remotesensing-logo

Journal Browser

Journal Browser

Satellite Remote Sensing of High-Temperature Thermal Anomalies

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 June 2020) | Viewed by 21433

Special Issue Editors

Istituto Di Metodologie Per L'analisi Ambientale, Tito Scalo, Italy
Interests: satellite remote sensing of volcanoes; fires; dust outbreaks; natural hazards
Special Issues, Collections and Topics in MDPI journals
Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova cesta 2, 1000 Ljubljana, Slovenia
Interests: thermal remote sensing; photogrammetry; volcanology; urban heat island; CubeSats; big data; machine learning
Special Issues, Collections and Topics in MDPI journals
Institute of Methodologies for Environmental Analysis, National Research Council, 85050 Potenza, Italy
Interests: monitoring and mitigation of forest fires; remote sensing of natural/anthropogenic risks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

High-temperature thermal sources are of great interest to the scientific community. Active magmatic surfaces, geothermal fields, forest fires, industrial hot spots and gas flaring emit more heat than their surroundings, generating thermal anomalies that may be investigated by means of satellite sensors operating in the infrared electromagnetic spectrum. This Special Issue aims at evaluating advances in detecting, monitoring and characterizing high-temperature thermal anomalies from space. It should increase our capacity to study and understand those features and their sources. The guest editors encourage the submission of manuscripts with particular reference to the:

  • Use of novel satellite remote sensing techniques for analyzing high-temperature thermal anomalies (e.g. improved hot spot products)
  • Use of data from new generation satellite sensors (offering improved features in terms of spatial, spectral and temporal resolution);
  • Multi-sensor data fusion (e.g. thermal, microwave);
  • Uncertainty analysis related to the remote sensing of high-temperature anomalies (time series analyses, influence of processing assumptions).

Dr. Francesco Marchese
Dr. Nicola Genzano
Dr. Klemen Zakšek
Dr. Carolina Filizzola
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

  • Thermal anomalies
  • Satellite remote sensing
  • High-temperature surfaces
  • Natural/anthropogenic sources
  • New generation satellite sensors

Published Papers (5 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

24 pages, 23389 KiB  
Article
Detection of Thermal Changes Related to the 2011 Shinmoedake Volcano Activity, Japan: Spatiotemporal Variation of Singularity of MODIS Data after Discriminating False Changes Due to Cloud
by Rika Tsutsumi, Katsumi Hattori, Chie Yoshino and Nicola Genzano
Remote Sens. 2020, 12(16), 2637; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12162637 - 15 Aug 2020
Cited by 1 | Viewed by 2646
Abstract
We proposed a cloud discrimination method applicable in Japan using MODIS nighttime data, monitored the singularity of the spatiotemporal correlation of surface temperature anomalies and investigated the possibility of detecting and monitoring lava activity in Shinmoedake. With the aim to detect lava eruption [...] Read more.
We proposed a cloud discrimination method applicable in Japan using MODIS nighttime data, monitored the singularity of the spatiotemporal correlation of surface temperature anomalies and investigated the possibility of detecting and monitoring lava activity in Shinmoedake. With the aim to detect lava eruption activity in 2011, nine years of data from 2003 to 2011 were analyzed. As a result, the first anomalous singularity in brightness temperature was detected on 26 January 2011. Moreover, the maximum value was detected on 30 January 2011. The values showed larger ones until early February 2011. When an anomalous singularity appeared, it was the only period with the magma-related volcanic activity for Shinmoedake over the analyzed period of nine years. The above facts indicate the effectiveness of the proposed singularity method to monitor the lava activity for Shinmoedake. Therefore, it is concluded that if cloud discrimination is realized with high accuracy, no spurious changes will come to arise, and no false detection of hotspots will be given. Full article
(This article belongs to the Special Issue Satellite Remote Sensing of High-Temperature Thermal Anomalies)
Show Figures

