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A group of students from the Master in Big Data Science wins the first phase of challenge 'Minsait Land Classification' of Cajamar University Hack 2020

Students will represent the University of Navarra in the national phase of the soil classification competition.

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The dataset contains a list of surfaces on which the satellite image has been cropped and a series of characteristics of their geometries have been extracted.
PHOTO: Courtesy
06/04/20 19:14 Natalia Rouzaut

The Hakuna Datata group, formed by students of the Master in Big Data Science of the University of Navarra, has won the first phase of the challenge 'Minsait Land Classification' of the Cajamar University Hack 2020 Datathon and will represent the University in the national phase. This is the III edition of the contest, organized by Cajamar Data Lab, which is aimed at students from the best data science training centers in Spain.

The challenge 'Minsait Land Classification' sought to have students develop the best automatic land classification model based on images provided by the Sentinel II satellite of the European Space Agency' s Copernicus service. Using R and Python programs and machine learning techniques, they had to classify a set of cadastral farms associated with a list of attributes extracted from the image.

To do this, the students first cleaned and enriched the data, which allowed them to achieve a high correspondence with reality. Then, they modeled the data with the Gradiant Boosting and Random Forest binary classification models.

The Hakuna Datata team is formed by Pablo Jordán de la source, Gabriel López Font and Manuel Alberto Mosquera Belfort. During this second phase, which ends on April 22, they will be able to improve their work on the same datasets and with the same goal.

The Master's Degree in Big Data Science at the University of Navarra is coordinated this academic year by the Institute for Culture and Society (ICS) and, starting next year, by the Institute of Data Science and Artificial Intelligence, attached to TECNUN School of Engineering.

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