Human influence on the environment differs in terms of distribution and intensity, thus producing a gradient of landscape modifications that translates into different landscape structures. Within this variety of landscapes, fringe areas represent complex spaces where dynamic processes and instable conditions can be observed. In this research Kernel Density Estimation, multivariate spatial analysis, landscape pattern analysis, and Principal Component Analysis (PCA) were combined to model and characterise landscape gradients, and to analyse the structural features of fringe areas. This methodology was applied to a rural area of central Italy, using density indicators associated with urbanisation, agriculture, and natural elements considered to be key components for the identification of landscape gradients. The results highlight not only specific "pillar" landscapes, which are dominated by said components, but also transitional landscapes, where the most relevant forms of interaction between land uses were identified. Characterisation of landscape structures along the gradient illustrated different trends in patch density, shape complexity and landscape diversity, demonstrating greater variability in fringe areas than in pillar landscapes. PCA revealed a partial overlap between the main structural characteristics of the agro-forestry matrix and the medium intensity agricultural landscapes, whereas urban fringes and semi-natural fringes were clearly separated. The discovery of the continuous landscape gradients and an understanding of the gamut of landscape types nested along them is crucial in allowing for more effective land-use planning in which also fringe areas become a relevant part of the process.

Landscape sequences along the urban-rural-natural gradient: A novel geospatial approach for identification and analysis

SIGURA, Maurizia
Ultimo
2015-01-01

Abstract

Human influence on the environment differs in terms of distribution and intensity, thus producing a gradient of landscape modifications that translates into different landscape structures. Within this variety of landscapes, fringe areas represent complex spaces where dynamic processes and instable conditions can be observed. In this research Kernel Density Estimation, multivariate spatial analysis, landscape pattern analysis, and Principal Component Analysis (PCA) were combined to model and characterise landscape gradients, and to analyse the structural features of fringe areas. This methodology was applied to a rural area of central Italy, using density indicators associated with urbanisation, agriculture, and natural elements considered to be key components for the identification of landscape gradients. The results highlight not only specific "pillar" landscapes, which are dominated by said components, but also transitional landscapes, where the most relevant forms of interaction between land uses were identified. Characterisation of landscape structures along the gradient illustrated different trends in patch density, shape complexity and landscape diversity, demonstrating greater variability in fringe areas than in pillar landscapes. PCA revealed a partial overlap between the main structural characteristics of the agro-forestry matrix and the medium intensity agricultural landscapes, whereas urban fringes and semi-natural fringes were clearly separated. The discovery of the continuous landscape gradients and an understanding of the gamut of landscape types nested along them is crucial in allowing for more effective land-use planning in which also fringe areas become a relevant part of the process.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1071777
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