Special Issue "Recent Advances in Remote Sensing Applied to Geohazards, Vulnerability and Risk Studies"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: 30 June 2020.

Special Issue Editors

Dr. François Kervyn
E-Mail Website
Guest Editor
Natural Hazards Service, Royal Museum for Central Africa, Leuvensesteenweg 13, 3080 Tervuren, Belgium
Interests: Central Africa; remote sensing; GIS; natural hazards; risk assessment; radar interferometry; old archive valorization
Dr. Benoît Smets
E-Mail Website
Guest Editor
Natural Hazards Service, Royal Museum for Central Africa, Leuvensesteenweg 13, 3080 Tervuren, Belgium
Interests: volcanology; natural hazards; optical and SAR remote sensing; photogrammetry; GIS; unmanned aerial systems; digital elevation modeling and analysis; topographic change detection

Special Issue Information

Dear Colleagues,

Earth Observation (EO) has become a major tool for the study, monitoring, and management of natural hazards and disasters. In developing countries, EO is sometimes the only solution available to get quantitative measurements. Remote sensing is increasingly used by scientists, local authorities, NGOs, and disaster responders to answer their needs in spatial information for each stage of risk management, from hazard and vulnerability assessment to disaster monitoring and response. Complementary to ground information, satellite- and drone-based sensors help to get observations and measurements at different spatial and temporal scales, and sometimes in difficult-to-access areas, providing key intel for decision-making and field action.

Geohazards, i.e., natural hazards of geological or geophysical origin, are also increasingly being studied by remote sensing, as is the vulnerability of populations and infrastructure to these hazards. Earth observation tools now offer a growing range of techniques for quantifying risks in addition to their evaluation alone. In this respect, the challenges that remote sensing faces today concern both the coverage and spatial resolution as well as the temporal frequency of observations. Indeed, geohazards such as volcanic eruptions, landslides, earthquakes or tsunamis, for example, are often sporadic natural events that occur over a relatively short period of time and at scales ranging from a few square kilometers to hundreds or even thousands of square kilometers. In addition, difficult atmospheric conditions often require the use of a combination of sensors working in appropriate spectral bands, from visible to microwave.

During the past decade, new series of sensors and platforms have become real game-changers by providing both high-temporal and high-spatial resolution at the same time, and/or more sensitive sensors with a better signal-to-noise ratio. This has been possible thanks to the technological progress in spatial and sensor engineering, the recent advances in computer data processing and storage, the increasing number of available satellites and sensors, the development of satellite constellations, and the emergence of the unmanned aerial systems (UAS) for civil applications. In addition, free access to remote sensing data for scientific research is an increasing trend, which promotes the use of EO. The European initiative Copernicus satellite missions, with the new Sentinel constellations, the constellations of >190 micro-satellites developed by Planet Labs, and the increasing performance and decreasing cost of UAS applications are among these game changers that make EO more efficient and exploited every day.

In the present Special Issue, we welcome all publications related to the innovative use of recent sensors and algorithms in order to improve geohazard, vulnerability and risk assessment, as well as monitoring and disaster response. Both methodological and application papers are accepted. Satellite- and drone-based remote sensing are the main targets, but ground-based remote sensing is also very welcome.

In particular, research papers are encouraged to cover a wide range of subjects related to geohazards, vulnerability, and risk studies, which may include but are not limited to the following topics:

  • Improvements provided by new algorithms, sensors, and constellations of satellites;
  • Fundamental natural processes controlling the occurrence of geohazards;
  • Mapping, monitoring and forecasting of geohazards;
  • EO approaches for vulnerability and risk assessment;
  • EO as a tool for disaster response;
  • Innovative multisensor approaches;
  • Innovative UAS applications;
  • Time-series analysis using high spatial resolution imagery.

