Articles | Volume 17, issue 7
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Direct local building inundation depth determination in 3-D point clouds generated from user-generated flood images
GIScience, Department of Geography, Heidelberg University, 69120 Heidelberg, Germany
GIScience, Department of Geography, Heidelberg University, 69120 Heidelberg, Germany
GIScience, Department of Geography, Heidelberg University, 69120 Heidelberg, Germany
Heidelberg Center for the Environment (HCE), Heidelberg University, 69120 Heidelberg, Germany
No articles found.
Lukas Winiwarter, Katharina Anders, Daniel Czerwonka-Schröder, and Bernhard Höfle
Earth Surf. Dynam., 11, 593–613,Short summary
We present a method to extract surface change information from 4D time series of topographic point clouds recorded with a terrestrial laser scanner. The method uses sensor information to spatially and temporally smooth the data, reducing uncertainties. The Kalman filter used for the temporal smoothing also allows us to interpolate over data gaps or extrapolate into the future. Clustering areas where change histories are similar allows us to identify processes that may have the same causes.
Lea Hartl, Thomas Zieher, Magnus Bremer, Martin Stocker-Waldhuber, Vivien Zahs, Bernhard Höfle, Christoph Klug, and Alessandro Cicoira
Earth Surf. Dynam., 11, 117–147,Short summary
The rock glacier in Äußeres Hochebenkar (Austria) moved faster in 2021–2022 than it has in about 70 years of monitoring. It is currently destabilizing. Using a combination of different data types and methods, we show that there have been two cycles of destabilization at Hochebenkar and provide a detailed analysis of velocity and surface changes. Because our time series are very long and show repeated destabilization, this helps us better understand the processes of rock glacier destabilization.
D. Hulskemper, K. Anders, J. A. Á. Antolínez, M. Kuschnerus, B. Höfle, and R. Lindenbergh
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-2-W2-2022, 53–60,
Hannah Weiser, Jannika Schäfer, Lukas Winiwarter, Nina Krašovec, Fabian E. Fassnacht, and Bernhard Höfle
Earth Syst. Sci. Data, 14, 2989–3012,Short summary
3D point clouds, acquired by laser scanning, allow us to retrieve information about forest structure and individual tree properties. We conducted airborne, UAV-borne and terrestrial laser scanning in German mixed forests, resulting in overlapping point clouds with different characteristics. From these, we generated a comprehensive database of individual tree point clouds and corresponding tree metrics. Our dataset may serve as a benchmark dataset for algorithms in forestry research.
K. Anders, L. Winiwarter, D. Schröder, and B. Höfle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 973–980,
V. Zahs, L. Winiwarter, K. Anders, M. Bremer, M. Rutzinger, M. Potůčková, and B. Höfle
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B2-2022, 1109–1116,
L. Winiwarter, K. Anders, D. Schröder, and B. Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 79–86,
K. Anders, L. Winiwarter, H. Mara, R. C. Lindenbergh, S. E. Vos, and B. Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2021, 137–144,
Veit Ulrich, Jack G. Williams, Vivien Zahs, Katharina Anders, Stefan Hecht, and Bernhard Höfle
Earth Surf. Dynam., 9, 19–28,Short summary
In this work, we use 3D point clouds to detect topographic changes across the surface of a rock glacier. These changes are presented as the relative contribution of surface change during a 3-week period to the annual surface change. By comparing these different time periods and looking at change in different directions, we provide estimates showing that different directions of surface change are dominant at different times of the year. This demonstrates the benefit of frequent monitoring.
M. Rutzinger, K. Anders, M. Bremer, B. Höfle, R. Lindenbergh, S. Oude Elberink, F. Pirotti, M. Scaioni, and T. Zieher
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B5-2020, 243–250,
L. Winiwarter, K. Anders, D. Wujanz, and B. Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2020, 789–796,
K. Anders, R. C. Lindenbergh, S. E. Vos, H. Mara, S. de Vries, and B. Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 317–324,
A. Kumar, K. Anders, L Winiwarter, and B. Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 373–380,
S. Crommelinck, B. Höfle, M. N. Koeva, M. Y. Yang, and G. Vosselman
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2, 81–88,
M. Scaioni, B. Höfle, A. P. Baungarten Kersting, L. Barazzetti, M. Previtali, and D. Wujanz
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1503–1510,
M. Hämmerle, N. Lukač, K.-C. Chen, Zs. Koma, C.-K. Wang, K. Anders, and B. Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W4, 59–65,
Sabrina Marx, Katharina Anders, Sofia Antonova, Inga Beck, Julia Boike, Philip Marsh, Moritz Langer, and Bernhard Höfle
Earth Surf. Dynam. Discuss.,
Revised manuscript has not been submittedShort summary
Global climate warming causes permafrost to warm and thaw, and, consequently, to release the carbon into the atmosphere. Terrestrial laser scanning is evaluated and current methods are extended in the context of monitoring subsidence in Arctic permafrost regions. The extracted information is important to gain a deeper understanding of permafrost-related subsidence processes and provides highly accurate ground-truth data which is necessary for further developing area-wide monitoring methods.
