Natural Hazards and Disaster Risks Reduction, 2nd Edition

Topic Information

Dear Colleagues,

Given the success of the first edition of the topic “Natural Hazards and Disaster Risks Reduction”, which also led to the publication of three re-print books (https://www.mdpi.com/topics/Natural_Hazards_Disaster_Risks_Reduction), we are pleased to announce its second edition. The physical forces governing Earth’s systems can give rise to abrupt and severe natural events, which come in the form of violent expressions of ordinary environmental processes. Their impact is unevenly distributed on land because of complex continental, regional, and local natural processes that overlap with anthropogenic forcing. The resultant climate variations can directly or indirectly exacerbate these occurrences at different spatial and temporal scales. When such phenomena interact directly with both inhabited areas and societies, different risk scenarios can develop, characterized by a continuous and persistent dynamic or by rapid mutability. From this perspective, natural hazards create potential disasters that can impact anthropic activities, either through the loss of life or injury or through economic loss. The degree of safety in a community equates to the impact of and exposure to these events, and of the level of preparation for them is based on awareness and perception. The social development and spatial growth of human activities by our use of soil and natural resources has further contributed to creating vulnerability, increasing the challenges to conscious societies trying to cope with severe natural processes and their effects. The protection of territory is a key element in the UN 2030 Agenda’s action strategy for sustainable development, and risk reduction is one of the guiding criteria of the 2015–2030 Sendai Framework’s sustainability policy. This topic will collect original studies of different types of natural hazards (extreme climate and weather-related events and geological occurrences such as floods, landslides, subsidence, volcanic eruptions, earthquakes, etc.), vulnerable domains, and exposure to disaster risk. also It will also feature manuscripts whose contents can help to mitigate risks. Among them, technical interventions and operational methodologies for implementing risk-reduction strategies, such as plans, protocols, working procedures, early warning systems, and other innovations in the sector; elements that combine modern concepts with consolidated realities of the past are also to be included. Papers on state-of-the-art techniques are welcome, especially those in the following three operating areas: spaceborne, aerial, and terrestrial activities. Numerical and experimental investigations for basic or applied research and representative case studies are also welcome, as are interdisciplinary and multidisciplinary approaches, which we think add additional value in progressing the field of responsible and sustainable risk mitigation.

Dr. Stefano Morelli
Dr. Veronica Pazzi
Dr. Mirko Francioni
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
GeoHazards geohazards	1.6	2.2	2020	19 Days	CHF 1000	Submit
Land land	3.2	5.9	2012	16.9 Days	CHF 2600	Submit
Remote Sensing remotesensing	4.1	8.6	2009	23.9 Days	CHF 2700	Submit
Sustainability sustainability	3.3	7.7	2009	19.7 Days	CHF 2400	Submit
Water water	3.0	6.0	2009	17.5 Days	CHF 2600	Submit

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Published Papers (12 papers)

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22 pages, 5381 KiB  

Open AccessArticle

Evaluation of Landslide Risk Using the WoE and IV Methods: A Case Study in the Zipaquirá–Pacho Road Corridor

by Sandra Velazco, Álvaro Rodríguez, Martín Riascos, Fernando Nieto and Dayana Granados

GeoHazards 2025, 6(2), 27; https://doi.org/10.3390/geohazards6020027 - 4 Jun 2025

Viewed by 528

Abstract

This study develops a landslide susceptibility zoning map for the Zipaquirá–Pacho road corridor in Cundinamarca, an area prone to frequent landslides. Two statistical methods—Weight of Evidence (WoE) and Information Value (IV)—were used alongside various causal factors to generate the map using GIS software [...] Read more.

This study develops a landslide susceptibility zoning map for the Zipaquirá–Pacho road corridor in Cundinamarca, an area prone to frequent landslides. Two statistical methods—Weight of Evidence (WoE) and Information Value (IV)—were used alongside various causal factors to generate the map using GIS software (ArcGIS Pro 3.5.0 software.). A landslide inventory with 101 points was compiled through fieldwork and Google Earth image analysis. Of these, 70% were used to build the models, while the remaining 30% were reserved for validation, ensuring spatial representativeness. The resulting susceptibility maps classified the area into five categories: “very high”, “high”, “moderate”, “low”, and “very low.” For WoE, 19.62% of the area was classified as “very high” and 19.71% as “high”, while for IV, the respective values were 17.57% and 26.55%. Notably, 88% of the identified landslides occurred in “high” and “very high” zones. Model validation using the AUC (Area Under Curve) metric yielded an efficiency of 81%, confirming the reliability of both methods for landslide prediction. The study’s findings are essential for supporting mitigation strategies and serve as valuable input for local authorities and stakeholders involved in risk management and infrastructure planning. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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23 pages, 5192 KiB  

