Dating lava flows of tropical volcanoes by means of spatial modeling of vegetation recovery |
| |
| Authors: | Long Li Lien Bakelants Carmen Solana Frank Canters Matthieu Kervyn |
| |
| Affiliation: | 1. School of Environmental Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, P. R. China;2. Department of Geography & Earth System Science, Vrije Universiteit Brussel, Brussels, Belgium;3. Department of Transport and Regional Economics, University of Antwerp, Antwerp, Belgium;4. School of Earth and Environmental Sciences, University of Portsmouth, Portsmouth, UK;5. Cartography and GIS Research Group, Department of Geography, Vrije Universiteit Brussel, Brussels, Belgium |
| |
| Abstract: | The age of past lava flows is crucial information for evaluating the hazards and risks posed by effusive volcanoes, but traditional dating methods are expensive and time‐consuming. This study proposes an alternative statistical dating method based on remote sensing observations of tropical volcanoes by exploiting the relationship between lava flow age and vegetation cover. First, the factors controlling vegetation density on lava flows, represented by the normalized difference vegetation index (NDVI), were investigated. These factors were then integrated into pixel‐based multi‐variable regression models of lava flow age to derive lava flow age maps. The method was tested at a pixel scale on three tropical African volcanoes with considerable recent effusive activity: Nyamuragira (Democratic Republic of Congo), Mt Cameroon (Cameroon) and Karthala (the Comoros). Due to different climatic and topographic conditions, the parameters of the spatial modeling are volcano‐specific. Validation suggests that the obtained statistical models are robust and can thus be applied for estimating the age of unmodified undated lava flow surfaces for these volcanoes. When the models are applied to fully vegetated lava flows, the results should be interpreted with caution due to the saturation of NDVI. In order to improve the accuracy of the models, when available, spatial data on temperature and precipitation should be included to directly represent climatic variation. Copyright © 2017 John Wiley & Sons, Ltd. |
| |
| Keywords: | dating lava flows NDVI remote sensing Nyamuragira Mt Cameroon Karthala |
|
|
