrot-Deseilligny, M., and Skupinski,
G.: Ground-based multi-view photogrammetry for the monitoring of landslide
deformation and erosion, Geomorphology, 231, 130–145, 2015. a
Thommeret, N., Bailly, J. S., and Puech, C.: Extraction of thalweg networks from DTMs:
application to badlands, Hydrol. Earth Syst. Sci., 14, 1527–1536, https://doi.org/10.5194/hess-14-1527-2010, 2010. a, b, c
Van Westen, C. J.: Remote sensing and GIS for natural hazards assessment and
disaster risk management, Treatise on geomorphology, 3, 259–298, 2013. a
Vandaele, K., Poesen, J., Govers, G., and van Wesemael, B.: Geomorphic
threshold conditions for ephemeral gully incision, Geomorphology, 16,
161–173, 1996. a
Vaze, J., Teng, J., and Spencer, G.: Impact of DEM accuracy and resolution on
topographic indices, Environ. Modell. Softw., 25, 1086–1098,
2010. a
Verhoeven, G., Taelman, D., and Vermeulen, F.: Computer vision-based orthophoto
mapping of complex archaeological sites: the ancient quarry of Pitaranha
(Portugal-Spain), Archaeometry, 54, 1114–1129, 2012. a
Vericat, D., Brasington, J., Wheaton, J., and Cowie, M.: Accuracy assessment of
aerial photographs acquired using lighter-than-air blimps: low-cost tools for
mapping river corridors, River Res. Appl., 25, 985–1000,
2009. a
Wigmore, O. and Mark, B.: High altitude kite mapping: evaluation of kite aerial
photography (KAP) and structure from motion digital elevation models in the
Peruvian Andes, Int. J. Remote Sens., 1–21, https://doi.org/10.1080/01431161.2017.1387312, 2017. a
Short summary
We present a method for acquiring very-high-resolution images for 3-D mapping of gullies over kilometre-square areas using kites. Kites used in appropriate conditions can be an advantageous alternative to light unmanned aircraft when local regulations or weather conditions hamper their use. We proved that kites can acquire images, allowing for high-quality 3-D coverage of large areas. We automatically detected and mapped gullies from a decimetre kite DEM with 74 % accuracy of the length.
We present a method for acquiring very-high-resolution images for 3-D mapping of gullies over...
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