Articles | Volume 22, issue 10
20 Oct 2022
Research article | 20 Oct 2022
Development of black ice prediction model using GIS-based multi-sensor model validation
Seok Bum Hong et al.
No articles found.
Sang-Guk Yum, Moon-Soo Song, and Manik Das Adhikari
Nat. Hazards Earth Syst. Sci. Discuss.,
Preprint under review for NHESSShort summary
1. Study performed analysis on typhoon-induced Coastal morphodynamics for Mokpo coast. 2. Wetland vegetation was severely impacted by typhoon Soulik. 3. 87.35 % of shoreline transects experienced seaward migration. 4. The result highlighted that sediment resuspension controls the land alteration process over the typhoon period. 5. The land accretion process was dominated during the pre- to post-typhoon period.
Ji-Myong Kim, Sang-Guk Yum, Hyunsoung Park, and Junseo Bae
Nat. Hazards Earth Syst. Sci., 22, 2131–2144,Short summary
Insurance data has been utilized with deep learning techniques to predict natural disaster damage losses in South Korea.
Moon-Soo Song, Hong-Sik Yun, Jae-Joon Lee, and Sang-Guk Yum
Nat. Hazards Earth Syst. Sci. Discuss.,
Manuscript not accepted for further reviewShort summary
In this study, emerging engineering techniques such as machine learning and deep learning technique was applied to predict heavy snowfall prediction in the Korean Peninsula. More specifically, it was observed that the predictive model using the RFR algorithm had the best performance based on a comparison between the observed and predicted data. In addition, it was observed that the performance of the ensemble models (RFR and XGB) was better than that of the single regression models.
Sang-Guk Yum, Hsi-Hsien Wei, and Sung-Hwan Jang
Nat. Hazards Earth Syst. Sci., 21, 2611–2631,Short summary
Developed statistical models to predict the non-exceedance probability of extreme storm surge-induced typhoons. Various probability distribution models were applied to find the best fitting to empirical storm-surge data.
Related subject area
Databases, GIS, Remote Sensing, Early Warning Systems and Monitoring TechnologiesForecasting vegetation condition with a Bayesian auto-regressive distributed lags (BARDL) modelA dynamic hierarchical Bayesian approach for forecasting vegetation conditionUsing a single remote-sensing image to calculate the height of a landslide dam and the maximum volume of a lakeComparison of machine learning techniques for reservoir outflow forecastingEnhancing disaster risk resilience using greenspace in urbanising Quito, EcuadorGridded flood depth estimates from satellite-derived inundationsProbFire: a probabilistic fire early warning system for IndonesiaIndex establishment and capability evaluation of space–air–ground remote sensing cooperation in geohazard emergency responseBrief communication: Monitoring a soft-rock coastal cliff using webcams and strain sensorsMultiscale analysis of surface roughness for the improvement of natural hazard modellingEUNADICS-AV early warning system dedicated to supporting aviation in the case of a crisis from natural airborne hazards and radionuclide cloudsAre sirens effective tools to alert the population in France?UAV survey method to monitor and analyze geological hazards: the case study of the mud volcano of Villaggio Santa Barbara, Caltanissetta (Sicily)Timely prediction potential of landslide early warning systems with multispectral remote sensing: a conceptual approach tested in the Sattelkar, AustriaCHILDA – Czech Historical Landslide DatabaseReview article: Detection of actionable tweets in crisis eventsLong-term magnetic anomalies and their possible relationship to the latest greater Chilean earthquakes in the context of the seismo-electromagnetic theoryHazMapper: a global open-source natural hazard mapping application in Google Earth EngineOpportunities and risks of disaster data from social media: a systematic review of incident informationOnline urban-waterlogging monitoring based on a recurrent neural network for classification of microblogging textPredicting power outages caused by extratropical stormsNear-real-time automated classification of seismic signals of slope failures with continuous random forestsAssessing the accuracy of remotely sensed fire datasets across the southwestern Mediterranean BasinResponses to severe weather warnings and affective decision-makingThe object-specific flood damage database HOWAS 21A spaceborne SAR-based procedure to support the detection of landslidesGIS-based DRASTIC and composite DRASTIC indices for assessing groundwater vulnerability in the Baghin aquifer, Kerman, IranReview article: The spatial dimension in the assessment of urban socio-economic vulnerability related to geohazardsDesign and implementation of a mobile device app for network-based earthquake early warning systems (EEWSs): application to the PRESTo EEWS in southern ItalyCCAF-DB: the Caribbean and Central American active fault databaseEvaluation of a combined drought indicator and its potential for agricultural drought prediction in southern SpainStudy on real-time correction of site amplification factorThree-dimensional rockfall shape back analysis: methods and implicationsEffects of high-resolution geostationary satellite imagery on the predictability of tropical thunderstorms over Southeast AsiaInSAR technique applied to the monitoring of the Qinghai–Tibet RailwayUnderstanding the