Remote Sensing for Agriculture
A.Y. 2023/2024
Learning objectives
The course aims to provide basic knowledge of multispectral optical remote sensing for environmental and agronomic applications. Explanation of physical principles of optical remote sensing, particularly with regard to the spectral response of vegetation, will be provided and characteristics of the main earth observation systems available will be presented. Emphasis will be placed on free satellite data at medium spatial resolution (e.g. Copernicus data) useful for land- and farm-scale applications. Techniques for processing remotely sensed images and their use in creating thematic maps will be explained.
Expected learning outcomes
- investigate image archives and obtain remotely sensed data
- Identify the most appropriate techniques for processing multispectral imagery and multitemporal data to generate information useful for the characterization of agricultural systems and optimized management of agricultural crops.
- critically interpret remotely sensed data in relation to variables of agronomic interest, crop system processes and environmental dynamics.
- Manage geo-spatial data and use analysis application software within workflows specific to Digital Agriculture.
- Identify the most appropriate techniques for processing multispectral imagery and multitemporal data to generate information useful for the characterization of agricultural systems and optimized management of agricultural crops.
- critically interpret remotely sensed data in relation to variables of agronomic interest, crop system processes and environmental dynamics.
- Manage geo-spatial data and use analysis application software within workflows specific to Digital Agriculture.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
The course is made of 6 credits (CFU). 4 CFU corresponding to 32 hours of lectures, including seminars and practical demonstrations with dedicated software and 2 CFU consisting in 32 hours of hands-on computer lab activities.
The lectures focus on concepts and physical principles of remote sensing for environmental and agricultural spatial applications aimed at the creation of thematic mapping: i) recognition of land-use classes present in a territory, ii) assessment of the state of crops by analysis of vegetation indices, iii) approaches for estimating biophysical parameters, iv) identification of inter-field and intra-field variability, and iv) to the analysis of temporal dynamics.
The following topics will be presented:
· Physical principles of remote sensing
· Spectral response of vegetation and soils
· Acquisition systems and characteristics of digital images
· Visualization, interpretation and statistical exploration of multispectral digital images
· Computation and interpretation of vegetation indices
· Approaches for creating thematic maps
· Agricultural applications and presentation of case studies
The laboratory deals with open source tools to investigate free data archives (e.g. Sentinel data-Copernicus Program), download, process and interpret multispectral optical satellite data.
In particular, the following topics will be covered:
· Search and download of Sentinel-2 satellite data
· Basic tools for the management of satellite data and basic operations for vegetation indices computation
· Interpretation of multispectral and multitemporal satellite data
· Presentation of approaches for creating thematic land use maps
· Presentation of approaches for creating maps of biophysical parameters
· Presentation of approaches for identifying management units
· A practical case study
The lectures focus on concepts and physical principles of remote sensing for environmental and agricultural spatial applications aimed at the creation of thematic mapping: i) recognition of land-use classes present in a territory, ii) assessment of the state of crops by analysis of vegetation indices, iii) approaches for estimating biophysical parameters, iv) identification of inter-field and intra-field variability, and iv) to the analysis of temporal dynamics.
The following topics will be presented:
· Physical principles of remote sensing
· Spectral response of vegetation and soils
· Acquisition systems and characteristics of digital images
· Visualization, interpretation and statistical exploration of multispectral digital images
· Computation and interpretation of vegetation indices
· Approaches for creating thematic maps
· Agricultural applications and presentation of case studies
The laboratory deals with open source tools to investigate free data archives (e.g. Sentinel data-Copernicus Program), download, process and interpret multispectral optical satellite data.
In particular, the following topics will be covered:
· Search and download of Sentinel-2 satellite data
· Basic tools for the management of satellite data and basic operations for vegetation indices computation
· Interpretation of multispectral and multitemporal satellite data
· Presentation of approaches for creating thematic land use maps
· Presentation of approaches for creating maps of biophysical parameters
· Presentation of approaches for identifying management units
· A practical case study
Prerequisites for admission
No prerequisites are required; however, knowledge of the fundamentals of Mathematical Analysis (function study, total and partial derivatives, integrals), Physics (electromagnetism and optics) and Statistics (treatment of observations) is considered useful.
Teaching methods
The classes include lectures, seminars, practical demonstrations and the presentation of a case studies on precision agriculture.
The computer laboratory provides students with hands-on experience on exploration, processing and exploitation of remote sensing data for precision agriculture purposes.
Attendance is strongly recommended.
The computer laboratory provides students with hands-on experience on exploration, processing and exploitation of remote sensing data for precision agriculture purposes.
Attendance is strongly recommended.
Teaching Resources
TEACHING UNIT: "Analysis of spatial variability in agriculture"
For the introductory part, relative to the mathematical topics:
Stewart, "Calculus", Brooks/Cole Pub Co
Greenwell, Ritchey, Lial, "Calculus for the Life Sciences", Pearson
Stewart, Day, "Biocalcucus: Calculus for the Life Sciences", Brooks/Cole Pub Co
Robert A. Adams and Christopher Essex, "Calculus: A Complete Course", 9th Edition, Pearson
For the part relative to geostatistics:
Webster&Oliver, "Geostatistics for Environmental Scientists", Wiley
Oliver, "Geostatistical applications for Precision Agriculture", Springer
Marsily, "Quantitative Hydrogeology", Academic Press Inc
Isaaks&Srivastava, "An Introduction to Applied Geostatistics", Oxford University Press
TEACHING UNIT: "Remote sensing for agriculture"
On lectures:
Slides displayed during the lessons.