Graphical abstract

16 pages, 2592 KiB  
Article
Temperature and Emissivity Separation ‘Draping’ Algorithm Applied to Hyperspectral Infrared Data
by Valerio Lombardo, Leonie Pick, Claudia Spinetti, Jacopo Tadeucci and Klemen Zakšek
Remote Sens. 2020, 12(12), 2046; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12122046 - 25 Jun 2020
Cited by 8 | Viewed by 2496
Abstract
In the presented work, the spectral emissivity of basaltic melts at magmatic temperatures was retrieved in a laboratory-controlled experiment by measuring their spectral radiance. Granulated bombs of Etnean basalts were melted and the radiant energy from the melting surface was recorded by a [...] Read more.
In the presented work, the spectral emissivity of basaltic melts at magmatic temperatures was retrieved in a laboratory-controlled experiment by measuring their spectral radiance. Granulated bombs of Etnean basalts were melted and the radiant energy from the melting surface was recorded by a portable spectroradiometer in the short wavelength infrared (SWIR) spectral range between 1500 and 2500 nm. The Draping algorithm, an improved algorithm for temperature and emissivity separation, was applied for the first time to SWIR hyperspectral data in order to take into account the non-uniform temperature distribution of the melt surface and, at the same time, solving the two temperatures and the spectral emissivity. The results have been validated by comparing our results with the emissivity measured at a "lava simulator". Basalt spectral emissivity does not vary significantly at magmatic temperature, but shows an absorption feature in the range 2180–2290 nm, an atmospheric window pivotal for the IR remote sensing of active volcanoes. Full article
(This article belongs to the Special Issue Satellite Remote Sensing of High-Temperature Thermal Anomalies)
Show Figures

Figure 1

32 pages, 15233 KiB  
Article
Volcanic Hot-Spot Detection Using SENTINEL-2: A Comparison with MODIS–MIROVA Thermal Data Series
by Francesco Massimetti, Diego Coppola, Marco Laiolo, Sébastien Valade, Corrado Cigolini and Maurizio Ripepe
Remote Sens. 2020, 12(5), 820; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12050820 - 03 Mar 2020
Cited by 29 | Viewed by 8002
Abstract
In the satellite thermal remote sensing, the new generation of sensors with high-spatial resolution SWIR data open the door to an improved constraining of thermal phenomena related to volcanic processes, with strong implications for monitoring applications. In this paper, we describe a new [...] Read more.
In the satellite thermal remote sensing, the new generation of sensors with high-spatial resolution SWIR data open the door to an improved constraining of thermal phenomena related to volcanic processes, with strong implications for monitoring applications. In this paper, we describe a new hot-spot detection algorithm developed for SENTINEL-2/MSI data that combines spectral indices on the SWIR bands 8a-11-12 (with a 20-meter resolution) with a spatial and statistical analysis on clusters of alerted pixels. The algorithm is able to detect hot-spot-contaminated pixels (S2Pix) in a wide range of environments and for several types of volcanic activities, showing high accuracy performances of about 1% and 94% in averaged omission and commission rates, respectively, underlining a strong reliability on a global scale. The S2-derived thermal trends, retrieved at eight key-case volcanoes, are then compared with the Volcanic Radiative Power (VRP) derived from MODIS (Moderate Resolution Imaging Spectroradiometer) and processed by the MIROVA (Middle InfraRed Observation of Volcanic Activity) system during an almost four-year-long period, January 2016 to October 2019. The presented data indicate an overall excellent correlation between the two thermal signals, enhancing the higher sensitivity of SENTINEL-2 to detect subtle, low-temperature thermal signals. Moreover, for each case we explore the specific relationship between S2Pix and VRP showing how different volcanic processes (i.e., lava flows, domes, lakes and open-vent activity) produce a distinct pattern in terms of size and intensity of the thermal anomaly. These promising results indicate how the algorithm here presented could be applicable for volcanic monitoring purposes and integrated into operational systems. Moreover, the combination of high-resolution (S2/MSI) and moderate-resolution (MODIS) thermal timeseries constitutes a breakthrough for future multi-sensor hot-spot detection systems, with increased monitoring capabilities that are useful for communities which interact with active volcanoes. Full article
(This article belongs to the Special Issue Satellite Remote Sensing of High-Temperature Thermal Anomalies)
Show Figures

