B5817 - TELERILEVAMENTO GEO-ECOLOGICO IN R

Academic Year 2024/2025

Learning outcomes

At the end of the course, each student will gather knowledge on the main principles shaping remote sensing from both a theoretical and practical point of view, with specific applications to Geology and Ecology. In particular, each student will be able to: • understand the main components related to satellite imagery (spatial radiometric, spectral and temporal resolutions), • gather suitable data for the main theme of interest and the scale of the study, • locate the main sources of remote sensing data, • interpret satellite images with respect to their spectral resolution, • calculate geological and ecological indices for characterizing landscapes, • use free and open source software for managing and analyzing remote sensing data, by implementing open source code.

Course contents

- The roots of remote sensing: introduction to the basic concepts related to remote sensing


- Reference systems: introduction to the main coordinate systems


- A matter of scale: main issues related to the analysis of remotely sensed data at different spatial scales, hierarchy theory, upscaling e downscalng


- Spatial data and Free and Open Source Software: how to obtain free spatial data and software on the web


- Visualising multi- e hyper-spectral data


- Satellite data pre-processing: radiometric correction; how to clean satellite images from atmospheric effects


- Spectral indices extracted from satellite imagery


- Generating land cover maps from remotely sensed data


- Land use change in space and time


- Continuous information of land cover


- Time Series Analysis:
multitemporal analysis, analysing changes based on map overlay


- Spatial pattern analysis by landscape metrics


- Species distribution modelling by using remotely sensed data


During the course we will make use of free and open source software such as R and GRASS GIS, which implement modules specifically dedicated to remote sensing. At the end of the program students will be able to analyse remote sensing data, by directly coding their own analysis. The Professor will also make two seminars on "scientific writing for lazy people" on the use of LaTeX for saving time and energy and let the computer do the job!


Crucial note (!): no preliminary knowledge on
geo- o eco-informatics is needed. We will start from scratch!

Readings/Bibliography

# Books
- Jensen, J.R. (2015). Introductory Digital Image Processing: A Remote Sensing Perspective. Pearson College.
- Wegmann, M., Leutner, B., Dech, S. (2016). Remote Sensing and GIS for Ecologists: Using Open Source Software. Pelagic Pub Ltd.


# Interesting journals:
- GEO-: Computers & Geosciences: https://www.journals.elsevier.com/computers-and-geosciences
- ECO-: Ecological Informatics: https://www.journals.elsevier.com/ecological-informatics

Teaching methods

The Course has a profoundly practical components. Few words, a lot of code, a lot of amusement... R rules!

Assessment methods

Students will prepare a personal project in R, by presenting it during the exam, together with the used code.

Teaching tools

- Free satellite images

- Free software

- Online presentations

- Online PDFs on the code produced

Office hours

See the website of Duccio Rocchini