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Registro Completo |
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
18/12/2014 |
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Data da última atualização: |
08/11/2021 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
VERWEIJ, P.; SIMOES, M.; ALVES, A.; FERRAZ, R.; CORMONT, A. |
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Afiliação: |
PETER VERWEIJ, WAGENINGEN-UR; MARGARETH SIMOES P MEIRELLES, CNPS; ANDREI ALVES, UERJ; RODRIGO PECANHA DEMONTE FERRAZ, CNPS; ANOUK CORMONT, WAGENINGEN-UR. |
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Título: |
Linking bayesian belief networks and GIS to assess the ecosystem integrity in the brazilian Amazon. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
In: INTERNATIONAL CONGRESS ON ENVIRONMENTAL MODELLING AND SOFTWARE, 7., 2014, San Diego. Proceedings... Manno, CH: International Environmental Modelling & Software Society, 2014. v. 2, p. 864-871. |
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Idioma: |
Inglês |
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Conteúdo: |
Deforestation and climate change heavily impact the ecosystem of the Amazon rainforest threatening its resilience and the sustainability of many human activities. Land protection may prevent ecosystems and their services to deteriorate from the pressures of agricultural expansion, population growth and wood harvesting. In the Brazilian Amazon land protection occurs in several forms such as environmental conservation, setting biodiversity priority areas and the delineation of indigenous lands. Still, the effects are not clear as understanding of the ecosystems is incomplete and responses to human actions are highly uncertain. Bayesian Belief Networks (BBN) are models that probabilistically represent correlative and causal relationships among variables. BBNs have been successfully applied to natural resource management to address environmental management problems and to assess the impact of alternative management measures. By training the probabilistic relationships using field data, Remote Sensing data and GIS data the BBN can provide information on the ecosystems: the ecosystem integrity and their likely response to climate change or alternative management actions. An increasing number of studies train and apply BBNs with evidence originating from GIS data; a cumbersome and error prone soft-linking method requiring manual conversion of data files between the BBN and GIS software systems. This paper presents the full integration of a BBN software system within an existing GIS based Discussion Support System (DSS) illustrated by the case of the ecosystem integrity of the Brazilian amazon. The full integration speeds up the processing and thereby allows doing multiple runs within a short period of time such as a stakeholder workshop. Each consecutive run is based upon insights from a previous one. Furthermore, the DSS provides the management of different options, visualize spatial summaries and trade-offs between different impact indicators and see regional differences. MenosDeforestation and climate change heavily impact the ecosystem of the Amazon rainforest threatening its resilience and the sustainability of many human activities. Land protection may prevent ecosystems and their services to deteriorate from the pressures of agricultural expansion, population growth and wood harvesting. In the Brazilian Amazon land protection occurs in several forms such as environmental conservation, setting biodiversity priority areas and the delineation of indigenous lands. Still, the effects are not clear as understanding of the ecosystems is incomplete and responses to human actions are highly uncertain. Bayesian Belief Networks (BBN) are models that probabilistically represent correlative and causal relationships among variables. BBNs have been successfully applied to natural resource management to address environmental management problems and to assess the impact of alternative management measures. By training the probabilistic relationships using field data, Remote Sensing data and GIS data the BBN can provide information on the ecosystems: the ecosystem integrity and their likely response to climate change or alternative management actions. An increasing number of studies train and apply BBNs with evidence originating from GIS data; a cumbersome and error prone soft-linking method requiring manual conversion of data files between the BBN and GIS software systems. This paper presents the full integration of a BBN software system within an existing GIS... Mostrar Tudo |
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Palavras-Chave: |
DSS; GIS; Integridade do ecossistema; Modelagem participativa; Rede Bayesiana; Sistema de suporte à decisão. |
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Thesagro: |
Ecossistema; Sistema de Informação Geográfica. |
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Thesaurus Nal: |
Bayesian theory; Decision support systems; Ecosystems; Geographic information systems. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/114043/1/iemss2014-submission-200.pdf
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Marc: |
LEADER 03062nam a2200301 a 4500
001 2003064
005 2021-11-08
008 2014 bl uuuu u00u1 u #d
100 1 $aVERWEIJ, P.
245 $aLinking bayesian belief networks and GIS to assess the ecosystem integrity in the brazilian Amazon.$h[electronic resource]
260 $aIn: INTERNATIONAL CONGRESS ON ENVIRONMENTAL MODELLING AND SOFTWARE, 7., 2014, San Diego. Proceedings... Manno, CH: International Environmental Modelling & Software Society, 2014. v. 2, p. 864-871.$c2014
520 $aDeforestation and climate change heavily impact the ecosystem of the Amazon rainforest threatening its resilience and the sustainability of many human activities. Land protection may prevent ecosystems and their services to deteriorate from the pressures of agricultural expansion, population growth and wood harvesting. In the Brazilian Amazon land protection occurs in several forms such as environmental conservation, setting biodiversity priority areas and the delineation of indigenous lands. Still, the effects are not clear as understanding of the ecosystems is incomplete and responses to human actions are highly uncertain. Bayesian Belief Networks (BBN) are models that probabilistically represent correlative and causal relationships among variables. BBNs have been successfully applied to natural resource management to address environmental management problems and to assess the impact of alternative management measures. By training the probabilistic relationships using field data, Remote Sensing data and GIS data the BBN can provide information on the ecosystems: the ecosystem integrity and their likely response to climate change or alternative management actions. An increasing number of studies train and apply BBNs with evidence originating from GIS data; a cumbersome and error prone soft-linking method requiring manual conversion of data files between the BBN and GIS software systems. This paper presents the full integration of a BBN software system within an existing GIS based Discussion Support System (DSS) illustrated by the case of the ecosystem integrity of the Brazilian amazon. The full integration speeds up the processing and thereby allows doing multiple runs within a short period of time such as a stakeholder workshop. Each consecutive run is based upon insights from a previous one. Furthermore, the DSS provides the management of different options, visualize spatial summaries and trade-offs between different impact indicators and see regional differences.
650 $aBayesian theory
650 $aDecision support systems
650 $aEcosystems
650 $aGeographic information systems
650 $aEcossistema
650 $aSistema de Informação Geográfica
653 $aDSS
653 $aGIS
653 $aIntegridade do ecossistema
653 $aModelagem participativa
653 $aRede Bayesiana
653 $aSistema de suporte à decisão
700 1 $aSIMOES, M.
700 1 $aALVES, A.
700 1 $aFERRAZ, R.
700 1 $aCORMONT, A.
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Embrapa Solos (CNPS) |
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| 1. |  | VERWEIJ, P.; SIMOES, M.; ALVES, A.; FERRAZ, R.; CORMONT, A. Linking bayesian belief networks and GIS to assess the ecosystem integrity in the brazilian Amazon. In: INTERNATIONAL CONGRESS ON ENVIRONMENTAL MODELLING AND SOFTWARE, 7., 2014, San Diego. Proceedings... Manno, CH: International Environmental Modelling & Software Society, 2014. v. 2, p. 864-871.| Tipo: Artigo em Anais de Congresso |
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