D1 - Knowledge and understanding: Students will acquire knowledge on the basis of remote sensing techniques to analyse remotely-sensed images and to monitor and assess biodiversity from remote.

D2 - Applying knowledge and understanding: Students will be able to apply the techniques taught during the course to answer ecologically-sound research questions.

D3 – Making judgements: students will be able to apply the acquired knowledge to judge and plan adequate remote sensing analyses related to the research question addressed/application requested.
D4 - Communication skills: students will be able to improve their communication skills through the preparation of an oral presentation of the group work needed for the exam.

D5 - Learning skills: Students will be stimulated to improve auto-learning skills by developing a project based on the knowledge acquired during the course.

Knowledge of fundamental of cartography and basic GIS techniques.

PART 1: Geographic Information Systems (GIS) as tools for managing environmental data. Free and open source GIS software. Computer laboratory exercises.
PART 2: Physical principles of remote sensing. Types of satellites and sensors for Earth observation. Acquisition of satellite data freely downloadable. Import in GIS and R environment and visual interpretation. Computer laboratory exercises.
PART 3: Methodologies for the interpretation and processing of remotely sensed images. Computer laboratory exercises.
PART 4: Remote Sensing of Biodiversity. Principal techniques to measure biodiversity and environmental changes. Computer laboratory exercises.

Chuvieco E. Fundamentals of Satellite Remote Sensing, CRC Press, Taylor & Francis Group.
Emery W. and Camps A. 2017. Introduction to Satellite Remote Sensing, Elsevier.
Horning N., Robinson J.A., Sterling E. J. and Turner W., 2010. Remote Sensing for Ecology and Conservation. Oxford University Press
Cavender-Bares J., Gamon J.A. and Townsend P.A. 2020.Remote Sensing of Plant Biodiversity. Springer


Materials and links indicated on the course Moodle website/MS Teams

PART 1.
- Characteristics of geographic data.
- Definition of geodetic-cartographic system .
- Fundamentals of cartography.
- Definition of GIS.
- QGIS: free and open source software and accessibility to geographic data, software download and installation procedure.
- Spatial data representation model: vector model, raster model; layers e databases; main GIS operations (selection, transformation, buffering, map dissolve, merge, intersection, clip); land surveys and GPS;

PART 2.
Physical principles of remote sensing.
- Definition of Remote Sensing for Earth Observation;
- Components of Optical Remote Sensing system
- Electromagnetic radiation properties
- Subdivision of electromagnetic spectrum;
- Radiometric dimensions
- Spectral signatures in the Solar Spectrum.
- Emission of radiation by the Earth's surface; interaction of radiation with the atmosphere
- Transparency of the atmosphere (atmospheric windows)
- Satellite acquisition systems

Types of satellites and sensors for Earth observation.
- Remote sensing platforms;
- Components of a remote sensing system
- Active and passive sensors;
- Sensor resolution: geometric, spectral, radiometric, temporal;
- Analog-digital conversion;
- Digital image concept;
- Spectral Bands (Multispectral Image)
- Landsat and Sentinel satellite series;
- Shuttle Radar Topograpgy Mission (STRM);
- Unmanned aerial vehicle

PART 3
Methodologies for the interpretation and processing of remotely sensed images.
- Digital volume
- Processing remote sensing images
- Pre-processing: radiometric and atmospheric corrections;
- Histogram and scatterplot;
- Short notes on color theory;
- Enhancement of black and white images;
- True and false colors composition (RGB);
- Generation of continuous variables
- Principal Component Analysis (PCA);
- Arithmetic operation between spectral bands: Vegetation indices

PART 4:
- Remote Sensing of Biodiversity.
- Change detection
- Multispectral image classification: Unsupervised classification; Supervised classification.
- Remote sensing applications: case studies.

Lectures, exercises in the computer lab, group work supervised by the teacher.

Slides shown during lessons, as well as additional study material, will be made available on moodle/MS Teams.

The exam includes the collective presentation of the group work and for each student an oral test on theoretical knowledge. The final grade awarded as follows: 25% on group work, 75% on the oral exam.
Any changes to the procedures described here, which may be necessary to ensure the implementation of safety protocols related to any emergency situations, will be communicated on the Department's website, the Study

This course deepens topics strictly connected to one or more UN Sustainable Development Agenda 2030 goals.