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Sensivity analysis of a decision tree classification to input data errors using a general Monte Carlo error sensitivity model / Zhi Huang in International journal of geographical information science IJGIS, vol 23 n°11-12 (november 2009)
[article]
Titre : Sensivity analysis of a decision tree classification to input data errors using a general Monte Carlo error sensitivity model Type de document : Article/Communication Auteurs : Zhi Huang, Auteur ; S.W. Laffan, Auteur Année de publication : 2009 Article en page(s) : pp 1433 - 1452 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de sensibilité
[Termes IGN] carte de la végétation
[Termes IGN] classification par arbre de décision
[Termes IGN] erreur de classification
[Termes IGN] erreur de positionnement
[Termes IGN] image Landsat-TM
[Termes IGN] incertitude des données
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle numérique de terrainRésumé : (Auteur) We analysed the sensitivity of a decision tree derived forest type mapping to simulated data errors in input digital elevation model (DEM), geology and remotely sensed (Landsat Thematic Mapper) variables. We used a stochastic Monte Carlo simulation model coupled with a one-at-a-time approach. The DEM error was assumed to be spatially autocorrelated with its magnitude being a percentage of the elevation value. The error of categorical geology data was assumed to be positional and limited to boundary areas. The Landsat data error was assumed to be spatially random following a Gaussian distribution. Each layer was perturbed using its error model with increasing levels of error, and the effect on the forest type mapping was assessed. The results of the three sensitivity analyses were markedly different, with the classification being most sensitive to the DEM error, than to the Landsat data errors, but with only a limited sensitivity to the geology data error used. A linear increase in error resulted in non-linear increases in effect for the DEM and Landsat errors, while it was linear for geology. As an example, a DEM error of as small as +2% reduced the overall test accuracy by more than 2%. More importantly, the same uncertainty level has caused nearly 10% of the study area to change its initial class assignment at each perturbation, on average. A spatial assessment of the sensitivities indicates that most of the pixel changes occurred within those forest classes expected to be more sensitive to data error. In addition to characterising the effect of errors on forest type mapping using decision trees, this study has demonstrated the generality of employing Monte Carlo analysis for the sensitivity and uncertainty analysis of categorical outputs that have distinctive characteristics from that of numerical outputs. Copyright Taylor & Francis Numéro de notice : A2009-515 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1080/13658810802634949 En ligne : https://doi.org/10.1080/13658810802634949 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30144
in International journal of geographical information science IJGIS > vol 23 n°11-12 (november 2009) . - pp 1433 - 1452[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-09071 RAB Revue Centre de documentation En réserve L003 Disponible 079-09072 RAB Revue Centre de documentation En réserve L003 Disponible Applications of signal detection theory to Geographic Information Science / A. Griffin in Cartographica, vol 44 n° 3 (September 2009)
[article]
Titre : Applications of signal detection theory to Geographic Information Science Type de document : Article/Communication Auteurs : A. Griffin, Auteur ; Scott Bell, Auteur Année de publication : 2009 Article en page(s) : pp 145 - 158 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] aide à la décision
[Termes IGN] détection du signal
[Termes IGN] incertitude des données
[Termes IGN] système d'information géographique
[Termes IGN] théorie du signal
[Termes IGN] utilisateurRésumé : (Auteur) Signal detection theory (SDT) is a framework used by psychologists to study decision making under uncertain conditions. While we often know a great deal about how different methodological choices can affect the outcome of an analysis, we know less about how information end users interpret and understand competing outcomes in the context of the decisions they are trying to make. We contend that such information would be useful and assert that SDT analysis is one method of building this understanding. We provide an introduction to SDT methods and an example of the methods applied to a navigation experiment, discuss why SDT may be useful for GIScientists, and provide several examples of other potential application areas. Copyright University of Toronto Press Numéro de notice : A2009-408 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3138/carto.44.3.145 Date de publication en ligne : 02/10/2009 En ligne : https://doi.org/10.3138/carto.44.3.145 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30039
in Cartographica > vol 44 n° 3 (September 2009) . - pp 145 - 158[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 031-09031 RAB Revue Centre de documentation En réserve L003 Disponible Detection, measurement and prediction of shoreline recession in Accra, Ghana / K. Appeaning Addo in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 5 (September - October 2008)