Open AccessArticle

Different Sensitivities of Earthquake-Induced Water Level Responses and the Influencing Factors in Fault Zones: Insights from the Dachuan-Shuangshi Fault

by Ju Zhang, Hongbiao Gu, Deyang Zhao, Xuelian Rui, Xiaoming Zhang and Xiansi Huang

Water 2025, 17(11), 1568; https://doi.org/10.3390/w17111568 - 23 May 2025

Viewed by 352

Abstract

The earthquake-induced water level responses in the fault zone may be distinctly different, even when the underground wells are very close. How to qualitatively and quantitatively analyze the differences and controlling factors of the groundwater response to earthquakes in the fracture zone is [...] Read more.

The earthquake-induced water level responses in the fault zone may be distinctly different, even when the underground wells are very close. How to qualitatively and quantitatively analyze the differences and controlling factors of the groundwater response to earthquakes in the fracture zone is a hot topic in seismic hydrogeology. This study utilizes three adjacent groundwater monitoring wells, located across distinct structural domains of the Dachuan-Shuangshi Fault, to systematically investigate the different sensitivities of earthquake-induced water level responses and their main influencing factors. The statistical results reveal that monitoring wells located on opposing fault blocks demonstrate higher co-seismic sensitivity compared to the well situated within the fault fracture zone. The water level co-seismic responses are governed by multiple controlling factors, rather than being dominated by individual parameters. Therefore, we employed random forest to quantitatively assess the importance of influencing factors related to hydraulic parameters, aquifer confinement, fault architecture, tidal characteristics, and barometric efficiency. The results showed that hydraulic properties and aquifer confinement are the primary factors influencing the differential sensitivity of water level co-seismic responses. In contrast, the influence of barometric efficiency on water level co-seismic responses is relatively minor. These findings provide critical insights into the understanding of the mechanism and characteristics of seismic hydrological responses in fault zones and provide support for optimizing the placement of groundwater monitoring in seismotectonic environments. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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23 pages, 11864 KiB  

Open AccessArticle

Utilizing Remote Sensing and Random Forests to Identify Optimal Land Use Scenarios and Address the Increase in Landslide Susceptibility

by Aditya Nugraha Putra, Jaenudin, Novandi Rizky Prasetya, Michelle Talisia Sugiarto, Sudarto, Cahyo Prayogo, Febrian Maritimo and Fandy Tri Admajaya

Sustainability 2025, 17(9), 4227; https://doi.org/10.3390/su17094227 - 7 May 2025

Cited by 1 | Viewed by 606

Abstract

Massive land use changes in Indonesia driven by deforestation, agricultural expansion, and urbanization have significantly increased landslide susceptibility in upper watersheds. This study focuses on the Sumber Brantas and Kali Konto sub-watersheds where rapid land conversion has destabilized slopes and disrupted ecological balance. [...] Read more.

Massive land use changes in Indonesia driven by deforestation, agricultural expansion, and urbanization have significantly increased landslide susceptibility in upper watersheds. This study focuses on the Sumber Brantas and Kali Konto sub-watersheds where rapid land conversion has destabilized slopes and disrupted ecological balance. By integrating remote sensing, Cellular Automata-Markov (CA-Markov), and Random Forest (RF) models, the research aims to identify optimal land use scenarios for mitigating landslide hazards. Three scenarios were analyzed: business as usual (BAU), land capability classification (LCC), and regional spatial planning (RSP) using 400 field-validated landslide data points alongside 22 topographic, geological, environmental, and anthropogenic parameters. Land use analysis from 2017 to 2022 revealed a 1% decline in natural forest cover, which corresponded to a 1% increase in high and very high landslide hazard areas. From 2017 to 2022, landslide risk increased as the “High” category rose from 33.95% to 37.59% and “Very High” from 10.24% to 12.18%; under BAU 2025, they reached 40.89% and 12.48%, while RSP and LCC reduced the “High” category to 44.12% and 34.44%, respectively. These findings highlight the critical role of integrating geospatial analysis and machine learning in regional planning to promote sustainable land use, reduce landslide hazards, and enhance watershed resilience with high model accuracy (>81%). Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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29 pages, 9362 KiB  