Principi e metodi di telerilevamento - Brivio P.A., Lechi G., Zilioli E., Ed. Città Studi, 2006
Elementi di geomatica. - Gomarasca Mario A. Editore: ASITA, 2004
ASRAR G., (1989). Theory and applications of optical remote sensing - Ed:John Wiley & Sons New York, 1989 XIV, 734 pp.
RICHARDS, J.A., (1993): Remote Sensing Digital Image Analysis. An Introduction, 2nd Ed., Berlin, Springer-Verlag.
Lillesand T. & Kiefer R. (2000): Remote sensing and image interpretation - 4. ed
LIANG S. (2004). Quantitative Remote Sensing of Land Surfaces, John Wiley & Sons, 534 p.
Jensen J. R. (2006). Remote Sensing of the Environment: An Earth Resource Perspective, Prentice Hall, 608 p.
On lab:
Tutorial on the activities performed during the classes and a template of the technical report.
Agricoltura Di Precisione - Casa R., 2016, Edagricole
R tutorials: (https://rcompanion.org/rcompanion/, https://geocompr.robinlovelace.net/, https://www.r-bloggers.com/, http://ww2.coastal.edu/kingw/statistics/R-tutorials/, http://zoonek2.free.fr/UNIX/48_R/02.html, https://cran.r-project.org/doc/contrib/Lemon-kickstart/)
QGIS tutorials: (https://www.qgistutorials.com/en/, https://docs.qgis.org/testing/en/docs/training_manual/)
SNAP tutorials: (https://step.esa.int/main/doc/tutorials/, https://step.esa.int/main/doc/tutorials/snap-tutorials/)
For the introductory part, relative to the mathematical topics:
Stewart, "Calculus", Brooks/Cole Pub Co
Greenwell, Ritchey, Lial, "Calculus for the Life Sciences", Pearson
Stewart, Day, "Biocalcucus: Calculus for the Life Sciences", Brooks/Cole Pub Co
Robert A. Adams and Christopher Essex, "Calculus: A Complete Course", 9th Edition, Pearson
For the part relative to geostatistics:
Webster&Oliver, "Geostatistics for Environmental Scientists", Wiley
Oliver, "Geostatistical applications for Precision Agriculture", Springer
Marsily, "Quantitative Hydrogeology", Academic Press Inc
Isaaks&Srivastava, "An Introduction to Applied Geostatistics", Oxford University Press
TEACHING UNIT: "Remote sensing for agriculture"
On lectures:
Slides displayed during the lessons.
Principi e metodi di telerilevamento - Brivio P.A., Lechi G., Zilioli E., Ed. Città Studi, 2006
Elementi di geomatica. - Gomarasca Mario A. Editore: ASITA, 2004
ASRAR G., (1989). Theory and applications of optical remote sensing - Ed:John Wiley & Sons New York, 1989 XIV, 734 pp.
RICHARDS, J.A., (1993): Remote Sensing Digital Image Analysis. An Introduction, 2nd Ed., Berlin, Springer-Verlag.
Lillesand T. & Kiefer R. (2000): Remote sensing and image interpretation - 4. ed
LIANG S. (2004). Quantitative Remote Sensing of Land Surfaces, John Wiley & Sons, 534 p.
Jensen J. R. (2006). Remote Sensing of the Environment: An Earth Resource Perspective, Prentice Hall, 608 p.
On lab:
Tutorial on the activities performed during the classes and a template of the technical report.
Agricoltura Di Precisione - Casa R., 2016, Edagricole
R tutorials: (https://rcompanion.org/rcompanion/, https://geocompr.robinlovelace.net/, https://www.r-bloggers.com/, http://ww2.coastal.edu/kingw/statistics/R-tutorials/, http://zoonek2.free.fr/UNIX/48_R/02.html, https://cran.r-project.org/doc/contrib/Lemon-kickstart/)
QGIS tutorials: (https://www.qgistutorials.com/en/, https://docs.qgis.org/testing/en/docs/training_manual/)
SNAP tutorials: (https://step.esa.int/main/doc/tutorials/, https://step.esa.int/main/doc/tutorials/snap-tutorials/)
Assessment methods and Criteria
The exam consists in a written report on laboratory activities and an oral exam.
- The written document will have the structure of a technical / scientific report and should be delivered before the oral test. This is mandatory for oral test admission.
- The oral exam consists in the discussion of the provided report and includes questions related on lectures topics.
- The written document will have the structure of a technical / scientific report and should be delivered before the oral test. This is mandatory for oral test admission.
- The oral exam consists in the discussion of the provided report and includes questions related on lectures topics.
ICAR/06 - SURVEYING AND MAPPING - University credits: 6
Computer room practicals: 32 hours
Lessons: 32 hours
Lessons: 32 hours
Professors:
Boschetti Mirco, Oberti Roberto
Professor(s)
Reception:
make an appointment
via Celoria 2 - Building 10: Ingegneria Agraria