Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
8.3
4.2
Journals
Remote Sensing
Special Issues
Remote Sensing Makes it Possible: Prediction and Evaluation of Natural...
remotesensing-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Remote Sensing Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Remote Sensing Makes it Possible: Prediction and Evaluation of Natural Hazards

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Earth Observation for Emergency Management".

Deadline for manuscript submissions: 15 August 2024 | Viewed by 4670

Special Issue Editors

Prof. Dr. Zhongtai He

E-Mail Website
Guest Editor
Institute of Geology, China Earthquake Administration, Beijing 100029, China
Interests: seismic disasters prevention; structural geomorphology; earthquake seismology; photogrammetry and remote sensing; earthquake emergency response
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wenliang Jiang

E-Mail Website
Guest Editor
National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
Interests: comprehensive remote sensing observation technology; remote sensing of active faults and tectonic landforms; visible remote sensing; InSAR and LiDAR technology; earthquake and geological hazards investigation; emergency observation technology of natural disasters
Dr. Dong Li

E-Mail Website
Guest Editor
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Interests: LiDAR data processing and application; simultaneous localization and mapping; aerial photogrammetry
Dr. Erick Mas

E-Mail Website
Guest Editor
International Research Institute of Disaster Science, Tohoku University, Sendai 980-8572, Japan
Interests: multi-agent systems and agent-based simulation; tsunami simulation; evacuation simulation; remote sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Disasters have always accompanied human society. The progress of modern civilization has made populations and wealth more concentrated, which is more likely to produce significant losses, secondary disasters, and even chain effects in the face of major disasters. For example, the earthquake and tsunami disaster in Japan on March 11, 2011, caused a large number of casualties as well as property losses and led to secondary disasters, such as nuclear power plant leakage. Disasters have become a key factor threatening the sustainable development of humankind. Remote sensing can obtain global observation data from multi-band, multi-time, and all-weather angles and has the ability of global observation, which is irreplaceable in disaster monitoring. In recent years, the spatial resolution of remote sensing has been rapidly improved, the recognition accuracy has been gradually enhanced, and the time of the repeated observation of ground objects has been continuously shortened. Remote sensing technology has been widely used in the monitoring, assessment, and early warning of disasters. Remote sensing technology is mainly used in earthquakes, landslides, droughts, climate change, and other disasters.

Furthermore, remote sensing data processing methods are the research hotspot because it poses various challenges. Remote sensing technology provides strong technical support for predicting and evaluating disasters. The deep coupling of remote sensing coordination monitoring and emergency response technology systems can significantly reduce the impact of disasters on human beings. We encourage the contribution of remote sensing technology to predicting and evaluating disasters, such as earthquakes, tsunamis, typhoons, rainstorms, hazes, sandstorms, droughts, forest and grassland fires, snow disasters, and floods.

Prof. Dr. Zhongtai He
Prof. Dr. Wenliang Jiang
Dr. Dong Li
Dr. Erick Mas
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • natural hazards
  • remote sensing
  • earthquake hazards
  • geological disaster
  • floods and droughts
  • forest and grassland fires
  • meteorological disaster
  • agricultural disaster
  • emergency and rescue
  • prediction and evaluation

Published Papers (5 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Other

23 pages, 20141 KiB  
Article
Spatial Variations of Late Quaternary Slip Rates along the Ganzi–Xianshuihe Fault Zone in the Eastern Tibet
by Kai Sun, Chuanyou Li, Mingjian Liang, Xinnan Li, Quanxing Luo, Guangxue Ren, Feipeng Huang and Junjie Li
Remote Sens. 2024, 16(14), 2612; https://doi.org/10.3390/rs16142612 - 17 Jul 2024
Viewed by 244
Abstract
The Ganzi–Xianshuihe Fault Zone is a large-scale sinistral strike-slip fault zone on the eastern Tibet. As the boundary fault zone of the Bayankala Block and the Chuandian Block, it controls the clockwise rotation of the southeastern Tibet. However, there is still controversy regarding [...] Read more.
The Ganzi–Xianshuihe Fault Zone is a large-scale sinistral strike-slip fault zone on the eastern Tibet. As the boundary fault zone of the Bayankala Block and the Chuandian Block, it controls the clockwise rotation of the southeastern Tibet. However, there is still controversy regarding the activity changes between fault zones. Therefore, accurately determining the slip rates of faults in the area is crucial for characterizing regional plate motions and assessing associated seismic hazards. We focused on studying four fault segments near the Ganzi–Xianshuihe Fault Zone, including the Manigango, Ganzi, Luhuo, and Daofu segments. In each segment, we selected typical sinistral piercing points and carried out Unmanned Aerial Vehicle (UAV) photogrammetry to obtain high-resolution terrain data. We utilized LaDiCaoz_V2.2 and GlobalMapper software (LaDiCaoz_V2.2 and Global Mapper v17.0) to measure the offsets, together with optically stimulated luminescence (OSL) dating, to constrain the timing of fault activity. The estimated slip rates for the Manigango, Ganzi, Luhuo, and Daofu segments are as follows: 9.2 ± 0.75 mm/yr, 9.59 ± 1.7 mm/yr, 4.23 ± 0.66 mm/yr, and 7.69 ± 0.76 mm/yr, respectively. Integrating previous results with slip rates estimated in this study, our analysis suggests the slip rate of the Ganzi–Xianshuihe Fault Zone is around 8–10 mm/year, exhibiting a consistent slip rate from northwest to southeast. This reflects the overall coordination of the movement on the eastern Tibet, with the strike-slip fault zone only controlling the direction of movement. Full article
(This article belongs to the Special Issue Remote Sensing Makes it Possible: Prediction and Evaluation of Natural Hazards)
►▼ Show Figures