Open AccessArticle

Natural Disaster Risk Assessment in Countries Along the Maritime Silk Road

by Chen Xu, Juanle Wang, Jingxuan Liu and Huairui Wang

Sustainability 2025, 17(7), 3219; https://doi.org/10.3390/su17073219 - 4 Apr 2025

Viewed by 491

Abstract

The 21st‑century Maritime Silk Road initiative highlights the importance of oceans as hubs for resources, ecology, and trade, yet a comprehensive understanding of marine natural disaster risks within this region remains limited. This study focused on 30 countries along the Maritime Silk Road [...] Read more.

The 21st‑century Maritime Silk Road initiative highlights the importance of oceans as hubs for resources, ecology, and trade, yet a comprehensive understanding of marine natural disaster risks within this region remains limited. This study focused on 30 countries along the Maritime Silk Road and developed a multi-hazard natural disaster risk assessment framework tailored for large-scale regional evaluation. It goes beyond single-factor or single-disaster assessments to enhance disaster resilience and support effective disaster response strategies. The framework integrates 65 indicators across four dimensions: disaster-causing factors, disaster-conceiving environments, disaster-bearing bodies, and disaster reduction capacities. It employs five single-indicator evaluation models alongside a combination assessment method based on maximum deviations to evaluate national-scale natural disaster risks. Results reveal spatial consistency in risk evaluations and capture the exposure and sensitivity of 30 countries to different hazards. South Asia exhibits higher seismic risks, while Saudi Arabia consistently receives the lowest risk. Tropical countries like Vietnam and the Philippines face significant storm risks. Drought hazard risk is higher in the Middle East and East Africa, while it is lower in Brunei, Indonesia, and Malaysia. Flood risks are notably higher in Bangladesh, while Iran and Tanzania consistently receive lower risk ratings. Overall, South Asia exhibits higher multi-hazard risks, with medium-to-low risks along the Mediterranean and Southeast Asia. These findings provide technical support for disaster risk reduction by identifying high-risk areas, prioritising resource allocation, and strengthening disaster reduction strategies. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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18 pages, 1912 KiB  

Open AccessArticle

Content Analysis of Disaster Risk Reduction in Secondary School Geography Textbooks in China and the United States: Promoting Disaster Resilience through Geography Education

by Hongbo Sun, Fangjing Song, Xin Ai and Yushan Duan

Sustainability 2024, 16(21), 9321; https://doi.org/10.3390/su16219321 - 26 Oct 2024

Cited by 2 | Viewed by 2190

Abstract

Geography education plays an important role in the promotion of disaster resilience; however, the relationship between geography education and disaster resilience has failed to attract systematic attention in China and the United States (US). This study compares the contents regarding disaster risk reduction [...] Read more.

Geography education plays an important role in the promotion of disaster resilience; however, the relationship between geography education and disaster resilience has failed to attract systematic attention in China and the United States (US). This study compares the contents regarding disaster risk reduction in secondary school geography textbooks in China and the US to explore the contributions of geography education to promoting disaster resilience. These textbooks are analyzed using content analysis based on the Sendai Framework with four actions. This study finds that geography textbooks in China and the US include disaster risk reduction content; however, the contents are unevenly distributed, with “understanding disaster risk” and “enhancing disaster preparedness” accounting for a higher proportion, whereas “strengthening disaster risk governance” and “investing in disaster risk management to enhance resilience” account for a lower proportion. The results indicate that geography education plays an important role in enhancing disaster resilience and can strengthen students’ understanding and preparedness for disaster risks. Meanwhile, this study points out the shortcomings in current disaster risk reduction education and provides a reference for improving educational practice and policy formulation. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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20 pages, 1893 KiB  

Open AccessArticle

Numerical Modeling of Tsunamis Generated by Subaerial, Partially Submerged, and Submarine Landslides

by Tomoyuki Takabatake and Ryosei Takemoto

GeoHazards 2024, 5(4), 1152-1171; https://doi.org/10.3390/geohazards5040054 - 21 Oct 2024

Viewed by 1695

Abstract

Using the existing two-dimensional experimental data and Open-source Fields Operation and Manipulation (OpenFOAM) software, this study performs a comprehensive comparative analysis of three types of landslide-generated tsunamis (subaerial, partially submerged, and submarine). The primary objective was to assess whether numerical simulations can accurately [...] Read more.

