B0519 - REMOTE SENSING OF COASTAL AND MARINE SYSTEMS

Learning outcomes

After an introduction to the field of remote sensing and image processing, we will focus on applications to coastal monitoring and currently open research questions. Students will acquire an operational knowledge of various remote-sensing tools and data types, with emphasis on their application in coastal areas, including, for example, the retrieval of shallow water quality, mapping salt marsh vegetation species, studying seagrass space-time distributions, change detection of coastal morphological structures, etc. Content will include theory, in-class laboratory exercises, and projects with environmental applications. Students will learn how to 1) critically evaluate the limits and the merits of currently available sensors, 2) select the remote sensing techniques and available data most suitable to solve a specific problem, 3) select and apply the most effective pre-processing and processing techniques, 4) assess the accuracy of their results.

Course contents

Satellite remote sensing has become in the last few decades a key tool for sea and coastal monitoring and research. Coastal environments often undergo rapid and extreme changes that are mainly related to (i) physical processes, such as sediment dynamics induced by hydrodynamic patterns or extreme meteorological events, (ii) biological processes, in connection with vegetation and algal dynamics, and (iii) anthropogenic pressure. Remote- and proximal-sensing provides data and tools to monitor such changes.

The course consists of lessons, practical activities (i.e. image processing using selected software), and a final project. During the course, students will learn the basics of remote sensing and image processing with applications to seas and coastal environments. Students will acquire a basic operational knowledge of various satellite remote-sensing tools, with specific hands-on applications on (1) change detection in coastal zones, focusing in particular on changes of the coastline; (2) mapping salt marsh vegetation and seagrass distribution; (3) the assessment of the main water quality parameters (as for example water temperature, solid suspended sediment, chlorophyll concentration). At the end of the course, students will develop a project that will allow them to apply the skills acquired during the course.

Readings/Bibliography

Main suggestions:

Canada Centre for Remote Sensing. Fundamentals of Remote Sensing, http://www.nrcan.gc.ca/earth-sciences/geography-boundary/remote-sensing/fundamentals/1430

Tempfli et al. Principle of Remote Sensing – An introductory textbook, https://webapps.itc.utwente.nl/librarywww/papers_2009/general/principlesremotesensing.pdf

Slides and other readings will be provided.

Teaching methods

Theoretical lessons will be complemented with readings of research articles that will be assigned to students. The course will include a strong operational component to be developed in class using personal laptops and specific software. After an introductory week, the first lesson of each week will illustrates the concepts and analytical frameworks relevant to that week’s topic while the second lesson will be dedicated to in-class activities based on image and data processing. Each activity has the objective to familiarize students with the technical tools and concepts needed to apply remote sensing at the analyses of marine and coastal systems.

Considering the type of teaching activities and methods, in order to follow this course students should have taken the e-learning Module 1- Safety General Training and Module 2- Sefety Specific Training [https://elearning-sicurezza.unibo.it/]

Assessment methods

The practical training will include exercises that will be evaluated during the course and will be part of the final grade. An individual project will be developed by each student for the final exam. The final oral exam will include the presentation of the project as well as answering questions regarding the project and other subjects of the course.

Teaching tools

The practical training will include activities that aim at providing basic knowledge in using and analyzing remote sensing data. Students are required to bring their own laptops. The software used for the training will be exclusively open access, as for example QGIS, SNAP and MultiSpec.

Students who need compensatory tools for reasons related to disabilities or specific learning disorders (SLD) can directly contact the Service for Students with Disabilities (disabilita@unibo.it [mailto:disabilita@unibo.it] ) and the Service for Students with learning disabilities (dsa@unibo.it [mailto:dsa@unibo.it] ) to agree on the adoption of the most appropriate measures.

Office hours

See the website of Sonia Silvestri