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The Environmental “Risky” Region: Identifying Land Degradation Processes Through Integration of Socio-Economic and Ecological Indicators in a Multivariate Regionalization Model

The Environmental “Risky” Region: Identifying Land Degradation Processes Through Integration of... Although several studies have assessed Land Degradation (LD) states in the Mediterranean basin through the use of composite indices, relatively few have evaluated the impact of specific LD drivers at the local scale. In this work, a computational strategy is introduced to define homogeneous areas at risk and the main factors acting as determinants of LD. The procedure consists of three steps and is applied to a set of ten environmental indicators available at the municipality scale in Latium, central Italy. A principal component analysis extracting latent patterns and simplifying data complexity was carried out on the original data matrix. Subsequently, a k-means cluster analysis was applied on a restricted number of meaningful, latent factors extracted by PCA in order to produce a classification of the study area into homogeneous regions. Finally, a stepwise discriminant analysis was performed to determine which indicators contributed the most to the definition of homogeneous regions. Three classes of “risky” regions were identified according to the main drivers of LD acting at the local scale. These include: (i) soil sealing (coupled with landscape fragmentation, fire risk, and related processes), (ii) soil salinization due to agricultural intensification, and (iii) soil erosion due to farmland depopulation and land abandonment in sloping areas. Areas at risk for LD covered 56 and 63% of the investigated areas in 1970 and 2000, respectively. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Management Springer Journals

The Environmental “Risky” Region: Identifying Land Degradation Processes Through Integration of Socio-Economic and Ecological Indicators in a Multivariate Regionalization Model

Salvati, Luca; Zitti, Marco
Environmental Management , Volume 44 (5) – Sep 29, 2009
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References (59)

Publisher
Springer Journals
Copyright
Copyright © 2009 by Springer Science+Business Media, LLC
Subject
Environment; Waste Water Technology / Water Pollution Control / Water Management / Aquatic Pollution; Forestry Management; Atmospheric Protection/Air Quality Control/Air Pollution; Nature Conservation ; Ecology; Environmental Management
ISSN
0364-152X
eISSN
1432-1009
DOI
10.1007/s00267-009-9378-5
pmid
19787396
Publisher site
See Article on Publisher Site

Abstract

Although several studies have assessed Land Degradation (LD) states in the Mediterranean basin through the use of composite indices, relatively few have evaluated the impact of specific LD drivers at the local scale. In this work, a computational strategy is introduced to define homogeneous areas at risk and the main factors acting as determinants of LD. The procedure consists of three steps and is applied to a set of ten environmental indicators available at the municipality scale in Latium, central Italy. A principal component analysis extracting latent patterns and simplifying data complexity was carried out on the original data matrix. Subsequently, a k-means cluster analysis was applied on a restricted number of meaningful, latent factors extracted by PCA in order to produce a classification of the study area into homogeneous regions. Finally, a stepwise discriminant analysis was performed to determine which indicators contributed the most to the definition of homogeneous regions. Three classes of “risky” regions were identified according to the main drivers of LD acting at the local scale. These include: (i) soil sealing (coupled with landscape fragmentation, fire risk, and related processes), (ii) soil salinization due to agricultural intensification, and (iii) soil erosion due to farmland depopulation and land abandonment in sloping areas. Areas at risk for LD covered 56 and 63% of the investigated areas in 1970 and 2000, respectively.

Journal

Environmental Management – Springer Journals

Published: Sep 29, 2009

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