[article]
Titre : Detection, measurement and prediction of shoreline recession in Accra, Ghana Type de document : Article/Communication Auteurs : K. Appeaning Addo, Auteur ; M. Walkden, Auteur ; Jon P. Mills, Auteur Année de publication : 2008 Article en page(s) : pp 543 - 558 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse diachronique
[Termes IGN] données de terrain
[Termes IGN] érosion côtière
[Termes IGN] Ghana
[Termes IGN] incertitude des données
[Termes IGN] littoral
[Termes IGN] modèle de simulation
[Termes IGN] montée du niveau de la mer
[Termes IGN] trait de côteRésumé : (Auteur) Coastal mapping, using various data capture and feature extraction techniques, has furthered understanding of trends in shoreline evolution by allowing calculation of accurate historic rates of change that subsequently enable the prediction of future shoreline positions through different modelling procedures. The results have helped influence coastal policy formulation and promoted the development of sustainable management practices in coastal regions throughout the developed world. However, sustainable coastal management is rarely practiced in developing countries, one of the fundamental reasons for this being a general lack of reliable and accurate historic data on shoreline position. Previous studies on the Ghanaian coastal region of Accra, where accurate and reliable geospatial data for analysis is scarce, have reported erosion rates of anything between two and eight metres per year. This high level of inconsistency in reported rates has hindered effective and sustainable coastal management. The research reported in this paper addresses this issue, using mapping data from 1904, 1974, 1996 and 2002 to estimate, by linear regression, shoreline recession in the Accra region. Predictions for the next 250 yr were then undertaken using a variety of techniques ranging from a process-based numerical model, SCAPE, to geometric approaches including historical trend analysis, the modified Bruun model and Sunamura’s shore platform model. Uncertainties in the various input data were accounted for, including historic recession rates, rock strength, sediment content and, importantly, future sea-level rise under different climate change scenarios. The mean historic rate of erosion in the Accra region was found to be 1.13 m/yr(10.17 m/yr), significantly less than previously reported, though still very high. Subsequent predictions were used to identify a series of significant economic, ecological and social features at risk, and to estimate when they will most likely be lost to erosion if left unprotected. The case study illustrates that, provided suitable predictive models are selected and the uncertainties involved in working with limited data sets are dealt with appropriately, it is possible to provide statistical information in support of sustainable coastal management for developing countries in the face of a changing climate. Copyright ISPRS Numéro de notice : A2008-387 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2008.04.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2008.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29380
in ISPRS Journal of photogrammetry and remote sensing > vol 63 n° 5 (September - October 2008) . - pp 543 - 558[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-08051 SL Revue Centre de documentation Revues en salle Disponible Exploring spatial data uncertainties in land-use change scenarios / N. Dendoncker in International journal of geographical information science IJGIS, vol 22 n° 8-9 (august 2008)
[article]
Titre : Exploring spatial data uncertainties in land-use change scenarios Type de document : Article/Communication Auteurs : N. Dendoncker, Auteur ; C. Schmit, Auteur ; M. Rounsevell, Auteur Année de publication : 2008 Article en page(s) : pp 1013 - 1030 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] agrégation spatiale
[Termes IGN] carte d'occupation du sol
[Termes IGN] changement d'utilisation du sol
[Termes IGN] données localisées
[Termes IGN] incertitude des données
[Termes IGN] limite de résolution géométrique
[Termes IGN] Luxembourg
[Termes IGN] planification
[Termes IGN] rastérisation
[Termes IGN] simulationRésumé : (Auteur) This paper evaluates errors and uncertainties in representing landscapes that arise from different data rasterization methods, spatial resolutions, and downscaled land-use change (LUC) scenarios. A vector LU dataset for Luxembourg (minimum mapping unit: 0.15 ha; year 2000) was used as the baseline reference map. This map was rasterized at three spatial resolutions using three cell class assignment methods. The landscape composition and configuration of these maps were compared. Four alternative scenarios of future LUC were also generated for the three resolutions using existing LUC scenarios and a statistical downscaling method creating 37 maps of LUC for the year 2050. These maps were compared in terms of composition and spatial configuration using simple metrics of landscape fragmentation and an analysis of variance (ANOVA). Differences in landscape composition and configuration between the three cell class assignment methods and the three spatial resolutions were found to be at least as large as the differences between the LUC scenarios. This occurred in spite of the large LUC projected by the scenarios. This demonstrates the importance of the rasterization method and the level of aggregation as a contribution to uncertainty when developing future LUC scenarios and in analysing landscape structure in ecological studies. Numéro de notice : A2008-313 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810701812836 En ligne : https://doi.org/10.1080/13658810701812836 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29306
