Data for: Outliers detection in Puracé volcano based on Recursive Density Estimation

Published: 22 April 2019| Version 1 | DOI: 10.17632/j4mws428tx.1
Emmanuel Lasso,
David Camilo Corrales,
Juan Carlos Corrales Munoz,
Jose Iglesias,
Jose Eduardo Gomez


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



Volcanology, Machine Learning, Outlier