spatiotemporal development of human settlement in hurricane-prone areas on the US Atlantic and Gulf coasts using nighttime remote sensingPre-disaster mapping with drones: an urban case study in Victoria, British Columbia, CanadaNew approaches to modelling of local seismic amplification susceptibility using direct characteristics of influencing criteria: case study of Bam City, IranSMC-Flood database: a high-resolution press database on flood cases for the Spanish Mediterranean coast (1960–2015)Statistical analysis for satellite-index-based insurance to define damaged pasture thresholdsMonitoring the seasonal dynamics of soil salinization in the Yellow River delta of China using Landsat dataTowards early warning of gravitational slope failure with co-detection of microseismic activity: the case of an active rock glacierDangerous degree forecast of soil loss on highway slopes in mountainous areas of the Yunnan–Guizhou Plateau (China) using the Revised Universal Soil Loss EquationAssessment of geodetic velocities using GPS campaign measurements over long baseline lengthsResponse time to flood events using a social vulnerability index (ReTSVI)Delimitation of flood areas based on a calibrated a DEM and geoprocessing: case study on the Uruguay River, Itaqui, southern BrazilIdentification and classification of urban micro-vulnerabilities in tsunami evacuation routes for the city of Iquique, ChileUsability of aerial video footage for 3-D scene reconstruction and structural damage assessmentUsing kites for 3-D mapping of gullies at decimetre-resolution over several square kilometres: a case study on the Kamech catchment, TunisiaA new approach for land degradation and desertification assessment using geospatial techniques
Edward E. Salakpi, Peter D. Hurley, James M. Muthoka, Adam B. Barrett, Andrew Bowell, Seb Oliver, and Pedram Rowhani
Nat. Hazards Earth Syst. Sci., 22, 2703–2723,Short summary
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
Nat. Hazards Earth Syst. Sci., 22, 2725–2749,Short summary
The impact of drought may vary in a given region depending on whether it is dominated by trees, grasslands, or croplands. The differences in impact can also be the agro-ecological zones within the region. This paper proposes a hierarchical Bayesian model (HBM) for forecasting vegetation condition in spatially diverse areas. Compared to a non-hierarchical model, the HBM proved to be a more natural method for forecasting drought in areas with different land covers and 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,Short summary
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.
Orlando García-Feal, José González-Cao, Diego Fernández-Nóvoa, Gonzalo Astray Dopazo, and Moncho Gómez-Gesteira
Nat. Hazards Earth Syst. Sci. Discuss.,
Revised manuscript accepted for NHESSShort summary
Extreme events have increased in the last decades, having a good estimation of the outflow of a reservoir can be an advantage for water management or early warning systems. This study analyses the efficiency of different machine learning techniques to predict reservoir outflow. The results obtained showed that the proposed models provided a good estimation of the outflow of the reservoirs, improving the results obtained with classical approaches.
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,
Patric Kellermann, Kai Schröter, Annegret H. Thieken, Sören-Nils Haubrock, and Heidi Kreibich
Nat. Hazards Earth Syst. Sci., 20, 2503–2519,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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,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.
Kwonmin Lee, Hye-Sil Kim, and Yong-Sang Choi
Nat. Hazards Earth Syst. Sci., 19, 2241–2248,Short summary
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,Short summary
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,Short summary
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,Short summary
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,Short summary
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.
Salvador Gil-Guirado, Alfredo Pérez-Morales, and Francisco Lopez-Martinez
Nat. Hazards Earth Syst. Sci., 19, 1955–1971,Short summary
In this study the SMC-Flood database for the municipalities of the Mediterranean coast of mainland Spain is presented. This database has enabled the reconstruction of 3008 cases of flooding on a municipal scale between 1960 and 2015. The data analysis reveals a growing trend in the frequency and area affected by flood cases. The main novelty lies in the fact that we have detected a clear latitudinal gradient of growing intensity and severity of flood cases with a north–south direction.
Juan José Martín-Sotoca, Antonio Saa-Requejo, Rubén Moratiel, Nicolas Dalezios, Ioannis Faraslis, and Ana María Tarquis
Nat. Hazards Earth Syst. Sci., 19, 1685–1702,Short summary
Vegetation indices based on satellite images, such as the normalized difference vegetation index (NDVI), have been used for damaged pasture insurance. The occurrence of damage is usually defined by NDVI thresholds mainly based on normal statistics. In this work a pasture area in Spain was delimited by MODIS images. A statistical analysis of NDVI was applied to search for alternative distributions. Results show that generalized extreme value distributions present a better fit than normal ones.
