Measuring Vegetation Lab
A.Y. 2025/2026
Learning objectives
To become familiar with the type of data (and derived indexes) useful to measure vegetation and its condition, how to collect such data, the available databases and technologies/tools employed to get them.
To practice on data acquisition for an area of interest using specific databases (satellite data) or multi-spectral cameras mounted on drones (only for areas of interest easily accessible and in close proximity, e.g. within the Lombardy region).
To learn how to interpret data and derived indexes in order to understand the ongoing phenomena (land use changes, growth stage of the vegetation, yield, health/nutritional status) and causes thereof.
To practice on data acquisition for an area of interest using specific databases (satellite data) or multi-spectral cameras mounted on drones (only for areas of interest easily accessible and in close proximity, e.g. within the Lombardy region).
To learn how to interpret data and derived indexes in order to understand the ongoing phenomena (land use changes, growth stage of the vegetation, yield, health/nutritional status) and causes thereof.
Expected learning outcomes
A student is expected to be able to:
1) identify the type of data required (wavelength and resolution) for the area of interest, how to obtain them, the type of tools/database needed, how to process them in order to get the derived indexes, and to store them in a reasonable timeframe;
2) correctly interpret the ongoing phenomena concerning vegetation cover on the basis of primary data and derived indexes in the area of interest.
3) present the results achieved for one or more area(s) of interest in written and oral form in a synthetic and complete manner
1) identify the type of data required (wavelength and resolution) for the area of interest, how to obtain them, the type of tools/database needed, how to process them in order to get the derived indexes, and to store them in a reasonable timeframe;
2) correctly interpret the ongoing phenomena concerning vegetation cover on the basis of primary data and derived indexes in the area of interest.
3) present the results achieved for one or more area(s) of interest in written and oral form in a synthetic and complete manner
Lesson period: Second semester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
The introductory lectures will focus on the physical basis of remote sensing, the type of data, their resolutions (spatial, temporal, spectral and radiometric), data repositories and historical series, the indexes used to describe vegetation status (NDVI [Normalized Difference Vegetation Index], LAI [Leaf Area Index], EVI [Enhanced Vegetation Index]...) their interpretation and representation using QGIS and the Google Earth Engine platform.
Examples are presented on how to use remote sensing data to highlight patterns and trends in land use change, health, growth and yield of vegetation cover, the effect of traumatic events (storms, floods, fires ) or anthropic disturbances.
Each student, either alone or in small groups, needs to identify an area of interest for which he/she needs to 1) gather quality data of spatial and temporal resolution adequate for the predetermined aim, and 2) calculate the relative indexes and their change over time. The selected areas of interest must undergo some type of change over time (e.g. due to some agricultural development or construction project) or exceptional events. The areas can be selected by the students on the basis of direct or indirect knowledge.
Depending on the availability of a drone with a multi spectral camera, a field trip shall be organized for direct data acquisition.
Examples are presented on how to use remote sensing data to highlight patterns and trends in land use change, health, growth and yield of vegetation cover, the effect of traumatic events (storms, floods, fires ) or anthropic disturbances.
Each student, either alone or in small groups, needs to identify an area of interest for which he/she needs to 1) gather quality data of spatial and temporal resolution adequate for the predetermined aim, and 2) calculate the relative indexes and their change over time. The selected areas of interest must undergo some type of change over time (e.g. due to some agricultural development or construction project) or exceptional events. The areas can be selected by the students on the basis of direct or indirect knowledge.
Depending on the availability of a drone with a multi spectral camera, a field trip shall be organized for direct data acquisition.
Prerequisites for admission
A basic understanding of remote sensing, plants and photosynthesis. A basic knowledge of GIS operations and familiarity with QGIS are useful.
Teaching methods
The introductory lectures will be delivered in a traditional format using powerpoint and practicing with live examples to familiarize with remote sensing data useful to measure vegetation, their characteristics and the relevant repositories to acquire and select remote sensing data (mainly from satellites and, where possible, from drones). The students are then asked, individually or in groups, to identify, in agreement with the instructors, one or more areas of interest for which they will gather satellite data (or, when possible, data collected with a drone).
Teaching Resources
Lecture slides as well as additional material employed during the laboratory (data, original literature, notes and bibliographic material) will be made available through the MyAriel website.
Assessment methods and Criteria
The exam shall focus on the material produced by the student at the end of the lab in the form of a written report (issue tackled, aim, methods employed, major achievements) and the related oral presentation.
BIO/04 - PLANT PHYSIOLOGY - University credits: 3
Lessons: 24 hours
Professor:
Morandini Piero Angelo
Professor(s)
Reception:
Please, contact me by email to fix an appointment
via Celoria 10, building 22120, floor -1