Next Article in Journal
Use of A Neural Network-Based Ocean Body Radiative Transfer Model for Aerosol Retrievals from Multi-Angle Polarimetric Measurements
Previous Article in Journal
Long-Term Change of the Secchi Disk Depth in Lake Maninjau, Indonesia Shown by Landsat TM and ETM+ Data
Previous Article in Special Issue
On the Applicability of Laboratory Thermal Infrared Emissivity Spectra for Deconvolving Satellite Data of Opaque Volcanic Ash Plumes
Open AccessArticle

A Multi-Channel Algorithm for Mapping Volcanic Thermal Anomalies by Means of Sentinel-2 MSI and Landsat-8 OLI Data

1
Consiglio Nazionale delle Ricerche—Istituto di Metodologie per l Analisi Ambientale, C. da S. Loja, 85050 Tito Scalo (Pz), Italy
2
Scuola di Ingegneria, Università degli Studi della Basilicata, Via dell’Ateneo Lucano 10, 85100 Potenza, Italy
3
Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Catania, Osservatorio Etneo, Piazza Roma 2, 95125 Catania, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(23), 2876; https://doi.org/10.3390/rs11232876
Received: 11 October 2019 / Revised: 27 November 2019 / Accepted: 29 November 2019 / Published: 3 December 2019
The Multispectral Instrument (MSI) and the Operational Land Imager (OLI), respectively onboard Sentinel-2A/2B and Landsat 8 satellites, thanks to their features especially in terms of spatial/spectral resolution, represents two important instruments for investigating thermal volcanic activity from space. In this study, we used data from those sensors to test an original multichannel algorithm, which aims at mapping volcanic thermal anomalies at a global scale. The algorithm, named Normalized Hotspot Indices (NHI), combines two normalized indices, analyzing near infrared (NIR) and short wave infrared (SWIR) radiances, to identify hotspot pixels in daylight conditions. Results, achieved studying a number of active volcanoes located in different geographic areas and characterized by a different eruptive behavior, demonstrated the NHI capacity in mapping both subtle and more intense volcanic thermal anomalies despite some limitations (e.g., missed detections because of clouds/volcanic plumes). In addition, the study shows that the performance of NHI might be further increased using some additional spectral/spatial tests, in view of a possible usage of this algorithm within a known multi-temporal scheme of satellite data analysis. The low processing times and the straight forth exportability to data from other sensors make NHI, which is sensitive even to other high temperature sources, suited for mapping hot volcanic targets integrating information provided by current and well-established satellite-based volcanoes monitoring systems. View Full-Text
Keywords: volcanoes; thermal anomalies; Sentinel 2 MSI; Landsat-8 OLI volcanoes; thermal anomalies; Sentinel 2 MSI; Landsat-8 OLI
Show Figures

Graphical abstract

MDPI and ACS Style

Marchese, F.; Genzano, N.; Neri, M.; Falconieri, A.; Mazzeo, G.; Pergola, N. A Multi-Channel Algorithm for Mapping Volcanic Thermal Anomalies by Means of Sentinel-2 MSI and Landsat-8 OLI Data. Remote Sens. 2019, 11, 2876.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop