Hyper-temporal remote sensing to support agricultural monitoring

The course presents an approach for improved mapping and differentiating spatial temporal facts at country level (agro-environmental stratification), using the best remotely sensed data and most modern interpretation/analysis methods.

The course is targeted at a broad range of producers and users of spatial and non-spatial agricultural statistics, analysts and technicians in geo-information organizations; national statistics offices and statistics assessment units of ministries of agriculture, as in early warning units, managers and decision makers will also find interesting ideas and examples in the proposed curricula materials.

Content of the course:

• Use of the hyper-temporal time-space domain
• Vegetation and remote sensing
• Acquisition and pre-processing of hyper-temporal Normalized Difference Vegetation Index (NDVI) data sets.
• Classification of hyper-temporal data
• How to visualize, interpret and analyze hyper-temporal data sets
• How to capture and display agricultural statistics, using NDVI-maps