Data for: Outliers detection in Puracé volcano based on Recursive Density Estimation
Published: 22 April 2019| Version 1 | DOI: 10.17632/j4mws428tx.1
Contributors:
Emmanuel Lasso, David Camilo Corrales, Juan Carlos Corrales Munoz, Jose Iglesias, Jose Eduardo GomezDescription
The Puracé volcano currently has a surveillance network composed of 43telemetric and 59 non-telemetric stations. These stations are used to measuredifferent monitoring parameters such as seismology, geodesy, geophysics, geo-290chemistry, climatology and the surface activity of the volcano. The data used inthis work comes from seven (7) telemetric stations that have adequate mainte-nance for volcanic monitoring of geochemical and deformation areas
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Categories
Volcanology, Machine Learning, Outlier