Graphical abstract

20 pages, 4030 KiB  
Article
The VIIRS-Based RST-FLARE Configuration: The Val d’Agri Oil Center Gas Flaring Investigation in Between 2015–2019
by Mariapia Faruolo, Teodosio Lacava, Nicola Pergola and Valerio Tramutoli
Remote Sens. 2020, 12(5), 819; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12050819 - 03 Mar 2020
Cited by 7 | Viewed by 3273
Abstract
The RST (Robust Satellite Techniques)-FLARE algorithm is a satellite-based method using a multitemporal statistical analysis of nighttime infrared signals strictly related to industrial hotspots, such as gas flares. The algorithm was designed for both identifying and characterizing gas flares in terms of radiant/emissive [...] Read more.
The RST (Robust Satellite Techniques)-FLARE algorithm is a satellite-based method using a multitemporal statistical analysis of nighttime infrared signals strictly related to industrial hotspots, such as gas flares. The algorithm was designed for both identifying and characterizing gas flares in terms of radiant/emissive power. The Val d’Agri Oil Center (COVA) is a gas and oil pre-treatment plant operating for about two decades within an anthropized area of Basilicata region (southern Italy) where it represents a significant potential source of social and environmental impacts. RST-FLARE, developed to study and monitor the gas flaring activity of this site by means of MODIS (Moderate Resolution Imaging Spectroradiometer) data, has exported VIIRS (Visible Infrared Imaging Radiometer Suite) records by exploiting the improved spatial and spectral properties offered by this sensor. In this paper, the VIIRS-based configuration of RST-FLARE is presented and its application on the recent (2015-2019) gas flaring activity at COVA is analyzed and discussed. Its performance in gas flaring characterization is in good agreement with VIIRS Nightfire outputs to which RST-FLARE seems to provide some add-ons. The great consistency of radiant heat estimates computed with both RST-FLARE developed configurations allows proposing a multi-sensor RST-FLARE strategy for a more accurate multi-year analysis of gas flaring. Full article
(This article belongs to the Special Issue Satellite Remote Sensing of High-Temperature Thermal Anomalies)
Show Figures

Graphical abstract

22 pages, 12078 KiB  
Article
The July/August 2019 Lava Flows at the Sciara del Fuoco, Stromboli–Analysis from Multi-Sensor Infrared Satellite Imagery
by Simon Plank, Francesco Marchese, Carolina Filizzola, Nicola Pergola, Marco Neri, Michael Nolde and Sandro Martinis
Remote Sens. 2019, 11(23), 2879; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11232879 - 03 Dec 2019
Cited by 29 | Viewed by 3899
Abstract
On 3 July 2019 a rapid sequence of paroxysmal explosions at the summit craters of Stromboli (Aeolian-Islands, Italy) occurred, followed by a period of intense Strombolian and effusive activity in July, and continuing until the end of August 2019. We present a joint [...] Read more.
On 3 July 2019 a rapid sequence of paroxysmal explosions at the summit craters of Stromboli (Aeolian-Islands, Italy) occurred, followed by a period of intense Strombolian and effusive activity in July, and continuing until the end of August 2019. We present a joint analysis of multi-sensor infrared satellite imagery to investigate this eruption episode. Data from the Spinning-Enhanced-Visible-and-InfraRed-Imager (SEVIRI) was used in combination with those from the Multispectral-Instrument (MSI), the Operational-Land-Imager (OLI), the Advanced-Very High-Resolution-Radiometer (AVHRR), and the Visible-Infrared-Imaging-Radiometer-Suite (VIIRS). The analysis of infrared SEVIRI-data allowed us to detect eruption onset and to investigate short-term variations of thermal volcanic activity, providing information in agreement with that inferred by nighttime-AVHRR-observations. By using Sentinel-2-MSI and Landsat-8-OLI imagery, we better localized the active lava-flows. The latter were quantitatively characterized using infrared VIIRS-data, estimating an erupted lava volume of 6.33 × 10 6 ± 3.17 × 10 6 m3 and a mean output rate of 1.26 ± 0.63 m3/s for the July/August 2019 eruption period. The estimated mean-output-rate was higher than the ones in the 2002–2003 and 2014 Stromboli effusive eruptions, but was lower than in the 2007-eruption. These results confirmed that a multi-sensor-approach might provide a relevant contribution to investigate, monitor and characterize thermal volcanic activity in high-risk areas. Full article
(This article belongs to the Special Issue Satellite Remote Sensing of High-Temperature Thermal Anomalies)
Show Figures

Graphical abstract

Back to TopTop