18 October 2016 Analyzing land surface temperature variations during Fogo Island (Cape Verde) 2014-2015 eruption with Landsat 8 images
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Abstract
Land Surface Temperature (LST) is an important parameter related to land surface processes that changes continuously through time. Assessing its dynamics during a volcanic eruption has both environmental and socio-economical interest. Lava flows and other volcanic materials produced and deposited throughout an eruption transform the landscape, contributing to its heterogeneity and altering LST measurements. This paper aims to assess variations of satellite-derived LST and to detect patterns during the latest Fogo Island (Cape Verde) eruption, extending from November 2014 through February 2015. LST data was obtained through four processed Landsat 8 images, focused on the caldera where Pico do Fogo volcano sits. QGIS’ plugin Semi-Automatic Classification was used in order to apply atmospheric corrections and radiometric calibrations. The algorithm used to retrieve LST values is a single-channel method, in which emissivity values are known. The absence of in situ measurements is compensated by the use of MODIS sensor-derived LST data, used to compare with Landsat retrieved measurements. LST data analysis shows as expected that the highest LST values are located inside the caldera. High temperature values were also founded on the south-facing flank of the caldera. Although spatial patterns observed on the retrieved data remained roughly the same during the time period considered, temperature values changed throughout the area and over time, as it was also expected. LST values followed the eruption dynamic experiencing a growth followed by a decline. Moreover, it seems possible to recognize areas affected by lava flows of previous eruptions, due to well-defined LST spatial patterns.
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D. Vieira, D. Vieira, A. Teodoro, A. Teodoro, A. Gomes, A. Gomes, "Analyzing land surface temperature variations during Fogo Island (Cape Verde) 2014-2015 eruption with Landsat 8 images", Proc. SPIE 10005, Earth Resources and Environmental Remote Sensing/GIS Applications VII, 1000508 (18 October 2016); doi: 10.1117/12.2241382; https://doi.org/10.1117/12.2241382
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