Assessment and monitoring of natural resources requires detailed, and up-to-date geospatial information on land cover (LC), land use (LU) and their changes over time. The LCLU information is essential for a broad range of users and applications. It is crucial for land management, monitoring of sustainable development of agriculture, forestry, rural areas, assessment of biodiversity status and losses, urban planning and land uptake. LCLU is also essential for various reporting obligations, for example, for counting greenhouse gas (GHG) emissions and removal from the Land Use, Land Use Change and Forestry (LULUCF) sector, a long-term climate mitigation, greening of Common Agricultural Policy (CAP), Biodiversity Conservation, Urban Agenda and plans for the upcoming Energy Union. Each of these regulations requires different level of details on land cover, land use and changes. The products of the Copernicus Land Monitoring Service are to some extent used in national research projects, but rarely in national mapping, reporting and monitoring programs carried out by national and regional authorities.

The main goal of InCoNaDa is to improve the user uptake of land cover and land use information derived from the integration of Copernicus Land Monitoring Services (CLMS) and national databases.
The proposed project will address the request for more detailed information on LCLU and its changes (in respect to spatial, temporal and thematic content), than is currently provided in Corine Land Cover (CLC) databases. Furthermore, the assessment of usefulness of enhanced LCLU database and CLMS products for decision makers, reporting obligations in natural resources monitoring, urban and spatial planning, agricultural management and reporting greenhouse gases emissions and removals from LULUCF in Poland and Norway.

The proposed project will address the following objectives:
1) to determine the most accurate land cover map based on a time series of Sentinel-2 data
using machine learning approaches;
2) to verify the EAGLE concept by developing and testing an approach for integration and population of land use information and delivering the enhanced LCLU database;
3) to design and develop web-based application enabling to query the enhanced LCLU database as well as to integrate and extract statistics from the CLMS adjusted to the user needs;
4) to proof if and how enhanced LCLU database and CLMS can be used in spatial planning;
5) to proof if and how the enhanced LCLU database and CLMS can be used in the agricultural management and environmental monitoring;
6) to demonstrate the usefulness of the enhanced LCLU database and CLMS for reporting GHG emissions and removals from LULUCF.