Roberto Valenti

Landscape changes of Rome through tree-lined roads

Rome has greatly expanded in the course of the last century, after it became the capital of the Italian state in 1870. In this period, many areas were built according to different urbanistic criteria. The city may now be divided into urban units (Wards, Districts, Suburbs and Zones), which have an almost concentric disposition. The changes of the whole urban landscape and of the single urban units (UUs) have been analysed by studying the different tree-species planted along the roads. A database has been created using the four censuses of the tree-lined roads made by the city administration in 1898, 1955, 1971 and 1998. This analysis has shown a strong link between the specific cultural and political period and the tree-species used. Moreover, for each year, the UUs have been classified according to the percentage composition of the species. The results have been mapped using the Arcview 3.1 GIS program in order to integrate them with a more general project on GIS-based cartography of the natural and anthropic vegetation of Rome.

Classifying and Mapping Potential Distribution of Forest Types Using a Finite Mixture Model

The present paper presents the application of a finite mixture model (FMM) to analyze spatially explicit data on forest composition and environmental variables to produce a high-resolution map of their current potential distribution. FMM provides a convenient yet formal setting for model-based clustering. Within this framework, forest data are assumed to come from an underlying FMM, where each mixture component corresponds to a cluster and each cluster is characterized by a different composition of tree species. An important extension of this model is based on including a set of covariates to predict class membership. These covariates can be climatic and topographical parameters as well as geographical coordinates and the class membership of neighbouring plots. FMM was applied to a national forest inventory of Italy consisting of 6,714 plots with a measure of abundance for 27 tree species. In this way, a map of potential forest types was produced. The limitations and usefulness of the proposed modelling approach were analyzed and discussed, comparing the results with an independently derived expert map.