The Nevado del Ruíz volcano, located between the limits of the Departments of Caldas and Tolima, in Colombia, presented an unstable behavior in the course of the year 2020, such volcanic activity led to secondary effects on the crust, which is why the prediction of deformations becomes the task of geoscientists. In the course of this article, the use of tropospheric variables such as evapotranspiration, UV aerosol index, carbon monoxide, nitrogen dioxide, methane, surface temperature, among others, is used to train a set of neural networks that can predict the behavior of the resulting phase of an unrolled interferogram with the DInsar technique, whose main objective is to identify and characterize the behavior of the crust based on the environmental conditions. For the above, the collection of variables, the conformation of a generalized linear model and the set of neural networks were carried out. After the training of the network, the validation was performed with the test data, giving an MSE of 0.17598 and an associated r-squared of approximately 0.88454. The resulting model allowed obtaining a data set with good thematic accuracy, reflecting the behavior of the volcano in the year 2020 given a set of environmental characteristics.
Mots clés : Crustal deformation|TROPOMI|Neural networks|Volcanic activity|DInSAR
A105100HJ