in International journal of geographical information science IJGIS > vol 22 n° 8-9 (august 2008) . - pp 1013 - 1030[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-08051 RAB Revue Centre de documentation En réserve L003 Disponible 079-08052 RAB Revue Centre de documentation En réserve L003 Disponible Fast error analysis of continuous GPS observations / M. Bos in Journal of geodesy, vol 82 n° 3 (March 2008)
[article]
Titre : Fast error analysis of continuous GPS observations Type de document : Article/Communication Auteurs : M. Bos, Auteur ; R. Fernandes, Auteur ; S. Williams, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 157 - 166 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] bruit blanc
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] données GPS
[Termes IGN] incertitude des données
[Termes IGN] série temporelleRésumé : (Auteur) It has been generally accepted that the noise in continuous GPS observations can be well described by a power-law plus white noise model. Using maximum likelihood estimation (MLE) the numerical values of the noise model can be estimated. Current methods require calculating the data covariance matrix and inverting it, which is a significant computational burden. Analysing 10 years of daily GPS solutions of a single station can take around 2 h on a regular computer such as a PC with an AMD AthlonTM 64 X2 dual core processor. When one analyses large networks with hundreds of stations or when one analyses hourly instead of daily solutions, the long computation times becomes a problem. In case the signal only contains power-law noise, the MLE computations can be simplified to a O(N log N) process where N is the number of observations. For the general case of power-law plus white noise, we present a modification of the MLE equations that allows us to reduce the number of computations within the algorithm from a cubic to a quadratic function of the number of observations when there are no data gaps. For time-series of three and eight years, this means in practise a reduction factor of around 35 and 84 in computation time without loss of accuracy. In addition, this modification removes the implicit assumption that there is no environment noise before the first observation. Finally, we present an analytical expression for the uncertainty of the estimated trend if the data only contains power-law noise. Copyright Springer Numéro de notice : A2008-167 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-007-0165-x En ligne : https://doi.org/10.1007/s00190-007-0165-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29162
in Journal of geodesy > vol 82 n° 3 (March 2008) . - pp 157 - 166[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 266-08031 RAB Revue Centre de documentation En réserve L003 Disponible 266-08032 RAB Revue Centre de documentation En réserve L003 Disponible Spatial sampling uncertainty in SMEX04 soil moisture fields: a data-based resampling experiment / M. Gebremichael in Remote sensing of environment, vol 112 n° 2 (15/02/2008)PermalinkFusion de connaissances imparfaites pour l'appariement de données géographiques / Ana-Maria Olteanu-Raimond (2008)PermalinkVisibility prediction based on artificial neural networks used in automatic network design / M. Saadatseresht in Photogrammetric record, vol 22 n° 120 (December 2007 - February 2008)PermalinkMultispectral image classification: a supervised neural computation approach based on rough-fuzzy membership function and weak fuzzy similarity relation / A. Agrawal in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkTesting the effects of thematic uncertainty on spatial decision-making / S. Hope in Cartography and Geographic Information Science, vol 34 n° 3 (July 2007)PermalinkInteractive visualization of uncertain spatial and spatio-temporal data under different scenarios: an air quality example / Edzer J. Pebesma in International journal of geographical information science IJGIS, vol 21 n° 5 (may 2007)PermalinkA probabilistic framework for representing and simulating uncertain environmental variables / Gerard B.M. Heuvelink in International journal of geographical information science IJGIS, vol 21 n° 5 (may 2007)PermalinkAssessing the effect of attribute uncertainty on the robustness of choropleth map classification / N. Xiao in International journal of geographical information science IJGIS, vol 21 n° 1-2 (january 2007)PermalinkPermalinkCan error explain map differences over time? / Robert Gilmore Pontius in Cartography and Geographic Information Science, vol 33 n° 2 (April 2006)Permalink