OLU4Africa

In African countries, where land cover and land use datasets currently exist, the data suffer from patchy coverage, outdated concurrency and unknown but assumed to be low accuracy and/or restricted access. Homogeneous data that allow regional and inter-regional analysis across regional and country boundaries are all but absent, yet critical in a continent where many boundaries were drawn as straight lines on small scale maps whereas ecology and natural boundaries are quite different, and developments made on one side of a boundary has a significant impact also on the other side. In the regions with a rapid rate of development, industrialization and intensification of primary production, the importance of targeted and informed policies, effective strategies and operational decision support are inestimable both in fostering new sustainable economic activity – and in mitigating negative environmental externalities from current modes of production. This creates demands to harmonise LULC data to compare them between countries and to compile time series to analyse change dynamics and detect trends. The Open Land Use (OLU) database is an advanced seamless database capable of doing such things.

Particularly, the OLU4Africa 2.0 covers selected territorial units with a seamless layer, which provides information on various topics on selected reference geometries. A combination of previously existing data Africover and (European Space Agency Climate Change Initiative) ESA CCI Land Cover 2016 from previous mapping activities with OpenStreetMap (OSM) allows for building maps with much better details than the previous mapping. This first step is easy and fully automated and allows to build basic maps of selected Eastern African countries in a matter of a day. Having such detailed basic geometry allows us to incorporate also modified Geographic Object-Based Image Analysis (GEOBIA) and provide interpretation of objects from images, not just single pixels. This can help us better interpret objects, where images are very fragmented. We are also able to integrate selected indexes from different time periods and compare dynamic changes in vegetation.

The original purpose of the LULC was mainly for spatial planning and investment, agriculture, landscape development, etc. Our current ambition is to create a model and database that will support the creation of various models of landscape development and scenarios and support the building of large-scale digital models. Our aim was to verify the new OLU 2.0 data model in multiple areas of human activity for regions in Africa.