Abstract
The weather and seasonal fluctuations impact the circumstances under which spectral measurements are acquired. To assess the influence of changing acquisition conditions on geological remote sensing products, we observed the repeatability of several geological spectral indices over a 5-year period and correlated to atmospheric water vapor, aerosol content, and solar zenith position. The Sentinel-2 multispectral imager has a frequent 5-days overpass at the equator and it’s potential geological applications and mineral mapping, particularly iron oxides, has been studied extensively. Sentinel-2 MSI data were therefore chosen to calculate spectral indices (band ratios) for green vegetation, ferric & ferrous iron oxide mineralogy and hydroxyl bearing alteration (clay) mineralogy in a semi-arid area in southern Spain.
In line with our expectations, spectral index stability is highest during periods of heightened water vapor content, specifically under moist atmospheric conditions that happen over summer. The same is observed for the solar zenith angle, during the astronomical summer, and periods of low aerosol concentrations also contribute to enhanced spectral index repeatability. Clearly, multiple environmental conditions exhibit confounding effects that can be compounded to seasonality cycles. In contrast to our expectations, it appears that top-of-atmosphere data has a higher stability than bottom-of-atmosphere data. The Sen2Cor atmospheric processor seems to over-correct atmospheric influences.
In line with our expectations, spectral index stability is highest during periods of heightened water vapor content, specifically under moist atmospheric conditions that happen over summer. The same is observed for the solar zenith angle, during the astronomical summer, and periods of low aerosol concentrations also contribute to enhanced spectral index repeatability. Clearly, multiple environmental conditions exhibit confounding effects that can be compounded to seasonality cycles. In contrast to our expectations, it appears that top-of-atmosphere data has a higher stability than bottom-of-atmosphere data. The Sen2Cor atmospheric processor seems to over-correct atmospheric influences.
Original language | English |
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Publication status | Published - 13 Dec 2023 |
Event | 34th Geological Remote Sensing Group Annual Conference & AGM 2023 - Burlington House, London, United Kingdom Duration: 11 Dec 2023 → 13 Dec 2023 Conference number: 34 https://www.grsg.org.uk/grsg-agm-conference-2023 |
Conference
Conference | 34th Geological Remote Sensing Group Annual Conference & AGM 2023 |
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Country/Territory | United Kingdom |
City | London |
Period | 11/12/23 → 13/12/23 |
Internet address |