Long-Term Assessment of Spatio-Temporal Landuse/Landcover Changes (LUCCs) of Ošljak Island (Croatia) Using Multi-Temporal Data—Invasion of Aleppo Pine

The karst landscapes of the Mediterranean are regarded as some of the most vulnerable, fragile, and complex systems in the world. They hold a particularly interesting group of small islands with a distinctive, recognizable landscape. The Republic of Croatia (HR), which has one of the most indented coasts in the world, is particularly known for them. In this paper, we analyzed the spatio-temporal changes (STCs) in the landscape of Ošljak Island, the smallest inhabited island in HR. Landuse/landcover change (LUCC) analysis has been conducted from 1944 to 2021. The methodology included the acquisition of multi-temporal data, data harmonization, production of landuse/landcover (LU/LC) maps, selection of optimal environmental indicators (EIs), and simulation modeling. In total, eleven comparable LU/LC models have been produced, with moderate accuracy. STCs have been quantified using the nine EIs. The dominant processes that influenced the changes in the Ošljak landscape have been identified. The results have shown that, in recent decades, Ošljak has undergone a landscape transformation which was manifested through (a) pronounced expansion of Aleppo pine; (b) deagrarianization, which led to secondary succession; and (c) urban sprawl, which led to the transformation of the functional landscape. The most significant of the detected changes is the afforestation of the Aleppo pine. Namely, in a 77-year span, the Aleppo pine has expanded intensively to an area of 11.736 ha, created a simulation model for 2025, and pointed to the possibility of the continued expansion of Aleppo pine. Specific guidelines for the management of this new transformed landscape have been proposed. This research provides a user-friendly methodological framework that can efficiently monitor LUCCs of a smaller area in the case when geospatial data are scarce and satellite imagery of coarser resolution cannot be used. Moreover, it gives an insight into the availability and quality of multi-temporal data for the HR.