Remote Sensing for Geosciences

Period: first semester

Course Units Contents: 

28 h lectures + 30h practical exercises
Theoretical concepts: physical principles and spectrophotometry.

Remote sensing platforms: introduction to technology such as satellites and drones (and associated sensors) to generate remotely sensed information.

Image analysis:
- Image pre-processing: atmospheric correction, geocoding, contrast enhancements, and convolution filters;
- Image classification: Unsupervised methods such as band ratios and spectral indexes (e.g., vegetation indexes), Principal Component Analysis, and clustering; Supervised methods based on machine learning algorithms; time series image classification.

Photogrammetry: introduction to SfM “Structure from Motion” technique to generate orthophotos and digital elevation model from drone acquisitions and 3D object reconstruction.

In the laboratory the student will utilize GIS (Geographic Information Systems), the language Python, Google Earth Engine and Colab.

24h of lectures (3 CFU, only for students of the master in ENVIRONMENTAL SUSTAINABILITY AND EDUCATION)
Techniques and indices applied in the analysis of the biological component of ecosystems. Evaluation of the global state of vegetation and analysis of its evolution in response to changes of environmental parameters. Interpretation of the NDVI, EVI and LAI vegetation indices and of data collected by the sensors of Eddy Covariance Flux Towers.

Planned learning activities and teaching methods:  

Frontal lectures with exercises; laboratory using Google Earth Engine and Colab (Python).

Students can use generative AI tools during their studies but are encouraged to compare their replies with the study materials covered in class and to come back to the teacher with questions that may rise from it.
No aiding tool will be allowed during the final test, this includes generative AI, phones, smartwatches, notes, books, etc.

In addition to contacting the course instructor, students with disabilities, specific learning disorders, special educational needs, or other health conditions may reach out to the Student Services Office – Inclusion Section to receive more information about available teaching support and tools.