Program

Monday 22 August 2022

Introduction to the Course and training objectives (school directors).  Student self presentation.

Statistical models and sampling design. Prof. Acutis, Prof. Perego.  First class: ANOVA (one way, factorial), regression (linear, non-linear and multiple). Second class: Sampling size, number of replications, and sampling design. Practical: Regression, general linear and mixed models. Sample size determination and power analysis.

Tuesday 23 August 2022

Conducting a meta-analysis in agro-environmental science”. Dr. Valkama.  First class: Literature search, data collection and database creation. Second class: Meta-analysis. Practical: Database creation and running a meta-analysis.

Wednesday 24 August 2022

Topography for agro-environmental modelling. Prof. Märker. First class: Fundamentals of Terrain analysis (TA). From soil catena to 3D landscape. Second class: Environmental process modelling with emphasis on soil erosion and storm flow. Practical: Examples and applications of TA. GIS-based assessment models for soil erosion.

Thursday 25 August 2022

Management and spatial assessment of the agro-environmental data. Dr. Schillaci, Prof. Saia. First class: Acquisition of reference databases, land cover, soil databases (e.g., LUCAS), weather and climate data), data processing and harmonization. Second class: Machine learning methods for soil and crop data modelling, (Boosted regression trees, Random Forest, ANN). Practical: Examples and applications of Soil Organic Carbon modelling using R and GIS.

Friday 26 August 2022

Machine learning and Geostatistics for environmental modelling. Dr. Veronesi, Prof. Lipani. First class: Geostatistics and Machine learning as a tool for agro-environmental modelling, land cover mapping, vegetation indices. Second Class: Deep learning classification of satellite images using convolutional neural networks, examples and applications using Pyton, R and GIS. Practical: Examples and applications of machine and deep learning.