Mapping landscapes of Africa using remote sensing data: detecting spatio-temporal environmental dynamics from the satellite images

This presentation proposes research on mapping landscapes of Africa using remote sensing data: detecting spatio-temporal environmental dynamics from the satellite images. The presentation is held on 13 June at the University of Salzburg. The presented research covers the problem of extracting knowledge and information from Earth Observation (EO) data which requires advanced technical cartographic tools. In particular, I presented the use of methods of machine learning (ML) and algorithms deep learning (DL) as well as scripting approaches to geospatial data handling. The concept of the study: Landscapes of Africa. Research focus: land surface of the African continent where diverse environmental processes interplay. Understanding landscape dynamics requires modelling and mapping the complexity of factors that affect the shape of the Earth using advanced methods of EO data processing. Landscape dynamics was analysed on several case study that demonstrate the evaluation of spatio-temporal changes caused by human and natural forces across various countries of Africa. Applications of landscape ecology and environmental monitoring of Africa were discussed on the example of landscape monitoring. Possible applications include land management (urban planning), diverse goals of sustainable development (food resources, agriculture) and theoretical issues of cartography and geoinformatics. Factors affecting formation of landscapes are reviewed in the published papers. These incldue geologic-tectonic setting, climate processes, anthropogenic activities in various countries across the African continent which is notable for different relief, soil and vegetation setting.