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Sensitivity analysis of spatial models / Linda Lilburne in International journal of geographical information science IJGIS, vol 23 n° 1-2 (january 2009)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 23 n° 1-2 (january 2009) . - pp 151 - 168 Titre : Sensitivity analysis of spatial models Type de document : Article/Communication Auteurs : Linda Lilburne, Auteur ; S. Tarantola, Auteur Année de publication : 2009 Article en page(s) : pp 151 - 168 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de sensibilité [Termes IGN] analyse spatiale [Termes IGN] contamination [Termes IGN] eau souterraine [Termes IGN] méthode de Monte-Carlo [Termes IGN] nitrate Résumé : (Auteur) Sensitivity analysis is the study of how uncertainty in model predictions is determined by uncertainty in model inputs. A global sensitivity analysis considers the potential effects from the simultaneous variation of model inputs over their finite range of uncertainty. A number of techniques are available to carry out global sensitivity analysis from a set of Monte Carlo simulations; some techniques are more efficient than others, depending on the strategy used to sample the uncertainty of model inputs and on the formulae employed for estimating sensitivity measures. The most common approaches are summarised in this paper by focusing on the limitations of each in the context of a sensitivity analysis of a spatial model. A novel approach for undertaking a spatial sensitivity analysis (based on the method of Sobol' and its related improvements) is proposed and tested. This method makes no assumptions about the model and enables the analysis of spatially distributed, uncertain inputs. The proposed approach is illustrated with a simple test model and a groundwater contaminant model. Copyright Taylor & Francis Numéro de notice : A2009-131 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810802094995 En ligne : https://doi.org/10.1080/13658810802094995 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29761 [article]

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Global sensitivity analysis, GIS and multi-criteria evaluation for a sustainable planning of a hazardous waste disposal site in Spain / M. Gomez-Delgado in International journal of geographical information science IJGIS, vol 20 n° 4 (april 2006)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 20 n° 4 (april 2006) . - pp 449 - 466 Titre : Global sensitivity analysis, GIS and multi-criteria evaluation for a sustainable planning of a hazardous waste disposal site in Spain Type de document : Article/Communication Auteurs : M. Gomez-Delgado, Auteur ; S. Tarantola, Auteur Année de publication : 2006 Article en page(s) : pp 449 - 466 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] acquisition de données [Termes IGN] aménagement durable [Termes IGN] analyse de sensibilité [Termes IGN] analyse multicritère [Termes IGN] déchet [Termes IGN] développement durable [Termes IGN] Espagne [Termes IGN] évaluation des données [Termes IGN] risque environnemental [Termes IGN] système d'information géographique [Termes IGN] variance Résumé : (Auteur) A novel application of Sensitivity Analysis is presented. Useful applications of Global SA (GSA) already exist in the field of numerical modelling. In this paper, we explore the joint use of GSA, Geographical Information Systems (GIS) and Multi-Criteria Evaluation. In this preliminary case study, 11 factors have been used to find the best place to locate a hazardous waste landfill. Two variance-based methods (Sobol' and E-FAST) are used to compute sensitivity indices in order to identify the factors that determine the variance of the model output. The results show that only three factors jointly account for 97% of the output variance. This information is employed to make a simplification of the original model, retaining only these three influential factors. In addition, if the SA is carried out in a pilot area where the spatial properties are similar to those of the whole region, we can infer the results to the whole area. This procedure achieves the goal of the study with an optimized allocation of resources for GIS data acquisition. Numéro de notice : A2006-182 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/13658810600607709 En ligne : https://doi.org/10.1080/13658810600607709 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27909 [article]

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Optimized resource allocation for GIS-based model implementation / M. Crosetto in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 3 (March 2002)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 3 (March 2002) . - pp 225 - 232 Titre : Optimized resource allocation for GIS-based model implementation Type de document : Article/Communication Auteurs : M. Crosetto, Auteur ; F. Crosetto, Auteur ; S. Tarantola, Auteur Année de publication : 2002 Article en page(s) : pp 225 - 232 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] aide à la décision [Termes IGN] analyse de sensibilité [Termes IGN] implémentation (informatique) [Termes IGN] incertitude des données [Termes IGN] modèle conceptuel de données Résumé : (Auteur) This paper focuses on a new procedure to support the planning and implementation of GIS-based models. Critical decisions are often based on the outputs of such models. A major goal of the GIS planning stage is to implement a model whose output can reliably support the decision process. The procedure allows the above goal to be achieved with an optimized allocation of resources for GIS data acquisition. It is based on two important modeling tools: uncertainty analysis and sensitivity analysis. An application of the procedure to a GIS-based hydrologic model for flood forecasting is discussed. Numéro de notice : A2002-027 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : sans En ligne : https://www.researchgate.net/profile/M-Crosetto/publication/251813611_Optimised_ [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21944 [article]

Uncertainty and sensitivity analysis: tools for GIS-based model implementation / M. Crosetto in International journal of geographical information science IJGIS, vol 15 n° 5 (july 2001)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 15 n° 5 (july 2001) . - pp 415 - 437 Titre : Uncertainty and sensitivity analysis: tools for GIS-based model implementation Type de document : Article/Communication Auteurs : M. Crosetto, Auteur ; S. Tarantola, Auteur Année de publication : 2001 Article en page(s) : pp 415 - 437 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes d'information géographique [Termes IGN] analyse coût-avantage [Termes IGN] analyse de sensibilité [Termes IGN] hydrologie [Termes IGN] implémentation (informatique) [Termes IGN] incertitude des données [Termes IGN] modélisation spatiale Résumé : (Auteur) A novel procedure to analyse the uncertainty associated to the output of GIS-based models is presented. The procedure can handle models of any degree of complexity that accept any kind of input data. Two important aspects of spatial modelling are addressed: the propagation of uncertainty from model inputs and model parameters up to the model output (uncertainty analysis) ; and the assessment of the relative importance of the sources of uncertainty in the output uncertainty (sensitivity analysis). Two main applications are proposed. The procedure allows implementation of a GIS-based model whose output can reliably support the decision process with an optimised allocation of resources for spatial data acquisition. This is possible in low cost strategy, based on numerical simulations on a small prototype of the GIS-based model. Furthermore, the procedure provides an effective model building tool to choose, from a group of alternative models, the best one in terms of cost-benefit analysis. A comprehensive case study is described. It concerns the implementation of a new GIS-based hydrologic model, whose goal is providing near real-time flood forecasting. Numéro de notice : A2001-112 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/13658810110053125 En ligne : https://doi.org/10.1080/13658810110053125 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21812 [article]

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