The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material. http://http://dspace.unitus.it:80 2013-06-18T05:00:13Z 2013-06-18T05:00:13Z Lamonaca, Andrea Calvani, Paolo Giuliarelli, Diego Corona, Piermaria http://hdl.handle.net/2067/2113 2011-06-10T00:30:47Z 2007-12-31T23:00:00Z

Title: Surveying black pine plantations in the province of Rieti (Italy) Authors: Lamonaca, Andrea; Calvani, Paolo; Giuliarelli, Diego; Corona, Piermaria Abstract: Durante il secolo scorso furono realizzati molti rimboschimenti di pino nero in ambito appenninico al fine di recuperare terreni degradati. Vari Autori hanno formulato proposte di gestione per la rinaturalizzazione di questi soprassuoli. La loro applicazione comporta però elevati costi di rilievo in sede di analisi. Obiettivo di questa nota è la proposizione di una metodologia di inventario ricognitivo degli attributi di questo tipo di soprassuoli che consenta di ottenere dati sufficientemente attendibili su ampie superfici, a costi relativamente contenuti. A livello sperimentale è stata realizzata la mappatura dei rimboschimenti di pino nero della provincia di Rieti. La tecnica k-NN è stata utilizzata per spazializzare la provvigione legnosa a partire da aree di saggio a terra con l’ausilio di un’immagine telerilevata Landsat 7 ETM+. A scopo esemplificativo, gli aspetti inventariali sono integrati da misure ecologico-paesistiche per la descrizione spaziale dei rimboschimenti mappati.; In the last century large afforestation programs were carried out in the Apennines to recover degraded lands, mainly by Pinus nigra plantations. Currently, many Authors have proposed management guidelines to foster the naturalization of such woodlands. However, such an option requires the availability of detailed surveys. The aim of this note is to propose a survey protocol for qualifying the landscape pattern of pine reafforestations and for mapping their growing stock on the basis of the k-Nearest Neighbor (k-NN) techniques. A case study application by Landsat 7 ETM+ imagery is here reported concerning the Pinus nigra plantations in the province of Rieti (Central Italy).

2007-12-31T23:00:00Z Corona, Piermaria Calvani, Paolo Scarascia Mugnozza, Giuseppe Pompei, Enrico http://hdl.handle.net/2067/2115 2011-06-10T00:30:44Z 2007-12-31T23:00:00Z

Title: Modelling natural forest expansion on a landscape level by multinomial logistic regression Authors: Corona, Piermaria; Calvani, Paolo; Scarascia Mugnozza, Giuseppe; Pompei, Enrico Abstract: Natural forest expansion is one of the most relevant landscape changes in many temperate countries. Although large areas are involved, relatively few studies have been carried out with the objective of unravelling the specific impact of the individual factors characterising the sites prone to such a process. The aim of this article is to present a research tool for assessing the factors characterising farmland sites prone to natural conversion from crop growing and pasture to forests and other wooded land (OWL), and for predicting the probability of such a land-use change. The methodological approach is based on multinomial logistic regression. As a case study, the approach was applied to land-use classification repeated on the same sites in a large area of central Italy on two successive occasions, spanning two decades, from the beginning of the 1980s up to 2002. Of all the factors assessed, landscape attributes were identified as a sufficient subset for quantitative prediction of change from farmland to OWL or to forest. The tested modelling approach is explicitly empirical and planning-oriented. From a quantitative point of view, the precision of the models may be only indicative for assessing land-use change probability for single observations, while it is appropriate for predicting mean probabilities at a landscape mapping level, where it is possible to sample a number of sites. At this level, the approach is a useful tool for simulating future landscape scenarios related to natural forest expansion. Description: L'articolo è disponibile sul sito dell'editore www.tandf.co.uk/journals/

2007-12-31T23:00:00Z