S. Bechtold and B. Höfle
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-3, 161–168,
Related subject area
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Vipasana Sharma, Sushil Kumar, and Rama Sushil
Nat. Hazards Earth Syst. Sci., 23, 2523–2530,Short summary
Snow avalanches are a natural hazard that can cause danger to human lives. This threat can be reduced by accurate prediction of the danger levels. The development of mathematical models based on past data and present conditions can help to improve the accuracy of prediction. This research aims to develop a neural-network-based model for correlating complex relationships between the meteorological variables and the profile variables.
Xabier Blanch, Marta Guinau, Anette Eltner, and Antonio Abellan
Nat. Hazards Earth Syst. Sci. Discuss.,
Revised manuscript accepted for NHESSShort summary
We present a cost-effective photogrammetric systems for high-resolution rockfall monitoring. The paper outlines the components, assembly, and programming codes required to build these systems. The systems utilize prime cameras to generate 3D models, offering comparable performance to LiDAR for change detection monitoring. Real-world applications highlight their potential in geohazards monitoring, enabling accurate detection of pre-failure deformation and rockfalls with a high temporal resolution.
Guillermo Tamburini-Beliveau, Sebastián Balbarani, and Oriol Monserrat
Nat. Hazards Earth Syst. Sci., 23, 1987–1999,Short summary
Landslides and ground deformation associated with the construction of a hydropower mega dam in the Santa Cruz River in Argentine Patagonia have been monitored using radar and optical satellite data, together with the analysis of technical reports. This allowed us to assess the integrity of the construction, providing a new and independent dataset. We have been able to identify ground deformation trends that put the construction works at risk.
Christian Werthmann, Marta Sapena, Marlene Kühnl, John Singer, Carolina Garcia, Bettina Menschik, Heike Schäfer, Sebastian Schröck, Lisa Seiler, Kurosch Thuro, and Hannes Taubenböck
Nat. Hazards Earth Syst. Sci. Discuss.,
Revised manuscript under review for NHESSShort summary
Early Warning Systems (EWS) promise to decrease the vulnerability of self-constructed (informal) settlements threatened by landslides. A living lab sought to develop an integrated EWS in a landslide exposed neighborhood in Medellín. Findings indicate that technical aspects can be manageable, lesser social and political dynamics. A resilient EWS for informal settlements has to achieve sufficient social and technical redundancy to maintain basic functionality in a reduced support scenario.
Adrian Wicki, Peter Lehmann, Christian Hauck, and Manfred Stähli
Nat. Hazards Earth Syst. Sci., 23, 1059–1077,Short summary
Soil wetness measurements are used for shallow landslide prediction; however, existing sites are often located in flat terrain. Here, we assessed the ability of monitoring sites at flat locations to detect critically saturated conditions compared to if they were situated at a landslide-prone location. We found that differences exist but that both sites could equally well distinguish critical from non-critical conditions for shallow landslide triggering if relative changes are considered.
Anirudh Rao, Jungkyo Jung, Vitor Silva, Giuseppe Molinario, and Sang-Ho Yun
Nat. Hazards Earth Syst. Sci., 23, 789–807,Short summary
This article presents a framework for semi-automated building damage assessment due to earthquakes from remote-sensing data and other supplementary datasets including high-resolution building inventories, while also leveraging recent advances in machine-learning algorithms. For three out of the four recent earthquakes studied, the machine-learning framework is able to identify over 50 % or nearly half of the damaged buildings successfully.
Jan Freihardt and Othmar Frey
Nat. Hazards Earth Syst. Sci., 23, 751–770,Short summary
In Bangladesh, riverbank erosion occurs every year during the monsoon and affects thousands of households. Information on locations and extent of past erosion can help anticipate where erosion might occur in the upcoming monsoon season and to take preventive measures. In our study, we show how time series of radar satellite imagery can be used to retrieve information on past erosion events shortly after the monsoon season using a novel interactive online tool based on the Google Earth Engine.
