Measuring Vegetation Lab
A.Y. 2023/2024
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 introduction will focus on sources of information, images and satellite data (Landsat, Sentinel-2, Zoom Earth, Google Maps ), the types of data available for free, at a cost or upon request (resolution, available spectral bands, historical time series, frequency ) and the accurate geolocation of the area of interest.
Description of parameters/indexes used to describe vegetation status: NDVI (Normalized Difference Vegetation Index), LAI (Leaf Area Index) and chlorophyll fluorescence. These will be explained in their meaning and with practical examples.
Remote sensing data are used to highlight: patterns and trends in land use change in areas of interest, health, growth and yield of vegetation cover, the effect of traumatic events (landslides, floods, fires) or anthropic disturbances.
The practical part of the course will concern two areas, one at national and one at international scale, to determine the status of vegetation and its evolution over time using remote sensing. The national site, when possible, will be selected among easily accessible sites, to organize a fieldtrip during the lab to acquire data using a multispectral camera mounted on a drone. The acquired data will be compared with data available from satellite sources.
For the international area, the focus will be on areas subject to change (e.g. areas with ongoing agricultural development or construction work). The areas can be selected based on direct or indirect knowledge by the students, but only satellite data or from already available platforms will be considered.
Description of parameters/indexes used to describe vegetation status: NDVI (Normalized Difference Vegetation Index), LAI (Leaf Area Index) and chlorophyll fluorescence. These will be explained in their meaning and with practical examples.
Remote sensing data are used to highlight: patterns and trends in land use change in areas of interest, health, growth and yield of vegetation cover, the effect of traumatic events (landslides, floods, fires) or anthropic disturbances.
The practical part of the course will concern two areas, one at national and one at international scale, to determine the status of vegetation and its evolution over time using remote sensing. The national site, when possible, will be selected among easily accessible sites, to organize a fieldtrip during the lab to acquire data using a multispectral camera mounted on a drone. The acquired data will be compared with data available from satellite sources.
For the international area, the focus will be on areas subject to change (e.g. areas with ongoing agricultural development or construction work). The areas can be selected based on direct or indirect knowledge by the students, but only satellite data or from already available platforms will be considered.
Prerequisites for admission
A basic understanding of plant morphology, plant taxonomy and photosynthesis. Basic knowledge of GIS operations.
Teaching methods
The introductory lectures will be delivered in traditional format using powerpoint and practicing with live examples to learn how to acquire and interpret remote sensing data (from satellite or drones). The students are then asked to identify, in agreement with the instructors, one or more areas of interest for which they will gather satellite data and, when possible, their own data with a multi spectral camera mounted on the drone made available by the lab course.
Teaching Resources
Lecture slides employed during the lab course will be made available as ppt or pdf files through the Ariel website, as well as additional material (data, original literature, notes and bibliographic material) in their own file format.
Assessment methods and Criteria
The exam shall focus on the material produced by the student at the end of the lab as a report and an oral presentation of the methods employed, content, and major achievements.
BIO/04 - PLANT PHYSIOLOGY - University credits: 3
Lessons: 24 hours
Professor:
Morandini Piero Angelo
Educational website(s)
Professor(s)
Reception:
Please, contact me by email to fix an appointment
via Celoria 10, building 22120, floor -1