Abstract:We propose a procedure to detect significant changes in forest spatial patterns and relevant scales. Our approach consists of four sequential steps. First, based on a series of multi-temporal forest maps, a set of geographic windows of increasing extents are extracted. Second, for each extent and date, specific stochastic simulations that replicate real-world spatial pattern characteristics are run. Third, by computing pattern metrics on both simulated and real maps, their empirical distributions and confidence intervals are derived. Finally, multi-temporal scalograms are built for each metric. Based on cover maps (1954, 2011) with a resolution of 10 m we analyze forest pattern changes in a central Apennines (Italy) reserve at multiple spatial extents (128, 256 and 512 pixels). We identify three types of multi-temporal scalograms, depending on pattern metric behaviors, describing different dynamics of natural reforestation process. The statistical distribution and variability of pattern metrics at multiple extents offers a new and powerful tool to OPEN ACCESS Remote Sens. 2014, 6 9299 detect forest variations over time. Similar procedures can (i) help to identify significant changes in spatial patterns and provide the bases to relate them to landscape processes; (ii) minimize the bias when comparing pattern metrics at a single extent and (iii) be extended to other landscapes and scales.
Abstract:Organized transhumant pastoralism has contributed to shaping the cultural landscape of many countries. It has affected areas designated for grazing, temporary and permanent shelters, and towns. Through the analysis of historical maps and recent information, in a temporal range from 1652 to 2014, this study focused on changes in land cover and conservation status of one of the main Italian transhumance paths, namely the Tratturo Castel di Sangro-Lucera. Although there are some areas where this drove road is still recognizable, it is mostly identifiable only through a few tangible signs. The methodological approach, which we present in this study, allowed us to compare historical and recent cartographies as well as archive documentation. The resulting virtual reinstatement is proposed as an efficient method for the conservation and management of material cultural heritage and can be applied in other countries with transhumance drove roads (e.g., France, Portugal).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.