Hongyan Chen, Gengxing Zhao, Yuhuan Li, Danyang Wang, and Ying Ma
Nat. Hazards Earth Syst. Sci., 19, 1499–1508,Short summary
Using Landsat data, the inversion model of soil salt content (SSC) for different seasons was determined in the Kenli District in the Yellow River Delta region of China. The SSC exhibited a gradual increasing trend from the southwest to northeast. The SSC accumulated in spring, decreased in summer, increased in autumn and reached its peak at the the end of winter. The results can provide data for the control of soil salt hazards and utilization of saline–alkali soil.
Jérome Faillettaz, Martin Funk, Jan Beutel, and Andreas Vieli
Nat. Hazards Earth Syst. Sci., 19, 1399–1413,Short summary
We developed a new strategy for real-time early warning of gravity-driven slope failures (such as landslides, rockfalls, glacier break-off, etc.). This method enables us to investigate natural slope stability based on continuous monitoring and interpretation of seismic waves generated by the potential instability. Thanks to a pilot experiment, we detected typical patterns of precursory events prior to slide events, demonstrating the potential of this method for real-word applications.
Yue Li, Shi Qi, Bin Liang, Junming Ma, Baihan Cheng, Cong Ma, Yidan Qiu, and Qinyan Chen
Nat. Hazards Earth Syst. Sci., 19, 757–774,Short summary
This study fully considers the characteristics of expressways in mountain areas. The catchment area is considered a prediction unit. The method of slope division is improved, and a method of improving the parameters in the model is proposed. Comparison and analysis with actual observation data show that the method of soil and water loss prediction adopted in this paper has less error and higher prediction accuracy than other models and can satisfy prediction requirements.
Huseyin Duman and Dogan Ugur Sanli
Nat. Hazards Earth Syst. Sci., 19, 571–582,Short summary
Research has been done to assess the performance of relative positioning over long baseline lengths in determining the accuracy of site velocities from GPS campaign measurements. GPS campaign measurements were generated from the IGS data, and the results were compared with PPP-derived findings. A major outcome of this study is that relative positioning over long baseline lengths produces similar accuracies to PPP. A newly proposed refinement method also improves the available PPP accuracy.
Alvaro Hofflinger, Marcelo A. Somos-Valenzuela, and Arturo Vallejos-Romero
Nat. Hazards Earth Syst. Sci., 19, 251–267,Short summary
In this work, we propose a novel methodology (ReTSVI) to integrate a social vulnerability index into flood hazard methodologies. ReTSVI combines a series of modules that are pieces of information that interact during an evacuation, such as evacuation rate curves, mobilization, inundation models, and social vulnerability indexes, to create an integrated map of the evacuation rate in a given location.
Paulo Victor N. Araújo, Venerando E. Amaro, Robert M. Silva, and Alexandre B. Lopes
Nat. Hazards Earth Syst. Sci., 19, 237–250,Short summary
This paper aims to map flood hazard areas under the influence of the Uruguay River, Itaqui (southern Brazil), using a calibrated digital elevation model (DEM), historic river level data and geoprocessing techniques. Assessment of the areas that can potentially be flooded can help to reduce the negative impact of flood events by supporting the process of land-use planning in areas exposed to flood hazards.
Gonzalo Álvarez, Marco Quiroz, Jorge León, and Rodrigo Cienfuegos
Nat. Hazards Earth Syst. Sci., 18, 2027–2039,Short summary
Evacuation planning has been recognized as one of the best tools for safeguarding the population against tsunami hazards. In this work we develop a novel methodology to identify and classify urban micro-vulnerabilities that may difficult pedestrian evacuation processes resulting from problems in urban design or informal uses of the public space. The correct identification and correction of these issues could make the difference in saving lives when the available time for evacuation is short.
Johnny Cusicanqui, Norman Kerle, and Francesco Nex
Nat. Hazards Earth Syst. Sci., 18, 1583–1598,Short summary
Aerial multi-perspective images can be used for the effective assessment of post-disaster structural damage. Alternatively, rapidly available video data can be processed for the same purpose. However, video quality characteristics are different than those of images taken with still cameras. The use of video data in post-disaster damage assessment has not been demonstrated. Based on a comparative assessment, our findings support the application of video data in post-disaster damage assessment.
Denis Feurer, Olivier Planchon, Mohamed Amine El Maaoui, Abir Ben Slimane, Mohamed Rached Boussema, Marc Pierrot-Deseilligny, and Damien Raclot
Nat. Hazards Earth Syst. Sci., 18, 1567–1582,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.
Masoud Masoudi, Parviz Jokar, and Biswajeet Pradhan
Nat. Hazards Earth Syst. Sci., 18, 1133–1140,Short summary
The paper attempts to create a new technique for assessing the current state of land degradation. Assessment of land degradation is difficult, because it includes a complex process. This assessment, using RS and GIS seems to be more realistic in finding the degree of degradation, because it is more related to its impact on land productivity. It is hoped that this attempt, which is the first attempt of its kind in the world, will be found applicable for other regions.
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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.
This study advances previous models through machine learning and multi-sensor-verified results....