Improved optical flow velocity analysis in SO 2 camera images of volcanic plumes – implications for emission-rate retrievals investigated at Mt Etna, Italy and Guallatiri, Chile
2018
Accurate gas velocity measurements in emission plumes are highly desirable for various atmospheric remote sensing applications. The imaging technique of UV SO 2 cameras is commonly used to monitor SO 2 emissions from volcanoes and anthropogenic sources (e.g. power plants, ships). The camera systems capture the emission plumes at high spatial and temporal resolution. This allows the gas velocities in the plume to be retrieved directly from the images. The latter can be measured at a pixel level using optical flow (OF) algorithms. This is particularly advantageous under turbulent plume conditions. However, OF algorithms intrinsically rely on contrast in the images and often fail to detect motion in low-contrast image areas. We present a new method to identify ill-constrained OF motion vectors and replace them using the local average velocity vector. The latter is derived based on histograms of the retrieved OF motion fields. The new method is applied to two example data sets recorded at Mt Etna (Italy) and Guallatiri (Chile). We show that in many cases, the uncorrected OF yields significantly underestimated SO 2 emission rates. We further show that our proposed correction can account for this and that it significantly improves the reliability of optical-flow-based gas velocity retrievals. In the case of Mt Etna, the SO 2 emissions of the north-eastern crater are investigated. The corrected SO 2 emission rates range between 4.8 and 10.7 kg s −1 (average of 7.1 ± 1.3 kg s −1 ) and are in good agreement with previously reported values. For the Guallatiri data, the emissions of the central crater and a fumarolic field are investigated. The retrieved SO 2 emission rates are between 0.5 and 2.9 kg s −1 (average of 1.3 ± 0.5 kg s −1 ) and provide the first report of SO 2 emissions from this remotely located and inaccessible volcano.
Keywords:
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
53
References
14
Citations
NaN
KQI