Using the existing two-dimensional experimental data and Open-source Fields Operation and Manipulation (OpenFOAM) software, this study performs a comprehensive comparative analysis of three types of landslide-generated tsunamis (subaerial, partially submerged, and submarine). The primary objective was to assess whether numerical simulations can accurately reproduce the experimental results of each type and to compare the predictive equations of the tsunami amplitudes derived from experimental and simulated data. The mesh size and dynamic viscosity parameters were initially optimized for a specific partially submerged landslide tsunami scenario and then applied across a broader range of experimental scenarios. Most of the simulated wave amplitudes remained within the 50% error margin, although significant discrepancies were observed between landslide types. When focusing on the crest amplitude of the first wave, the simulations of subaerial landslides least deviated from the experimental data, with a mean absolute percentage error of approximately 20%, versus approximately 40% for the partially submerged and submarine landslides. The predictive equations derived from the simulations closely matched those from the experimental data, confirming that OpenFOAM can effectively capture complex landslide–tsunami dynamics. Nonetheless, variations in the coefficients related to slope angles highlight the need for further calibration to enhance the simulation fidelity. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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17 pages, 7111 KiB  

Open AccessArticle

Landslide Displacement Prediction Using Kernel Extreme Learning Machine with Harris Hawk Optimization Based on Variational Mode Decomposition

by Chenhui Wang, Gaocong Lin, Cuiqiong Zhou, Wei Guo and Qingjia Meng

Land 2024, 13(10), 1724; https://doi.org/10.3390/land13101724 - 21 Oct 2024

Viewed by 909

Abstract

Displacement deformation prediction is critical for landslide disaster monitoring, as a good landslide displacement prediction system helps reduce property losses and casualties. Landslides in the Three Gorges Reservoir Area (TGRA) are affected by precipitation and fluctuations in reservoir water level, and displacement deformation [...] Read more.

Displacement deformation prediction is critical for landslide disaster monitoring, as a good landslide displacement prediction system helps reduce property losses and casualties. Landslides in the Three Gorges Reservoir Area (TGRA) are affected by precipitation and fluctuations in reservoir water level, and displacement deformation shows a step-like curve. Landslide displacement in TGRA is related to its geology and is affected by external factors. Hence, this study proposes a novel landslide displacement prediction model based on variational mode decomposition (VMD) and a Harris Hawk optimized kernel extreme learning machine (HHO-KELM). Specifically, VMD decomposes the measured displacement into trend, periodic, and random components. Then, the influencing factors are also decomposed into periodic and random components. The feature data, with periodic and random data, are input into the training set, and the trend, periodic, and random term components are predicted by HHO-KELM, respectively. Finally, the total predicted displacement is calculated by summing the predicted values of the three components. The accuracy and effectiveness of the prediction model are tested on the Shuizhuyuan landslide in the TGRA, with the results demonstrating that the new model provides satisfactory prediction accuracy without complex parameter settings. Therefore, under the premise of VMD effectively decomposing displacement data, combined with the global optimization ability of the HHO heuristic algorithm and the fast-learning ability of KELM, HHO-KELM can be used for displacement prediction of step-like landslides in the TGRA. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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20 pages, 10746 KiB  

Open AccessEssay

An Investigation into the Susceptibility to Landslides Using Integrated Learning and Bayesian Optimization: A Case Study of Xichang City

by Fucheng Xing, Ning Li, Boju Zhao, Han Xiang and Yutao Chen

Sustainability 2024, 16(20), 9085; https://doi.org/10.3390/su16209085 - 20 Oct 2024

Cited by 4 | Viewed by 1372

Abstract

In the middle southern section of the Freshwater River–Small River Fault system, Xichang City, Daliang Prefecture, Sichuan Province, is situated in the junction between the Anning River Fault and the Zemu River Fault. There has been a risk of increased activity in the [...] Read more.

