Discriminating lava flows of different age within Nyamuragira’s volcanic field using spectral mixture analysis

Long Li, Frank Canters, Carmen Solana, Weiwei Ma, Longqian Chen, Matthieu Kervyn

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In this study, linear spectral mixture analysis (LSMA) is used to characterize the spectral heterogeneity of lava flows from Nyamuragira volcano, Democratic Republic of Congo, where vegetation and lava are the two main land covers. In order to estimate fractions of vegetation and lava through satellite remote sensing, we made use of 30 m resolution Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Land Imager (ALI) imagery. 2 m Pleiades data was used for validation. From the results, we conclude that (1) LSMA is capable of characterizing volcanic fields and discriminating between different types of lava surfaces; (2) three lava endmembers can be identified as lava of old, intermediate and young age, corresponding to different stages in lichen growth and chemical weathering; (3) a strong relationship is observed between vegetation fraction and lava age, where vegetation at Nyamuragira starts to significantly colonize lava flows ∼15 years after eruption and occupies over 50% of the lava surfaces ∼40 years after eruption. Our study demonstrates the capability of spectral unmixing to characterize lava surfaces and vegetation colonization over time, which is particularly useful for poorly known volcanoes or those not accessible for physical or political reasons.
Original languageEnglish
Pages (from-to)1-10
Number of pages11
JournalInternational Journal of Applied Earth Observation and Geoinformation
Early online date31 Mar 2015
Publication statusPublished - 1 Aug 2015


  • vegetation fraction
  • lava flow
  • spectral mixture analysis
  • Nyamuragira
  • ALI
  • Pleiades


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