Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropies
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.5/13724 |
Resumo: | Concept Paper |
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7160 |
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Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropiesdecision modelsnon-expected utility methodsweighted Shannon entropyweighted Gini-Simpson indexeconomic valueslandscape diversityprecautionary approachlandscape servicessystem manifoldConcept PaperThe search for hypothetical optimal solutions of landscape composition is a major issue in landscape planning and it can be outlined in a two-dimensional decision space involving economic value and landscape diversity, the latter being considered as a potential safeguard to the provision of services and externalities not accounted in the economic value. In this paper, we use decision models with different utility valuations combined with weighted entropies respectively incorporating rarity factors associated to Gini-Simpson and Shannon measures. A small example of this framework is provided and discussed for landscape compositional scenarios in the region of Nisa, Portugal. The optimal solutions relative to the different cases considered are assessed in the two-dimensional decision space using a benchmark indicator. The results indicate that the likely best combination is achieved by the solution using Shannon weighted entropy and a square root utility function, corresponding to a risk-averse behavior associated to the precautionary principle linked to safeguarding landscape diversity, anchoring for ecosystem services provision and other externalities. Further developments are suggested, mainly those relative to the hypothesis that the decision models here outlined could be used to revisit the stability-complexity debate in the field of ecological studiesMDPIRepositório da Universidade de LisboaCasquilho, José PintoRego, Francisco Castro2017-06-06T13:40:48Z20172017-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.5/13724eng"Entropy". ISSN 1099-4300. 19 (2017) 661099-430010.3390/e19020066info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-06T14:43:49Zoai:www.repository.utl.pt:10400.5/13724Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T16:59:40.101443Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropies |
title |
Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropies |
spellingShingle |
Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropies Casquilho, José Pinto decision models non-expected utility methods weighted Shannon entropy weighted Gini-Simpson index economic values landscape diversity precautionary approach landscape services system manifold |
title_short |
Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropies |
title_full |
Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropies |
title_fullStr |
Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropies |
title_full_unstemmed |
Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropies |
title_sort |
Discussing landscape compositional scenarios generated with maximization of non-expected utility decision models based on weighted entropies |
author |
Casquilho, José Pinto |
author_facet |
Casquilho, José Pinto Rego, Francisco Castro |
author_role |
author |
author2 |
Rego, Francisco Castro |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Casquilho, José Pinto Rego, Francisco Castro |
dc.subject.por.fl_str_mv |
decision models non-expected utility methods weighted Shannon entropy weighted Gini-Simpson index economic values landscape diversity precautionary approach landscape services system manifold |
topic |
decision models non-expected utility methods weighted Shannon entropy weighted Gini-Simpson index economic values landscape diversity precautionary approach landscape services system manifold |
description |
Concept Paper |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-06-06T13:40:48Z 2017 2017-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.5/13724 |
url |
http://hdl.handle.net/10400.5/13724 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
"Entropy". ISSN 1099-4300. 19 (2017) 66 1099-4300 10.3390/e19020066 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
MDPI |
publisher.none.fl_str_mv |
MDPI |
dc.source.none.fl_str_mv |
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instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799131083698077696 |