A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy

The multifunctional Ecosystem Service supply analysis at the spatial level is often the output of a weighted sum of layers in a Geographic Information System (GIS). This procedure is weak in detecting and representing the relationships between the input layers. Nonetheless, composite indicators prod...

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Autores principales:	Stefano Salata, Carlo Grillenzoni
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Ecosystem Services Principal Component Analysis Composite indicators Overlay Geographic information system Environmental indicators Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/65a42be2f13e4f0fb5bb810c50ece834
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id	oai:doaj.org-article:65a42be2f13e4f0fb5bb810c50ece834
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spelling	oai:doaj.org-article:65a42be2f13e4f0fb5bb810c50ece8342021-12-01T04:52:53ZA spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy1470-160X10.1016/j.ecolind.2021.107758https://doaj.org/article/65a42be2f13e4f0fb5bb810c50ece8342021-08-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21004234https://doaj.org/toc/1470-160XThe multifunctional Ecosystem Service supply analysis at the spatial level is often the output of a weighted sum of layers in a Geographic Information System (GIS). This procedure is weak in detecting and representing the relationships between the input layers. Nonetheless, composite indicators produced by overlaying techniques are quite common in applied research and their discrepancies are underestimated in the scientific community, thus affecting the quality of resulting composite maps. In this work, we empirically test the effectiveness of multivariate statistics to obtain reliable composite Ecosystem Maps in the Turin metropolitan area (north-west Italy). We apply the Principal Component Analysis (PCA, using Matlab and ESRI ArcGis) to seven Ecosystem Service models (Habitat Quality, Carbon Sequestration, Water Yield, Nutrient Retention, Sediment Retention, Crop Production and Crop Pollination) and we evaluate how much the resulting composite map differs from the traditional GIS overlay. In doing this, the spectral analysis (with eigenvectors and eigenvalues) of the covariance matrix of the normalized layers confirms the heuristic arguments about the dependence between Ecosystem Services. We show that the PCA method can provide valuable results in landscape Green Network design, avoiding the limits of standard overlaying procedures. Finally, smoothing and classification techniques, applied to PCA estimates, can further improve the approach and encourage its use in various ecological indicators.Stefano SalataCarlo GrillenzoniElsevierarticleEcosystem ServicesPrincipal Component AnalysisComposite indicatorsOverlayGeographic information systemEnvironmental indicatorsEcologyQH540-549.5ENEcological Indicators, Vol 127, Iss , Pp 107758- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Ecosystem Services Principal Component Analysis Composite indicators Overlay Geographic information system Environmental indicators Ecology QH540-549.5
spellingShingle	Ecosystem Services Principal Component Analysis Composite indicators Overlay Geographic information system Environmental indicators Ecology QH540-549.5 Stefano Salata Carlo Grillenzoni A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy
description	The multifunctional Ecosystem Service supply analysis at the spatial level is often the output of a weighted sum of layers in a Geographic Information System (GIS). This procedure is weak in detecting and representing the relationships between the input layers. Nonetheless, composite indicators produced by overlaying techniques are quite common in applied research and their discrepancies are underestimated in the scientific community, thus affecting the quality of resulting composite maps. In this work, we empirically test the effectiveness of multivariate statistics to obtain reliable composite Ecosystem Maps in the Turin metropolitan area (north-west Italy). We apply the Principal Component Analysis (PCA, using Matlab and ESRI ArcGis) to seven Ecosystem Service models (Habitat Quality, Carbon Sequestration, Water Yield, Nutrient Retention, Sediment Retention, Crop Production and Crop Pollination) and we evaluate how much the resulting composite map differs from the traditional GIS overlay. In doing this, the spectral analysis (with eigenvectors and eigenvalues) of the covariance matrix of the normalized layers confirms the heuristic arguments about the dependence between Ecosystem Services. We show that the PCA method can provide valuable results in landscape Green Network design, avoiding the limits of standard overlaying procedures. Finally, smoothing and classification techniques, applied to PCA estimates, can further improve the approach and encourage its use in various ecological indicators.
format	article
author	Stefano Salata Carlo Grillenzoni
author_facet	Stefano Salata Carlo Grillenzoni
author_sort	Stefano Salata
title	A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy
title_short	A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy
title_full	A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy
title_fullStr	A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy
title_full_unstemmed	A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy
title_sort	spatial evaluation of multifunctional ecosystem service networks using principal component analysis: a case of study in turin, italy
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/65a42be2f13e4f0fb5bb810c50ece834
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A spatial evaluation of multifunctional Ecosystem Service networks using Principal Component Analysis: A case of study in Turin, Italy

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