Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier
Territorial planning and management requires that the spatial structure of the socioecological sectors is adequately understood. Several classification techniques exist that have been applied to detect ecological, or socioeconomic sectors, but not simultaneously in the same model; and also, with a...
| Main Authors: | , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
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Elsevier
2024
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/14998 |
| _version_ | 1789406598074990592 |
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| author | Fernández Ropero, Rosa María Aguilera Aguilera, Pedro Rumí Rodríguez, Rafael |
| author_facet | Fernández Ropero, Rosa María Aguilera Aguilera, Pedro Rumí Rodríguez, Rafael |
| author_sort | Fernández Ropero, Rosa María |
| collection | DSpace |
| description | Territorial planning and management requires that the spatial structure of the socioecological sectors is adequately understood. Several classification techniques exist that have been applied to detect ecological, or socioeconomic
sectors, but not simultaneously in the same model; and also, with a limited number of variables. We have developed and applied a new probabilistic methodology – based on hierarchical hybrid Bayesian network classifiers - to
identify the different socioecological sectors in Andalusia, a region in southern Spain, and incorporate a scenario of change. Results show that a priori, the socioecological structure is highly heterogeneous, with an altitude gradient
from the river basin to the mountain peaks. However, under a scenario of Global Environmental Change this heterogeneity is lost, making the territory more vulnerable to any alteration or disturbance. The methodology applied
allows dealing with complex problems, containing a large number of variables, by splitting them into several sub-problems that can be easily solved. In the case of territorial planning, each component of the territory is modelled
independently before combining them into a general classifier model. Furthermore, it can be applied to any complex unsupervised classification problem with no modification to the methodology. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-14998 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2024 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-149982024-01-09T11:53:04Z Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier Fernández Ropero, Rosa María Aguilera Aguilera, Pedro Rumí Rodríguez, Rafael Hierarchical classifier Mixture of Truncated Exponential models Probabilistic clustering Socio ecological systems Global environmental change Territorial planning and management requires that the spatial structure of the socioecological sectors is adequately understood. Several classification techniques exist that have been applied to detect ecological, or socioeconomic sectors, but not simultaneously in the same model; and also, with a limited number of variables. We have developed and applied a new probabilistic methodology – based on hierarchical hybrid Bayesian network classifiers - to identify the different socioecological sectors in Andalusia, a region in southern Spain, and incorporate a scenario of change. Results show that a priori, the socioecological structure is highly heterogeneous, with an altitude gradient from the river basin to the mountain peaks. However, under a scenario of Global Environmental Change this heterogeneity is lost, making the territory more vulnerable to any alteration or disturbance. The methodology applied allows dealing with complex problems, containing a large number of variables, by splitting them into several sub-problems that can be easily solved. In the case of territorial planning, each component of the territory is modelled independently before combining them into a general classifier model. Furthermore, it can be applied to any complex unsupervised classification problem with no modification to the methodology. 2024-01-09T11:53:04Z 2024-01-09T11:53:04Z 2015 info:eu-repo/semantics/article R.F. Ropero, P.A.Aguilera, R. Rumí. Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier. Ecological Modelling 2015, 311, pag. 73-87 http://hdl.handle.net/10835/14998 en https://www.sciencedirect.com/science/article/pii/S0304380015002057 Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Elsevier |
| spellingShingle | Hierarchical classifier Mixture of Truncated Exponential models Probabilistic clustering Socio ecological systems Global environmental change Fernández Ropero, Rosa María Aguilera Aguilera, Pedro Rumí Rodríguez, Rafael Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier |
| title | Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier |
| title_full | Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier |
| title_fullStr | Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier |
| title_full_unstemmed | Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier |
| title_short | Analysis of the socioecological structure and dynamics of the territory using a hybrid Bayesian network classifier |
| title_sort | analysis of the socioecological structure and dynamics of the territory using a hybrid bayesian network classifier |
| topic | Hierarchical classifier Mixture of Truncated Exponential models Probabilistic clustering Socio ecological systems Global environmental change |
| url | http://hdl.handle.net/10835/14998 |
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