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The identification of subtle thermal anomalies (i.e., of low-temperature and/or spatial extent) at volcanoes by satellite is of great interest for scientists, especially because minor changes in surface temperature might reveal an unrest phase or impending activity. A good test case for assessing the sensitivity level of satellite-based methods is to study the thermal activity of Oldoinyo Lengai (OL) (Africa, Tanzania), which is the only volcano on Earth emitting natrocarbonatite lavas at a lower temperature (i.e., in the range 500–600 °C) than usual magmatic surfaces. In this work, we assess the potential of the RSTVOLC multi-temporal algorithm in detecting subtle hot spots at OL for comparison with MODLEN: A thermal anomaly detection method tailored to OL local conditions, by using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Our results investigating the eruptive events of 2000–2008 using RSTVOLC reveal the occurrence of several undocumented thermal activities of OL, and may successfully integrate MODLEN observations. In spite of some known limitations strongly affecting the identification of volcanic thermal anomalies from space (e.g., cloud cover; occurrence of short-lived events), this work demonstrates that RSTVOLC may provide a very important contribution for monitoring the OL, identifying subtle hot spots showing values of the radiant flux even around 1 MW.

remote sensing

Assessing Performance of the RSTVOLC Multi-Temporal Algorithm in Detecting Subtle Hot Spots at Oldoinyo Lengai (Tanzania, Africa) for Comparison with MODLEN