Class Data Science for Forestry and Agricultural Applications

This course presents the main concepts, techniques, and applications of data science in forestry and agricultural applications.

Not applicable

1. Assimilate the basic principles and techniques used in data science applications for physical forest space and precision agriculture applications. 2. RGB color compositions and vegetation indicies.. 3. Spectral signatures. 4. Automatic classification and assisted classification of satellite images. 5. Forest applications: introduction to the physical forest space, forest occupation charts. 6. Applications of data science in the forestry field. 7. Precision agriculture: most common types of cultures. 8. Data processing used in agriculture, such as vegetation indices, process modeling, biophysical attributes of crops, temporal dynamics of crops, and agricultural geophysics. 9. Analysis of the main agricultural applications from a precision agriculture perspective: inference of agronomic processes.

The teaching methodology uses the expository method, using documents on illustrative slides (provided to students), as a way of presenting the subjects and solving practical exercises of data science techniques in relation to forestry and agricultural applications.   Evaluation: Continuous assessment, consisting of 1 theoretical test and 1 assignment, each corresponding to 50 % of the final grade. The practical work requires an oral presentation. The practical work requires the application of the syllabus learned and must be developed throughout the semester. All elements of the continuous assessment are mandatory and the students must have a minimum score of 7 points in each of the elements.

- Jensen, John R. - Remote Sensing of the Environment: An Earth Resource Perspective. Prentice Hall. Upper Saddle River. New Jersey. 2000. ISBN: ISBN: 0-13-489733-1. - Lillesand, Thomas; Kiefer, Ralph W.; Chipman, Jonathan - Remote Sensing and Image Interpretation. John Wiley and Sons. New York. London. 2015. ISBN: ISBN: 978-1-118-34328-9. - Richards, John A.; Jia, Xiuping - Remote Sensing Digital Image Analysis. Springer-Verlag. 2013. ISBN:ISBN: 978-3-642-30062-2.