Figure 1

20 pages, 14793 KiB  
Article
Comprehensive Study on the 143 A.D. West Gangu Earthquake in the West Qinling Area, Northeastern Margin of Tibetan Plateau
by Ruihuan Su, Daoyang Yuan, Hong Xie, Aiguo Wang, Yameng Wen, Jinchao Yu, Yanwen Chen, Hongqiang Li, Hao Sun and Lijun Zhang
Remote Sens. 2024, 16(12), 2109; https://doi.org/10.3390/rs16122109 - 11 Jun 2024
Viewed by 482
Abstract
The 143 A.D. west Gangu earthquake is documented to have occurred in the West Qinling area, which is located on the northeastern margin of the Tibetan Plateau. Initial limited historical records suggest the earthquake took place along the West Qinling fault (WQLF) in [...] Read more.
The 143 A.D. west Gangu earthquake is documented to have occurred in the West Qinling area, which is located on the northeastern margin of the Tibetan Plateau. Initial limited historical records suggest the earthquake took place along the West Qinling fault (WQLF) in the western region of Gangu County. However, the absence of corresponding geological and geomorphological evidence has posed a considerable challenge in accurately quantifying parameters such as the precise location, magnitude, and seismogenic fault segment in earlier investigations. In this study, a comprehensive examination of multiple residual surface rupture zones within the macroseismic zone of this earthquake enabled the determination of the seismogenic structure, magnitude, and rupture zone scale through diverse methodologies, which include field geological investigations, chronology testing, Unmanned Aerial Vehicle (UAV) aerial surveying, and interpretation of landslides along the fault zone. The results reveal that the seismogenic structure of this seismic event is associated with the Zhangxian fault segment of the WQLF, also marked by a dense distribution of large landslides from Zhangxian to Yuanyangzhen. The epicenter was identified at the eastern end of the Zhangxian fault segment of the WQLF. Furthermore, the magnitude of the 143 A.D. west Gangu earthquake is estimated to be approximately Ms 7–7.3, with the residual surface rupture zone intermittently extending over about 22 km and a maximum horizontal dislocation along the rupture zone of 2.8 ± 0.5 m. This detailed investigation contributes foundational insights for further evaluating the seismic risk across various segments of the WQLF. Full article
(This article belongs to the Special Issue Remote Sensing Makes it Possible: Prediction and Evaluation of Natural Hazards)
►▼ Show Figures

Graphical abstract

25 pages, 27480 KiB  
Article
A Bayesian Approach for Forecasting the Probability of Large Earthquakes Using Thermal Anomalies from Satellite Observations
by Zhonghu Jiao and Xinjian Shan
Remote Sens. 2024, 16(9), 1542; https://doi.org/10.3390/rs16091542 - 26 Apr 2024
Cited by 1 | Viewed by 605
Abstract
Studies have demonstrated the potential of satellite thermal infrared observations to detect anomalous signals preceding large earthquakes. However, the lack of well-defined precursory characteristics and inherent complexity and stochasticity of the seismicity continue to impede robust earthquake forecasts. This study investigates the potential [...] Read more.
Studies have demonstrated the potential of satellite thermal infrared observations to detect anomalous signals preceding large earthquakes. However, the lack of well-defined precursory characteristics and inherent complexity and stochasticity of the seismicity continue to impede robust earthquake forecasts. This study investigates the potential of pre-seismic thermal anomalies, derived from five satellite-based geophysical parameters, i.e., skin temperature, air temperature, total integrated column water vapor burden, outgoing longwave radiation (OLR), and clear-sky OLR, as valuable indicators for global earthquake forecasts. We employed a spatially self-adaptive multiparametric anomaly identification scheme to refine these anomalies, and then estimated the posterior probability of an earthquake occurrence given observed anomalies within a Bayesian framework. Our findings reveal a promising link between thermal signatures and global seismicity, with elevated forecast probabilities exceeding 0.1 and significant probability gains in some strong earthquake-prone regions. A time series analysis indicates probability stabilization after approximately six years. While no single parameter consistently dominates, each contributes precursory information, suggesting a promising avenue for a multi-parametric approach. Furthermore, novel anomaly indices incorporating probabilistic information significantly reduce false alarms and improve anomaly recognition. Despite remaining challenges in developing dynamic short-term probabilities, rigorously testing detection algorithms, and improving ensemble forecast strategies, this study provides compelling evidence for the potential of thermal anomalies to play a key role in global earthquake forecasts. The ability to reliably estimate earthquake forecast probabilities, given the ever-present threat of destructive earthquakes, holds considerable societal and ecological importance for mitigating earthquake risk and improving preparedness strategies. Full article
(This article belongs to the Special Issue Remote Sensing Makes it Possible: Prediction and Evaluation of Natural Hazards)
►▼ Show Figures

