Dating lava flows of tropical volcanoes by means of spatial modeling of vegetation recovery

Long Li, Lien Bakelants, Carmen Solana, Frank Canters, Matthieu Kervyn

Onderzoeksoutput: Articlepeer review

28 Citaten (Scopus)
265 Downloads (Pure)

Samenvatting

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.

Originele taal-2English
Pagina's (van-tot)840-856
Aantal pagina's17
TijdschriftEarth Surface Processes and Landforms
Volume43
Nummer van het tijdschrift4
DOI's
StatusPublished - 30 mrt 2018

Vingerafdruk

Duik in de onderzoeksthema's van 'Dating lava flows of tropical volcanoes by means of spatial modeling of vegetation recovery'. Samen vormen ze een unieke vingerafdruk.

Citeer dit