APPLICATION OF MULTI-SCALE REMOTE SENSING IMAGERY IN MONITORING OF A MOUNTAIN PROTECTED AREA

In highly human-dominated European regions traditional activities deeply shaped the landscape with strong consequences on biodiversity patterns. However, in the last few decades the rapid socio-economic change led to the abandonment of “marginal” land modifying the landscape structures. In this context Alps are of great interest due to particular habitat disposition along the altitudinal gradient and to the presence of highly adapted species providing many ecosystem services. In this scenario it is necessary to stablish long-term monitoring programs to quantify the present and future landscape changes. Remote sensed data are useful tools in understanding landscape processes through different scales of analysis. Assuming that landscape change at given scale is the result of many interacting process at smaller scales, in order to explore mechanisms shaping landscape structure there is the need to integrate information derived from different platforms to overtake gaps in spatial or temporal resolution. We aim to understand the landscape dynamics and the effectiveness of different kind of remote sensed data at different scales of analysis in a mountain protected area context, Gran Paradiso National Park (North-Western Italian Alps). The broader landscape change occurred in the last few decades were reconstructed using satellite imagery. To understand the vegetation pattern change orthorectified aerial images were compared with recently acquired orthophotos; a preliminary study of image classification to derive land cover map was also carried out. UAV and field sampling were collected to link ground observation and remotely-sensed imagery. In this study it was pointed out that the integration of different sensors and their peculiarities is a valuable tool to explore the ecological processes of complex Alpine environments. The proposed methods were set in perspective to sustain protected area management plans to protect the vanishing biodiversity patterns, strongly dependent the traditional land use.