Remote sensing of agro-environmental change
A.A. 2024/2025
Obiettivi formativi
Earth observation (EO) through remote sensing (RS) technologies and methods is nowadays a fundamental disciplinary field to analyze and monitor the status and changes of agroecosystems and environmental processes. EO approaches at multiple scale have become part of daily work for scientist, land managers and professional addressing global and regional challenges, and a fundamental instrument to inform international environmental policies.
This class aims at introducing the main principles and methods of RS and the use of the information collected from sensor on board of Earth-observing satellites and other platforms (airplanes, drones, ground) to study agro-environmental processes. The class conveys current RS applications for addressing global/regional challenges (e.g., food security, biodiversity conservation, climate change, sustainable farming) with selected case studies from ongoing research or implementation projects. Students will be guided in gaining practical skills to handle remote sensing data and develop processing flows and will be encouraged in acquiring analytical and critical thinking competences on how to address complex environmental challenges using EO approaches and data products.
This class aims at introducing the main principles and methods of RS and the use of the information collected from sensor on board of Earth-observing satellites and other platforms (airplanes, drones, ground) to study agro-environmental processes. The class conveys current RS applications for addressing global/regional challenges (e.g., food security, biodiversity conservation, climate change, sustainable farming) with selected case studies from ongoing research or implementation projects. Students will be guided in gaining practical skills to handle remote sensing data and develop processing flows and will be encouraged in acquiring analytical and critical thinking competences on how to address complex environmental challenges using EO approaches and data products.
Risultati apprendimento attesi
By the end of the course, students should be able to:
- Illustrate the basics of RS principles, methods, processing workflow and applications
- Use tools for finding, visualizing, pre-processing and analyzing RS imagery
- Critically evaluate and compare different EO operational products and applications/services
- Assess opportunities and trade-offs in EO environmental applications' design
- Articulate complexity and challenges in addressing global/regional environmental changes using RS technologies.
- Illustrate the basics of RS principles, methods, processing workflow and applications
- Use tools for finding, visualizing, pre-processing and analyzing RS imagery
- Critically evaluate and compare different EO operational products and applications/services
- Assess opportunities and trade-offs in EO environmental applications' design
- Articulate complexity and challenges in addressing global/regional environmental changes using RS technologies.
Periodo: Primo semestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento può essere seguito come corso singolo.
Programma e organizzazione didattica
Edizione unica
Responsabile
Periodo
Primo semestre
Programma
Programma
LU1. Fundamentals of remote sensing (RS) and Earth Observation (EO)
This learning unit introduces RS and EO as a discipline, its physical principles, and the main physical quantities that needs to be known to understand RS and EO applications. It also presents the reflectance signatures concept and examples for different land surfaces.
LU2. EO images, sensors and platforms
This learning unit covers the general concepts of RS measurements and image acquisition and presents the main EO missions and their features. Practical exercises include the exploration of data platforms to find and download EO data and the visualization of EO imagery.
LU3. EO data processing
This learning unit focuses on the main pre-processing steps needed to convert an image expressed in digital number (DN) values into reflectance. The focus will be mainly practical using available tools.
LU4. Image analysis, classification and change detection
This learning unit introduces methodologies for EO image classifications, accuracy assessment, categorical map generation and detection of changes.
LU5. Quantitative analysis of land surfaces
This learning unit covers quantitative approaches to estimate land surface biophysical properties using statistical and physically based models.
LU6. EO and global/regional agro-environmental challenges
This cross-cutting learning unit covers practical EO applications to address environmental challenges and will be conducted during the whole course duration to stimulate ideas, debates, and critical thinking about EO as an instrument for land management and planning. Case studies will be discussed also with guest lecturers.
LU1. Fundamentals of remote sensing (RS) and Earth Observation (EO)
This learning unit introduces RS and EO as a discipline, its physical principles, and the main physical quantities that needs to be known to understand RS and EO applications. It also presents the reflectance signatures concept and examples for different land surfaces.
LU2. EO images, sensors and platforms
This learning unit covers the general concepts of RS measurements and image acquisition and presents the main EO missions and their features. Practical exercises include the exploration of data platforms to find and download EO data and the visualization of EO imagery.
LU3. EO data processing
This learning unit focuses on the main pre-processing steps needed to convert an image expressed in digital number (DN) values into reflectance. The focus will be mainly practical using available tools.
LU4. Image analysis, classification and change detection
This learning unit introduces methodologies for EO image classifications, accuracy assessment, categorical map generation and detection of changes.
LU5. Quantitative analysis of land surfaces
This learning unit covers quantitative approaches to estimate land surface biophysical properties using statistical and physically based models.
LU6. EO and global/regional agro-environmental challenges
This cross-cutting learning unit covers practical EO applications to address environmental challenges and will be conducted during the whole course duration to stimulate ideas, debates, and critical thinking about EO as an instrument for land management and planning. Case studies will be discussed also with guest lecturers.
Prerequisiti
Basic knowledge of physics, statistics and ecology
Metodi didattici
The class combines passive and active learning, practicals (with laptop and field/lab instruments) and project/group-based learning.
Materiale di riferimento
1. Class slides, videos and reading material provided during the course
Optional
2. Book: Tempfli, K., Huurneman, G., Bakker, W., Janssen, L. L., Feringa, W. F., Gieske, A. S. M., ... & Woldai, T. (2009). Principles of remote sensing: an introductory textbook. International Institute for Geo-Information Science and Earth Observation. (open source)
Optional
2. Book: Tempfli, K., Huurneman, G., Bakker, W., Janssen, L. L., Feringa, W. F., Gieske, A. S. M., ... & Woldai, T. (2009). Principles of remote sensing: an introductory textbook. International Institute for Geo-Information Science and Earth Observation. (open source)
Modalità di verifica dell’apprendimento e criteri di valutazione
Written exam and oral discussion. The written exam includes closed and open questions. Project/Group-based learning activities will be also part of the final evaluation.
Students with SLD or disability certifications are kindly requested to contact the teacher at least 15 days before the date of the exam session to agree on individual exam requirements. In the email please make sure to add in cc the competent offices: [email protected] (for students with SLD) o [email protected] (for students with disability).
Students with SLD or disability certifications are kindly requested to contact the teacher at least 15 days before the date of the exam session to agree on individual exam requirements. In the email please make sure to add in cc the competent offices: [email protected] (for students with SLD) o [email protected] (for students with disability).
Siti didattici
Docente/i
Ricevimento:
su appuntamento tramite e-mail
Dipartimento di Scienze e Politiche Ambientali (ESP), Via Celoria 10, Milano