Biodiversity

Remote Sensing for Change Detection

This course explores techniques for detecting and analyzing changes in the Earth’s surface using multi-temporal remote sensing data. Students learn image preprocessing, temporal analysis, and key change detection methods such as image differencing, post-classification comparison, and machine learning approaches. Practical exercises with GIS and remote sensing software enable hands-on experience in monitoring land use, urban growth, deforestation, and environmental changes. By the end, participants can design change detection workflows, interpret results, and apply findings for research, planning, and environmental management.

Quelques photos prises lors de missions réalisées dans différentes régions d’Algérie

Quelques photos prises lors de missions effectués en différentes régions d'Algérie montrant la richesse floristique de nos forets dans l 'ordre ; cedrus atlantica(chrea); chene zeen (akfadou); juniperus thurifera (batna);pinus canariensis (colline jardin d'essai); pinus halepensis (foret saida);pinus nigra (jurjura) quercus canariensis (akfadou) ; qurcus suber (yakouren).

Mobilizing primary biodiversity data for Mozambican species of conservation concern

Mozambique, heavily dependent on natural resources, faces increasing pressure on its biodiversity. This project aims to digitize data on endemic species and create Red Lists to support sustainable decision-making.