Lessons: Basics of Meteorology and Climatology: Atmosphere Composition, Weather and Climate, Climatology and crops. Agricultural Meteorology. Agro-climatic parameters: radiation, air/soil temperature and moisture, precipitation, evapotranspiration. Climate change. Crop modelling. Tools for for monitoring crops: digital cartography, GIS, remote sensing.
Practice: Exercises with GIS and crop models.
Agricultural Meteorology and Climatology (Lalic et al., 2018, Florence University Press)
Lessons notes.
Didactic material edited by the Professor.
Learning Objectives
Knowledge acquired:
Concepts essential for understanding: climate variables and their dynamics; relationships between climate and crops; techniques for crop monitoring and analyses; impacts of climate change.
Competence acquired:
Students will be able to assess the characteristics of meteo-climatic conditions of crops (spatially and temporarily) and of monitoring systems in tropical environment. Expected impacts of climate change, including mitigation and adaptation practices to cope with extreme events. Principle and basic concepts of crop modelling.
GIS: principles and basic concept on digital cartography and GIS domain. Spatial data characteristics and mining, Geoprocessing procedures, raster and vector data model, data harmonization, georeferencing, database management, spatial advanced procedures.
REMOTE SENSING: principles and basic concept on remote sensing. Satellite images treatment and analysis. Vegetation indexes. Classification maps. Validation of classifications
Skills acquired (at the end of the course):
Monitoring and analysis of the climate. Analysis of the relations between climate and plant in tropical environments. Climate change impacts on crops and mitigation and adaptation strategies.
Capacity to make spatial analysis within a GIS domain. Spatial data mining. Capacity to make remote sensing analysis.
Learning the use of tools for the analysis and generation of meteorological data (climate generators) and the analysis of crop productivity in reference to the pedo-climatic and management context (crop simulation models)
Prerequisites
Agronomy, Ecophysiology
Teaching Methods
CFU: 9
Total hours of the course (including the time spent in attending lectures, seminars, private study, examinations, etc...): 150
Hours reserved to private study and other individual formative activities: 96
Contact hours for: Lectures (hours): 24
Contact hours for: Laboratory (hours):
Contact hours for: Laboratory-field/practice (hours): 24
Seminars (hours): 0-2
Stages: 0
Intermediate examinations: 0
Further information
Frequency of lectures, practice and lab, although not compulsory, is strongly recommended.
Type of Assessment
Exam modality: Written text with multiple answers and exercises.
Course program
Weather and Climate; Agroclimatology, Agrometeorology and their role in agriculture; Elements of climate; Climate classifications; The climate system; The atmosphere and its composition; Radiation and the energy balance; Temperature; Air and Soil Humidity; Precipitation; Wind; Weather & Crops: Photosynthesis, Photoperiodism, Phototropism, Optimal and critical temperature, thermal accumulation, Thermoperiodism, Vernalization, Dormancy, Risks from hot and cold temperatures, water effect on crop productivity, effect of wind on plants. Climate change: causes of climate change; Observed temperature and precipitation changes; Emission scenarios, Prospected changes, Global circulation models, Downscaling, Tools for studying response to high CO2, Effect of climate change on crops, Direct and indirect effects, Effects on the main components of the agrosystem, Definition and classification of adaptation and mitigation strategies. Crop Modelling: Basic concepts and definitions, model classification,empirical and mechanistic models, static and dynamic models, deterministic and stochastic models, production levels and limiting factors, data needs, selection and evaluation of models.
Cartography: fundamentals, topographic database, projections and datum, the digital cartography.
GIS: spatial data, vector and raster data model, table of attributes, spatial projections, georeferencing, geoprocessing, join and spatial join, map composer,data conversion, queries and spatial queries
REMOTE SENSING: principles of remote sensing, main satellite for agriculture analysis, type of sensors, resolutions, raster images, raster calculator, satellite, spectral corrections, raster classification, vegetation indexes, classification evaluation, confusion matrix