Dr. François Kervyn
Dr. Benoît Smets
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 papers will be 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 1800 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

  • Earth observation
  • Geohazards
  • Vulnerability
  • Risk mitigation
  • Disaster response

Published Papers (2 papers)

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Open AccessLetter
Land Surface Temperature Variation Following the 2017 Mw 7.3 Iran Earthquake
Remote Sens. 2019, 11(20), 2411; https://doi.org/10.3390/rs11202411 - 17 Oct 2019
Abstract
During an earthquake, crustal deformation, fluid flow, and temperature variation are coupled; however, earthquake-related land surface temperature (LST) variations remain unclear. To determine whether post-seismic fluid migration can cause changes in LST, and taking the Mw 7.3 2017 Iran earthquake as an example, [...] Read more.
During an earthquake, crustal deformation, fluid flow, and temperature variation are coupled; however, earthquake-related land surface temperature (LST) variations remain unclear. To determine whether post-seismic fluid migration can cause changes in LST, and taking the Mw 7.3 2017 Iran earthquake as an example, we modeled surface cooling (CA) and warming (WA) areas induced by co-seismic slip and fluid migration using a thermo-hydro-mechanical (THM) coupled numerical simulation. Moreover, using nighttime LST data with 15-min resolution, the daily attenuation coefficient k of nighttime LST was extracted by attenuation function fitting, and the trend of the k time series was analyzed using the Mann–Kendall and Sen’s methods. Based on the comparison of k trends between the post-seismic and 2010–2016 periods, we obtained cooling and warming trends for the modeled CA and WA. The numerical simulation and observational data show good consistency, and both indicate that fluid migration caused by crustal deformation can lead to changes in LST. The numerical simulations show that after the Iran earthquake, the surface projection area of co-seismic slip correlated with a cooling area (CA), while the surrounding area correlated with a warming area (WA). For the LST observational data, the post-seismic k trends of the calculated CA and WA are positive and negative, indicating sustained cooling and warming processes, respectively. This study provides evidence that LST variation is caused by co-seismic crustal deformation and fluid migration and reveals the coupled evolution of deformation, fluid, and temperature fields. The results provide new insights into the mechanisms of seismic thermal anomalies. Full article
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Open AccessLetter
Detection of Liquefaction Phenomena from the 2017 Pohang (Korea) Earthquake Using Remote Sensing Data
Remote Sens. 2019, 11(18), 2184; https://doi.org/10.3390/rs11182184 - 19 Sep 2019
Abstract
On 15 November 2017, liquefaction phenomena were observed around the epicenter after a 5.4 magnitude earthquake occurred in Pohang in southeast Korea. In this study, we attempted to detect areas of sudden water content increase by using SAR (synthetic aperture radar) and optical [...] Read more.
On 15 November 2017, liquefaction phenomena were observed around the epicenter after a 5.4 magnitude earthquake occurred in Pohang in southeast Korea. In this study, we attempted to detect areas of sudden water content increase by using SAR (synthetic aperture radar) and optical satellite images. We analyzed coherence changes using Sentinel-1 SAR coseismic image pairs and analyzed NDWI (normalized difference water index) changes using Landsat 8 and Sentinel-2 optical satellite images from before and after the earthquake. Coherence analysis showed no liquefaction-induced surface changes. The NDWI time series analysis models using Landsat 8 and Sentinel-2 optical images confirmed liquefaction phenomena close to the epicenter but could not detect liquefaction phenomena far from the epicenter. We proposed and evaluated the TDLI (temporal difference liquefaction index), which uses only one SWIR (short-wave infrared) band at 2200 nm, which is sensitive to soil moisture content. The Sentinel-2 TDLI was most consistent with field observations where sand blow from liquefaction was confirmed. We found that Sentinel-2, with its relatively shorter revisit period compared to that of Landsat 8 (5 days vs. 16 days), was more effective for detecting traces of short-lived liquefaction phenomena on the surface. The Sentinel-2 TDLI could help facilitate rapid investigations and responses to liquefaction damage. Full article
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