Assessing the status and monitoring the trends of land cover dynamics in and around protected areas is of utmost importance for park managers and decision makers. Moreover, to support the Convention on Biological Diversity (CBD)’s Strategic Action Plan including the Aichi Biodiversity Targets, such efforts are necessary to set a framework to reach the agreed national, regional or global targets. The integration of land use/cover change (LULCC) data with information on habitats and population density provides the means to assess potential degradation and disturbance resulting from anthropogenic activities such as agriculture and urban area expansion. This study assesses the LULCC over a 20 year (1990–2000–2010) period using freely available Landsat imagery and a dedicated method and toolbox for the Udzungwa Mountains National Park (UMNP) and its surroundings (20 km buffer) in Tanzania. Habitat data gathered from the Digital Observatory for Protected Areas (DOPA)’s eHabitat+ Web service were used to perform ecological stratification of the study area and to develop similarity maps of the potential presence of comparable habitat types outside the protected area. Finally, integration of the habitat similarity maps with the LULCC data was applied in order to evaluate potential pressures on the different habitats within the national park and on the linking corridors between UMNP and other protected areas in the context of wildlife movement and migration. The results show that the UMNP has not suffered from relevant human activities during the study period. The natural vegetation area has remained stable around 1780 km2
. In the surrounding 20 km buffer area and the connecting corridors, however, the anthropogenic impact has been strong. Artificially built up areas increased by 14.24% over the last 20 years and the agriculture area increased from 11% in 1990 to 30% in the year 2010. The habitat functional types and the similarity maps confirmed the importance of the buffer zone and the connecting corridors for wildlife movements, while the similarity maps detected other potential corridors for wildlife.
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