Webinar: introduction to the High Resolution Land Cover Map

This webinar - hosted by the aiforgood platform - presents the architectures and the methodologies for implementing the full processing chains that have been developed to process Earth Observation data and generate the products relating to the European Space Agency (ESA) Climate Programme, the Climate Change Initiative (CCI) High Resolution Land Cover project.

The project aims to generate high resolution (10/30m) land-cover and change detection maps at subcontinental/regional level to study the role of the spatial resolution in climate modelling research.

Land cover is one of the main environmental climate variables that is highly correlated with climate change. The role of land for storing carbon and its future potential for offsetting carbon emissions is an area of active research.

Special focus will be given to the:

• data processing and machine learning approaches used
• adopted cascade paradigm to multitemporal data classification and
• procedures used for model training and map validation. These steps are very complex considering the requirements to work at large scale with multisensor (multispectral and SAR) images and heterogeneous data quality moving since 1990 to nowadays.

The primary products of the project consist of:

• land-cover maps at subcontinental scale at 10m (generated for 2019 only) as reference static input to the climate models
• a long-term record of regional land cover maps at 30m for the historical analysis every 5 years (generated in the period 1990-2019), and
• change information at 30m at yearly scale consistent with historical land-cover maps.