In the middle southern section of the Freshwater River–Small River Fault system, Xichang City, Daliang Prefecture, Sichuan Province, is situated in the junction between the Anning River Fault and the Zemu River Fault. There has been a risk of increased activity in the fault zone in recent years, and landslide susceptibility evaluation for the area can effectively reduce the risk of disaster occurrence. Using integrated learning and Bayesian hyperparameter optimization, 265 landslides in Xichang City were used as samples in this study. Thirteen influencing factors were chosen to assess landslide susceptibility, and the BO-XGBoost, BO-LightGBM, and BO-RF models were evaluated using precision, recall, F1, accuracy, and AUC curves. The findings indicated that after removing the terrain relief evaluation factor, the four most significant factors associated with landslide susceptibility were NDVI, distance from faults, slope, and distance from rivers. The study demonstrates that the AUC value of the BO-XGBoost model in the study area is 0.8677, demonstrating a better generalization ability and higher prediction accuracy than the BO-LightGBM and BO-RF models. After Bayesian optimization of hyperparameters, the model offers a significant improvement in prediction accuracy. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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19 pages, 21202 KiB  

Open AccessArticle

Distribution Characteristics and Genesis Mechanism of Ground Fissures in Three Northern Counties of the North China Plain

by Chao Xue, Mingdong Zang, Zhongjian Zhang, Guoxiang Yang, Nengxiong Xu, Feiyong Wang, Cheng Hong, Guoqing Li and Fujiang Wang

Sustainability 2024, 16(18), 8027; https://doi.org/10.3390/su16188027 - 13 Sep 2024

Viewed by 1225

Abstract

The North China Plain is among the regions most afflicted by ground fissure disasters in China. Recent urbanization has accelerated ground fissure activity in the three counties of the northern North China Plain, posing significant threats to both the natural environment and socioeconomic [...] Read more.

The North China Plain is among the regions most afflicted by ground fissure disasters in China. Recent urbanization has accelerated ground fissure activity in the three counties of the northern North China Plain, posing significant threats to both the natural environment and socioeconomic sustainability. Despite the increased attention, a lack of comprehensive understanding persists due to delayed recognition and limited research. This study conducted field visits and geological surveys across 43 villages and 80 sites to elucidate the spatial distribution patterns of ground fissures in the aforementioned counties. By integrating these findings with regional geological data, we formulated a causative model to explain ground fissure formation. Our analysis reveals a concentration of ground fissures near the Niuxi and Rongxi faults, with the former exhibiting the most extensive distribution. The primary manifestations of ground fissures include linear cracks and patch-shaped collapse pits, predominantly oriented in east-west and north-south directions, indicating tensile failure with minimal vertical displacement. Various factors contribute to ground fissure development, including fault activity, ancient river channel distribution, bedrock undulations, rainfall, and ground settlement. Fault activity establishes a concealed fracture system in shallow geotechnical layers, laying the groundwork for ground fissure formation. Additionally, the distribution of ancient river channels and bedrock undulations modifies regional stress fields, further facilitating ground fissure emergence. Rainfall and differential ground settlement serve as triggering mechanisms, exposing ground fissures at the surface. This research offers new insights into the causes of ground fissures in the northern North China Plain, providing crucial scientific evidence for sustaining both the natural environment and the socio-economic stability of the region. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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24 pages, 10977 KiB  

Open AccessArticle

Examining the Controls on the Spatial Distribution of Landslides Triggered by the 2008 Wenchuan Ms 8.0 Earthquake, China, Using Methods of Spatial Point Pattern Analysis

by Guangshun Bai, Xuemei Yang, Guangxin Bai, Zhigang Kong, Jieyong Zhu and Shitao Zhang

Sustainability 2024, 16(16), 6974; https://doi.org/10.3390/su16166974 - 14 Aug 2024

Viewed by 1275

Abstract

Landslide risk management contributes to the sustainable development of the region. Understanding the spatial controls on the distribution of landslides triggered by earthquakes (EqTLs) is difficult in terms of the prediction and risk assessment of EqTLs. In this study, landslides are regarded as [...] Read more.

