Special Issue "Remote Sensing for Volcano Systems Monitoring"
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 September 2021.
Interests: In the context of Earth Observation; research has focused on the structure of the Earth system and is specifically addressed to the quantitative analysis of the geodynamic processes that have characterized the evolution of volcanic; seismogenic; and geothermal areas. Specifically; studies have been carried out through integration and full exploitation of remote sensing data such as satellite RADAR; optical; thermal images and their integration with GPS; EDM; and other geodetic; geophysical measurements. In this framework; particular interest has been devoted to the development of quantitative methods of a physical; mathematical; and statistical tool to build analytical and numerical models and complete data fusion; for the interpretation and characterization of the sources that control short- and long-term evolution of volcanic systems.
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Interests: The research activity concerns the analysis of the deformative processes that characterize the evolution of volcanic and seismogenic areas, through the development of algorithms for the generation of deformation velocity maps and time series obtained with synthetic aperture radar interferometry (InSAR) techniques and geophysical modeling with analytical and numerical inversions. Recent activity is mainly focused on the development of multi-parametric and multiphysical methodologies for the characterization of stress sources that control the short- and long-term evolution of different geodynamic contexts. The obtained results have been published in peer-reviewed ISI journals.
Understanding the behavior and state of volcano systems represents an efficient and robust tool to reduce the associated hazards. The use of data from volcano monitoring represents a scientifically valid basis for short-term forecasts of a future eruption. In recent decades, remote sensing techniques have furnished a fundamental contribution in the growth of knowledge of volcanic systems as well as their structural evolution. Many volcanoes are inaccessible during the climax eruption (or they are located in inaccessible regions of the Earth) and may continue to be inaccessible for a long time also after the eruptive activity. To overcome these limitations, remote sensing is now playing an important role in understanding the science underlying volcanic behavior and is consequently present in any effective hazards-mitigation program.
New research lines are often driven by technological advancements in the development of novel sensors or acquisition platforms. For this reason, processing and complete data fusion of multiparametric, proximal, and remote sensing datasets is crucial for understanding the volcanic processes, increasing the interpretative capacity of the observed volcanic phenomena.
The volume will be favorable to collect studies oriented toward the understanding of several aspects of volcano systems, from the physical characterization of a system to its eruption process, and in proposing adequate multiplatform, multifrequencies, and interdisciplinary data analysis.Dr. Pietro Tizzani
Dr. Giuseppe Solaro
Dr. Raffaele Castaldo
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 2400 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.
- Volcano monitoring systems
- Multiplatform remote sensing
- Geophysical methods
- Analytical and numerical modeling
- Integration and data fusion
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Study of the surface deformation in La Palma (Canary Islands), 2006-2010, using advanced satellite radar interferometry and modeling
Authors: José Fernández; Joaquín Escayo; Juan F. Prieto; Antonio G. Camacho; Mimmo Palano
Affiliation: Institute of Geosciences (CSIC, UCM), C/ Doctor Severo Ochoa, 7, Ciudad Universitaria, 28040 Madrid, Spain
Title: Anticorrelated Ground Deformation Pattern between Mauna Loa and Kīlauea
Authors: Monika Przeor; Luca D’Auria; Susi Pepe; Pietro Tizzani
Affiliation: Instituto Volcanológico de Canarias (INVOLCAN), San Cristóbal de La Laguna, Spain
Abstract: The contrasting dynamics between Mauna Loa and Kīlauea have been studied over the last 100 years from several points of view. The fact that dynamic changes of one volcano trigger a response of the other volcano seems to indicate that a sort of connection between them may exist. However, petrology studies, discard the existence of a direct connection between the magmatic systems of these two volcanoes. In this work we aim at contributing to this discussion by studying the spatio-temporal relationship between the ground deformation observed at these two volcanoes. For this purpose, we analyzed both DInSAR and GPS data. We used a DInSAR SBAS dataset spanning the 2003–2010time interval and acquired along ascending and descending orbits of the ENVISAT (ESA) satellite under different look angles. From a total of 10 tracks that cover the Big Island (Hawai`i), we selected three of them, covering both volcanic edifices. We considered also the available GPS measurements in the area. Specifically, we computed areal strain time series on 15 triplets of stations for Kīlauea volcano and 11 for Mauna Loa volcano. We applied the Independent Component Analysis (ICA) to the DInSAR SBAS data to identify correlated pattern in the observed ground deformation of both volcanoes. The results revealed an anticorrelated behavior in the ground deformation pattern among the areas of the summit calderas of Mauna Loa and Kīlauea meaning that the opposite respond is seen in the ground deformation behavior of one volcano respect to the other. At the same time Kīlauea shows a more complex pattern, exhibiting an additional component which is not correlated with Mauna Loa. These results are supported by the GPS areal strain time series. To corroborate these findings and to aid the interpretation of the results, we performed an inverse modeling to uncover the parameters of the sources that produce observed ground deformation The results indicate that the anticorrelated sources are both located at shallow depth (about 900 m) beneath the summit calderas. This excludes a direct hydraulic connection as a possible mechanism. Instead we postulate a stress-transfer mechanism to explain the observed anticorrelated behavior. The independent component observed at Kīlauea is located at greater depth (3 km) and shows a more complex spatial pattern. It is likely to be related with the deeper parts of the magmatic reservoir of Kīlauea. Keywords: Volcano Geodesy, Independent Component Analysis, Mauna Loa, Kīlauea, DInSAR, SBAS time series.