Remote Sensing for Agriculture

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.

- 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.