Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package— rasterdiv —to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open‐source algorithms.

This paper presents the results of a forest cover analysis over a time span of 150 years in a protected area of Eastern Trentino (Northern Italy), Paneveggio Pale di S. Martino Nature Park. With the aid of Grass GIS two historical maps (1859 and 1936) and a set of aerial photographs taken from 1945 to 2006 have been analysed, orthorectified and classified with a supervised method, in order to derive a series of forest cover maps. Techniques applied and problems encountered in using heterogeneous material are discussed. The research shows that from 1859 to the present the increase of forest cover is about 25%, due to the reduced impact of forestry and farming. Timberline dynamics have also been considered; an average growth of about 1 m/year has been estimated for the last 150 years and the data have been compared with the timberline cartography and to field surveys. Timberline estimation for recent years appears to be affected mainly by lower human pressure while the relationship with climate changes is difficult to evaluate. Landscape metrics were used to quantify the changes in forest fragmentation and to identify three core areas that have remained unchanged over time. This case study fills a gap of knowledge about the history of forest cover in the area, shows how multi temporal analysis can support protected area management. This study has been requested by the Park managers, a sign t that landscape planners are becoming aware of past landscape importance.