Jiale Qian, Yunyan Du, Jiawei Yi, Fuyuan Liang, Nan Wang, Ting Ma, and Tao Pei
Nat. Hazards Earth Syst. Sci., 23, 317–328,Short summary
Human activities across China show a similar trend in response to rains. However, urban resilience varies significantly by region. The northwestern arid region and the central underdeveloped areas are very fragile, and even low-intensity rains can trigger significant human activity anomalies. By contrast, even high-intensity rains might not affect residents in the southeast.
Orlando García-Feal, José González-Cao, Diego Fernández-Nóvoa, Gonzalo Astray Dopazo, and Moncho Gómez-Gesteira
Nat. Hazards Earth Syst. Sci., 22, 3859–3874,Short summary
Extreme events have increased in the last few decades; having a good estimation of the outflow of a reservoir can be an advantage for water management or early warning systems. This study analyzes 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.
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,Short summary
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.
Adriaan L. van Natijne, Thom A. Bogaard, Thomas Zieher, Jan Pfeiffer, and Roderik C. Lindenbergh
Landslides are one of the major weather related geohazards. To assess their potential impact and design mitigation solutions, a detailed understanding of the slope is required. We tested if use of machine learning, combined with satellite remote sensing data, would allow us to forecast deformation. Our results on the Vögelsberg landslide, a deep-seated landslide near Innsbruck, Austria, show that the formulation of such machine learning system is not as straightforward as often hoped for.
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.
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.
Abdullah, A. F., Rahman, A. A., and Vojinovic, Z.: LiDAR filtering algorithms for urban flood application: Review on current algorithms and filters test, in: ISPRS Archives (XXXVIII, Part3/W8), edited by: Bretar, F., Pierrot-Deseilligny, M., and Vosselman, G., Laser scanning 2009, Paris, France, 1–2 September 2009, 30–36, 2009.
Albuquerque, J., Herfort, B., and Eckle, M.: The Tasks of the Crowd: A Typology of Tasks in Geographic Information Crowdsourcing and a Case Study in Humanitarian Mapping, Remote Sensing, 8, 859, https://doi.org/10.3390/RS8100859, 2016.
Bates, P. D., Marks, K. J., and Horritt, M. S.: Optimal use of high-resolution topographic data in flood inundation models, Hydrol. Process., 17, 537–557, https://doi.org/10.1002/hyp.1113, 2003.
Besl, P. J. and McKay, N. D.: A method for registration of 3-D shapes, IEEE Trans. Pattern Anal. Mach. Intell., 14, 239–256, https://doi.org/10.1109/34.121791, 1992.
Blanc, J., Hall, J. W., Roche, N., Dawson, R. J., Cesses, Y., Burton, A., and Kilsby, C. G.: Enhanced efficiency of pluvial flood risk estimation in urban areas using spatial-temporal rainfall simulations, J. Flood Risk Manage., 5, 143–152, https://doi.org/10.1111/j.1753-318X.2012.01135.x, 2012.
Bruinink, M., Chandarr, A., Rudinac, M., van Overloop, P.-J., and Jonker, P.: Portable, automatic water level estimation using mobile phone cameras, in: 14th IAPR International Conference on Machine Vision Applications (MVA), Tokyo, Japan, 18–22 May, 426–429, 2015.
Chen, J., Hill, A. A., and Urbano, L. D.: A GIS-based model for urban flood inundation, J. Hydrol., 373, 184–192, https://doi.org/10.1016/j.jhydrol.2009.04.021, 2009.
Chen, Y. and Medioni, G.: Object modelling by registration of multiple range images, Image and Vision Comput., 10, 145–155, https://doi.org/10.1016/0262-8856(92)90066-c, 1992.
CRED – Centre for Research on the Epidemiology of Disasters: EM-DAT Disaster Trends: The International Disaster Database, available at: http://www.emdat.be/disaster_trends/index.html, last access: 11 September 2016.
Douglas, I., Garvin, S., Lawson, N., Richards, J., Tippett, J., and White, I.: Urban pluvial flooding: A qualitative case study of cause, effect and nonstructural mitigation, J. Flood Risk Manage., 3, 112–125, https://doi.org/10.1111/j.1753-318X.2010.01061.x, 2010.
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.
Fazeli, H. R., Nor Said, M., Amerudin, S., and Abd Rahman, M. Z.: A Study of Volunteered Geographic Information (VGI) Assessment Methods for Flood Hazard Mapping: A Review, Jurnal Teknologi, 75, 127–134, https://doi.org/10.11113/jt.v75.5281, 2015.
