A soft clustering approach to detect socio-ecological landscape boundaries using bayesian networks

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Ropero, R.F.; Maldonado, A.D.; Uusitalo, L.; Salmerón, A.; Rumí, R.; Aguilera, P.A. A Soft Clustering Approach to Detect Socio-Ecological Landscape Boundaries Using Bayesian Networks. Agronomy 2021, 11, 740. https://doi.org/10.3390/agronomy11040740

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Title: A soft clustering approach to detect socio-ecological landscape boundaries using bayesian networks
Author: Ropero, Rosa F.; Maldonado, Ana D.; Uusitalo, Laura; Salmerón, Antonio; Rumí, Rafael; Aguilera, Pedro A.
Publisher: MDPI AG
Date: 2021
Language: en
Belongs to series: Agronomy 11(4), 740
ISSN: 2073-4395
DOI: https://doi.org/10.3390/agronomy11040740
URI: http://hdl.handle.net/10138/332344
Abstract: Detecting socio-ecological boundaries in traditional rural landscapes is very important for the planning and sustainability of these landscapes. Most of the traditional methods to detect ecological boundaries have two major shortcomings: they are unable to include uncertainty, and they often exclude socio-economic information. This paper presents a new approach, based on unsupervised Bayesian network classifiers, to find spatial clusters and their boundaries in socio-ecological systems. As a case study, a Mediterranean cultural landscape was used. As a result, six socio-ecological sectors, following both longitudinal and altitudinal gradients, were identified. In addition, different socio-ecological boundaries were detected using a probability threshold. Thanks to its probabilistic nature, the proposed method allows experts and stakeholders to distinguish between different levels of uncertainty in landscape management. The inherent complexity and heterogeneity of the natural landscape is easily handled by Bayesian networks. Moreover, variables from different sources and characteristics can be simultaneously included. These features confer an advantage over other traditional techniques.
Subject: boundary detection
Mediterranean cultural landscape
Bayesian networks
Bayesian analysis
landscape planning
landscape management
climate changes
sustainable development
Subject (ysa): bayesilainen menetelmä
kestävä kehitys
Rights: CC BY 4.0

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