Understanding temporal and spatial dimensions of land cover dynamics is a critical factor to link ecosystem transformation to land and environmental management. The trajectory of land cover change is not a simple difference between two conditions, but a continuous process. Therefore, there is a need to integrate multiple time periods to identify slow and rapid transformations over time. We mapped land cover composition and configuration changes using time series of Landsat TM/ETM+ images (1985-2011) in Southern Chile to understand the transformation process of a temperate rainforest relict and biodiversity hotspot. Our analysis builds on 28 Landsat scenes from 1985 to 2011 that have been classified using a random forests approach. Base on the high temporal data set we quantify land cover change and fragmentation indices to fully understand landscape transformation in this area. Our results show a high deforestation process for old growth forest strongest at the beginning of the study period (1985-1986-1998-1999) followed by a progressive slowdown until 2011. Within different study periods deforestation rates were much larger than the average rate over the complete study period (0.65%), with the highest annual deforestation rate of 1.2% in 1998-1999. The deforestation resulted in a low connectivity between native forest patches. Old-growth forest was less fragmented, but was concentrated mainly in two large regions (the Andes and Coastal mountain range) with almost no connection in between. Secondary forest located in more intensively used areas was highly fragmented. Exotic forest plantation areas, one of the most important economic activities in the area, increased sevenfold (from 12,836 to 103,540 ha), especially during the first periods at the expense of shrubland, secondary forest, grassland/arable land and old grown forest. Our analysis underlines the importance of expanding temporal resolution in land cover/use change studies to guide sustainable ecosystem management strategies as increase landscape connectivity and integrate landscape planning to economic activities. The study is highlighting the key role of remote sensing in the sustainable management of human influenced ecosystems. (C) 2016 Elsevier Ltd. All rights reserved.