Fohringer, J., Dransch, D., Kreibich, H., and Schröter, K.: Social media as an information source for rapid flood inundation mapping, Nat. Hazards Earth Syst. Sci., 15, 2725–2738, https://doi.org/10.5194/nhess-15-2725-2015, 2015.
Furukawa, Y. and Ponce, J.: Patch-based Multi-view Stereo Software: Documentation – (PMVS - Version 2):, available at: http://www.di.ens.fr/pmvs/documentation.html, last access: 21 August 2016.
Goodchild, M. F.: Citizens as sensors: The world of volunteered geography, GeoJournal, 69, 211–221, https://doi.org/10.1007/s10708-007-9111-y, 2007.
Hammond, M. J., Chen, A. S., Djordjević, S., Butler, D., and Mark, O.: Urban flood impact assessment: A state-of-the-art review, Urban Water J., 12, 14–29, https://doi.org/10.1080/1573062X.2013.857421, 2013.
Iervolino, P., Guida, R., Iodice, A., and Riccio, D.: Flooding Water Depth Estimation With High-Resolution SAR, IEEE Trans. Geosci. Remote Sensing, 53, 2295–2307, https://doi.org/10.1109/TGRS.2014.2358501, 2015.
Klonner, C., Marx, S., Usón, T., Porto de Albuquerque, J., and Höfle, B.: Volunteered Geographic Information in Natural Hazard Analysis: A Systematic Literature Review of Current Approaches with a Focus on Preparedness and Mitigation, ISPRS International Journal of Geo-Information, 5, 103, https://doi.org/10.3390/ijgi5070103, 2016.
Kraus, K., Karel, W., Briese, C., and Mandlburger, G.: Local accuracy measures for digital terrain models, Photogramm. Rec., 21, 342–354, https://doi.org/10.1111/j.1477-9730.2006.00400.x, 2006.
Lo, S.-W., Wu, J.-H., Lin, F.-P., and Hsu, C.-H.: Visual Sensing for Urban Flood Monitoring, Sensors, 15, 20006–20029, https://doi.org/10.3390/s150820006, 2015.
LUBW – Landesanstalt für Umwelt, Messungen und Naturschutz Baden-Württemberg: Hochwasser-Vorhersage-Zentrale Baden-Württemberg, available at: http://www.hvz.baden-wuerttemberg.de/, last access: 21 September 2016.
Maksimović, Č., Prodanović, D., Boonya-Aroonnet, S., Leitão, J. P., Djordjević, S., and Allitt, R.: Overland flow and pathway analysis for modelling of urban pluvial flooding, J. Hydraul. Res., 47, 512–523, https://doi.org/10.1080/00221686.2009.9522027, 2009.
Marx, S., Hämmerle, M., Klonner, C., and Höfle, B.: 3D Participatory Sensing with Low-Cost Mobile Devices for Crop Height Assessment – A Comparison with Terrestrial Laser Scanning Data, PloS one, 11, e0152839, https://doi.org/10.1371/journal.pone.0152839, 2016.
Mason, D. C., Speck, R., Devereux, B., Schumann, G.-P., Neal, J. C., and Bates, P. D.: Flood Detection in Urban Areas Using TerraSAR-X, IEEE Trans. Geosci. Remote Sensing, 48, 882–894, https://doi.org/10.1109/TGRS.2009.2029236, 2010.
Mason, D. C., Giustarini, L., Garcia-Pintado, J., and Cloke, H. L.: Detection of flooded urban areas in high resolution Synthetic Aperture Radar images using double scattering, Int. J. Appl. Earth Obs., 28, 150–159, https://doi.org/10.1016/j.jag.2013.12.002, 2014.
Matgen, P., Schumann, G., Henry, J.-B., Hoffmann, L., and Pfister, L.: Integration of SAR-derived river inundation areas, high-precision topographic data and a river flow model toward near real-time flood management, Int. J. Applied Earth Obs., 9, 247–263, https://doi.org/10.1016/j.jag.2006.03.003, 2007.
McDougall, K. and Temple-Watts, P.: The use of lidar and volunteered geographic information to map flood extentx and inundation, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., I-4, 251–256, https://doi.org/10.5194/isprsannals-I-4-251-2012, 2012.
Meesuk, V., Vojinovic, Z., Mynett, A. E., and Abdullah, A. F.: Urban flood modelling combining top-view LiDAR data with ground-view SfM observations, Adv. Water Res., 75, 105–117, https://doi.org/10.1016/j.advwatres.2014.11.008, 2015.
Merkuryeva, G., Merkuryev, Y., Sokolov, B. V., Potryasaev, S., Zelentsov, V. A., and Lektauers, A.: Advanced river flood monitoring, modelling and forecasting, J. Comput. Sci., 10, 77–85, https://doi.org/10.1016/j.jocs.2014.10.004, 2015.