Figure 1

24 pages, 35052 KiB  
Article
Using Keyhole Images to Map Soil Liquefaction Induced by the 1966 Xingtai Ms 6.8 and 7.2 Earthquakes, North China
by Yali Guo, Yueren Xu, Haofeng Li, Lingyu Lu, Wentao Xu and Peng Liang
Remote Sens. 2023, 15(24), 5777; https://doi.org/10.3390/rs15245777 - 18 Dec 2023
Viewed by 1067
Abstract
In March 1966, Ms 6.8 and 7.2 earthquakes occurred in Xingtai, North China, resulting in widespread soil liquefaction that caused severe infrastructure damage and economic losses. Using Keyhole satellite imagery combined with aerial images and fieldwork records, we interpreted and identified 66,442 [...] Read more.
In March 1966, Ms 6.8 and 7.2 earthquakes occurred in Xingtai, North China, resulting in widespread soil liquefaction that caused severe infrastructure damage and economic losses. Using Keyhole satellite imagery combined with aerial images and fieldwork records, we interpreted and identified 66,442 liquefaction points and analyzed the coseismic liquefaction distribution characteristics and possible factors that influenced the Xingtai earthquakes. The interpreted coseismic liquefaction was mainly concentrated above the IX-degree zone, accounting for 80% of all liquefaction points. High-density liquefaction zones (point density > 75 pieces/km2) accounted for 22% of the total liquefaction points. Most of the interpreted liquefaction points were located at the region with a peak ground acceleration (PGA) of >0.46 g. The liquefaction area on 22 March was significantly larger than that on 8 March. The region of liquefaction was mainly limited by sandy soil conditions, water system conditions, and seismic geological conditions and distributed in areas with loose fine sand and silt deposits, a high water table (groundwater level increases before both mainshocks corresponding to the liquefaction intensive regions), rivers, and ancient river channels. Liquefaction exhibited a repeating characteristic in the same region. Further understanding of the liquefaction characteristics of Xingtai can provide a reference for the prevention of liquefaction in northern China. Full article
(This article belongs to the Special Issue Remote Sensing Makes it Possible: Prediction and Evaluation of Natural Hazards)
►▼ Show Figures

Graphical abstract

Other

Jump to: Research

13 pages, 5668 KiB  
Technical Note
Two Sets of High-Conductivity Systems with Different Scales Reveal the Seismogenic Mechanism of Earthquakes in the Songyuan Area, Northeastern China
by Xiaodong Jia, Zhuoyang Li, Jiangtao Han, Hesheng Hou, Zhonghua Xin, Lijia Liu and Wenyu Liu
Remote Sens. 2024, 16(3), 547; https://doi.org/10.3390/rs16030547 - 31 Jan 2024
Viewed by 729
Abstract
To reveal the deep seismogenic environment and mechanism of earthquakes in Songyuan City, Northeastern China, 59 broadband magnetotelluric sites in the Songyuan area were arranged in this study at a spacing of 5 km. In addition, two intersecting magnetotelluric profiles, with a total [...] Read more.
To reveal the deep seismogenic environment and mechanism of earthquakes in Songyuan City, Northeastern China, 59 broadband magnetotelluric sites in the Songyuan area were arranged in this study at a spacing of 5 km. In addition, two intersecting magnetotelluric profiles, with a total of 23 measuring sites and a spacing of 2 km, were established near the Ningjiang earthquake swarm. Using a nonlinear conjugate gradient (NLCG) algorithm, resistivity structures in the lithosphere were obtained at different scales using three-dimensional (3D) inversion. The research results show that: a deep high-conductivity system (<10 Ω·m) was identified at 25–85 km depth in the lithosphere under Songyuan, corresponding closely to a region of high heat flow. It is inferred to be the molten material of mantle upwelling. In addition, a shallow high-conductivity system (<10 Ω·m) was identified beneath the Ningjiang earthquake swarm, which is interpreted to correspond to the Fuyu North fault. It is the main seismo-controlling structure of the Ningjiang earthquake swarm. The deep seismogenic environment and seismogenic mechanism of the Ningjiang earthquake swarm can be described as a deep upwelling of molten mantle material, which provides the power source. The deep magma intruded into the lower crust and accumulated, then intruded along faults and fissures, resulting in the activation of the North Fuyu fault and triggering the Ningjiang earthquake. It is attributed to the activation of shallow faults caused by the upwelling of molten mantle material. Full article
(This article belongs to the Special Issue Remote Sensing Makes it Possible: Prediction and Evaluation of Natural Hazards)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-5
Back to TopTop