Landslide risk management contributes to the sustainable development of the region. Understanding the spatial controls on the distribution of landslides triggered by earthquakes (EqTLs) is difficult in terms of the prediction and risk assessment of EqTLs. In this study, landslides are regarded as a spatial point pattern to test the controls on the spatial distribution of landslides and model the landslide density prediction. Taking more than 190,000 landslides triggered by the 2008 Wenchuan Ms 8.0 earthquake (WcEqTLs) as the research object, the relative density estimation, Kolmogorov–Smirnov testing based on cumulative distribution, receiver operating characteristic curve (ROC) analysis, and Poisson density modeling are comprehensively applied to quantitatively determine and discuss the different control effects of seven factors representing earthquakes, geology, and topography. The distance to the surface ruptures (dSR) and the distance to the epicenter (dEp) show significant and strong control effects, which are far stronger than the other five factors. Using only the dSR, dEp, engineering geological rock group (Eg), and the range, a particularly effective Poisson model of landslide density is constructed, whose area under the ROC (AUC) reaches 0.9244 and whose very high-density (VHD) zones can contain 50% of landslides and only comprise 3.9% of the study areas. This research not only deepens our understanding of the spatial distribution of WcEqTLs but also provides new technical methods for such investigation and analysis. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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32 pages, 31386 KiB  

Open AccessEssay

Street Community-Level Urban Flood Risk Assessment Based on Numerical Simulation

by Cailin Li, Yue Wang, Baoyun Guo, Yihui Lu and Na Sun

Sustainability 2024, 16(16), 6716; https://doi.org/10.3390/su16166716 - 6 Aug 2024

Cited by 3 | Viewed by 2200

Abstract

Urban waterlogging is a serious urban disaster, which brings huge losses to the social economy and environment of the city. As an important means of urban rainfall inundation analysis, numerical simulation plays an important role in promoting the risk assessment of urban waterlogging. [...] Read more.

Urban waterlogging is a serious urban disaster, which brings huge losses to the social economy and environment of the city. As an important means of urban rainfall inundation analysis, numerical simulation plays an important role in promoting the risk assessment of urban waterlogging. Scientific and accurate assessment of waterlogging disaster losses is of scientific significance for the formulation of disaster prevention and mitigation measures and the guidance of post-disaster recovery and reconstruction. In this study, the SCS-CN hydrological model and GIS coupling numerical simulation method were used to simulate the inundation of urban waterlogging under four different rainfall return periods and to realize the visualization of the inundation range and waterlogging depth in Zhengzhou. At the same time, based on the numerical simulation results, the building is used as the basic assessment unit to construct a refined assessment framework for urban waterlogging risk at the street community level based on hazard, exposure, and vulnerability analysis. The refined risk assessment results have an important reference value for optimizing the working ideas of waterlogging control and providing a reference for local management departments to effectively deal with waterlogging disasters. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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17 pages, 25206 KiB  

Open AccessArticle

The Use of an Unmanned Aerial Vehicle (UAV) for First-Failure Landslide Detection

by Michele Mercuri, Deborah Biondino, Mariantonietta Ciurleo, Gino Cofone, Massimo Conforti, Giovanni Gullà, Maria Carmela Stellato and Luigi Borrelli

GeoHazards 2024, 5(3), 683-699; https://doi.org/10.3390/geohazards5030035 - 12 Jul 2024

Cited by 3 | Viewed by 1749

Abstract

The use of unmanned aerial vehicles (UAVs) can significantly assist landslide detection and characterization in different geological contexts at a detailed scale. This study investigated the role of UAVs in detecting a first-failure landslide occurring in Calabria, South Italy, and involving weathered granitoid [...] Read more.

The use of unmanned aerial vehicles (UAVs) can significantly assist landslide detection and characterization in different geological contexts at a detailed scale. This study investigated the role of UAVs in detecting a first-failure landslide occurring in Calabria, South Italy, and involving weathered granitoid rocks. After the landslide event, which caused the interruption of State Road 107, a UAV flight was carried out to identify landslide boundaries and morphological features in areas where there are problems of safe access. The landslide was classified as flow-type, with a total length of 240 m, a maximum width of 70 m, and a maximum depth of about 6.5 m. The comparison of the DTMs generated from UAV data with previously available LIDAR data indicated significant topographic changes across the landslide area. A minimum negative value of −6.3 m suggested material removal at the landslide source area. An approximate value of −2 m in the transportation area signified bed erosion and displacement of material as the landslide moved downslope. A maximum positive value of 4.2 m was found in the deposition area. The landslide volume was estimated to be about 6000 m³. These findings demonstrated the effectiveness of UAVs for landslide detection, showing their potentiality as valuable tools in planning further studies for a detailed landslide characterization and for defining the most appropriate risk mitigation measures. Full article

(This article belongs to the Topic Natural Hazards and Disaster Risks Reduction, 2nd Edition)

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