Narayana, R. K., Lekshmy, V. M., Rao, S., and Sasidhar, K.: A Novel Approach to Urban Flood Monitoring Using Computer Vision, in: 5th Computing, Communication and Networking (ICCCNT), Hefei, China, 11–13 July 2014.
Price, R. K. and Vojinovic, Z.: Urban flood disaster management, Urban Water J., 5, 259–276, https://doi.org/10.1080/15730620802099721, 2008.
Pu, S. and Vosselman, G.: Automatic extraction of building features from terrestrial laserscanning, in: Proceedings of the ISPRS Commission V Symposium, edited by: Maas, H.-G. and Schneider, D., Image Engineering and Vision Metrology, Dresden, Germany, 25–27 September 2006.
Riegl: VZ-400 data sheet, available at: http://riegl.com/uploads/tx_pxpriegldownloads/10_DataSheet_VZ-400 2014-09-19.pdf, last access: 12 September 2016.
Rosnell, T. and Honkavaara, E.: Point Cloud Generation from Aerial Image Data Acquired by a Quadrocopter Type Micro Unmanned Aerial Vehicle and a Digital Still Camera, Sensors, 12, 453–480, https://doi.org/10.3390/s120100453, 2012.
Schumann, G., Matgen, P., Cutler, M., Black, A., Hoffmann, L., and Pfister, L.: Comparison of remotely sensed water stages from LiDAR, topographic contours and SRTM, ISPRS Journal of Photogrammetry and Remote Sensing, 63, 283–296, https://doi.org/10.1016/j.isprsjprs.2007.09.004, 2008.
Schumann, G. J.-P., Neal, J. C., Mason, D. C., and Bates, P. D.: The accuracy of sequential aerial photography and SAR data for observing urban flood dynamics, a case study of the UK summer 2007 floods, Remote Sens. Environ., 115, 2536–2546, https://doi.org/10.1016/j.rse.2011.04.039, 2011.
Serna, A., Marcotegui, B., and Hernández, J.: Segmentation of Façades from Urban 3D Point Clouds Using Geometrical and Morphological Attribute-Based Operators, ISPRS International Journal of Geo-Information, 5, 6, https://doi.org/10.3390/ijgi5010006, 2016.
Shaad, K., Ninsalam, Y., Padawangi, R., and Burlando, P.: Towards high resolution and cost-effective terrain mapping for urban hydrodynamic modelling in densely settled river-corridors, Sustainable Cities and Society, 20, 168–179, https://doi.org/10.1016/j.scs.2015.09.005, 2016.
Smith, M. W., Carrivick, J. L., Hooke, J., and Kirkby, M. J.: Reconstructing flash flood magnitudes using “Structure-from-Motion”: A rapid assessment tool, J. Hydrol., 519, 1914–1927, https://doi.org/10.1016/j.jhydrol.2014.09.078, 2014.
Stefanidis, A., Crooks, A., and Radzikowski, J.: Harvesting ambient geospatial information from social media feeds, GeoJournal, 78, 319–338, https://doi.org/10.1007/s10708-011-9438-2, 2013.
Thieken, A. H.: Hochwasserschutz in Deutschland: Neue Modelle zur Abschätzung von Hochwasserschäden, Ökologisches Wirtschaften, 2008, 30–34, 2008.
Triglav-Čekada, M. and Radovan, D.: Using volunteered geographical information to map the November 2012 floods in Slovenia, Nat. Hazards Earth Syst. Sci., 13, 2753–2762, https://doi.org/10.5194/nhess-13-2753-2013, 2013.
Xiao, J., Fang, T., Tan, P., Zhao, P., Ofek, E., and Quan, L.: Image-based façade modeling, ACM Transactions on Graphics, 27, https://doi.org/10.1145/1457515.1409114, 2008.
Zevenbergen, C., Veerbeek, W., Gersonius, B., and van Herk, S.: Challenges in urban flood management: Travelling across spatial and temporal scales, J. Flood Risk Manage., 1, 81–88, https://doi.org/10.1111/j.1753-318X.2008.00010.x, 2008.
This study provides a new method for flood documentation based on user-generated flood images. We demonstrate how flood elevation and building inundation depth can be derived from photographs by means of 3-D reconstruction of the scene. With an accuracy of 0.13 m ± 0.10 m, the derived building inundation depth can be used to facilitate damage assessment.
This study provides a new method for flood documentation based on user-generated flood images....