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Spatial data quality / P. Van Oort (2005)
Titre : Spatial data quality : from description to application Type de document : Monographie Auteurs : P. Van Oort, Auteur Editeur : Delft : Netherlands Geodetic Commission NGC Année de publication : 2005 Collection : Netherlands Geodetic Commission Publications on Geodesy, ISSN 0165-1706 num. 60 Importance : 125 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-90-6132-295-5 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] base de données d'occupation du sol
[Termes IGN] covariance
[Termes IGN] données localisées
[Termes IGN] erreur de classification
[Termes IGN] généalogie des données
[Termes IGN] incertitude des données
[Termes IGN] occupation du sol
[Termes IGN] précision de la classification
[Termes IGN] qualité des données
[Termes IGN] terminologie
[Termes IGN] varianceRésumé : (Auteur) The growing availability of spatial data along with growing ease to use the spatial data (thanks to wide-scale adoption of GIS) have made it possible to use spatial data in applications inappropriate considering the quality of the data. As a result, concerns about spatial data quality have increased. To deal with these concerns, it is necessary to (1) formalise and standardise descriptions of spatial data quality and (2) to apply these descriptions in assessing the suitability (fitness for use) of spatial data, before using the data. The aim of this thesis was twofold: (1) to enhance the description of spatial data quality and (2) to improve our understanding of the implications of spatial data quality.
Chapter 1 sets the scene with a discussion on uncertainty and an explanation of why concerns about spatial data quality exist. Knowledge gaps are identified and the chapter concludes with six research questions.
Chapter 2 presents an overview of definitions of spatial data quality. Overall, I found a strong agreement on which elements together define spatial data quality. Definitions appear to differ in two aspects: (1) the location within the meta-data report: some elements occur not in the spatial data quality section but in another section of the meta-data report-, and (2) the explicitness with which elements are recognised as individual elements. For example, the European pre-standard explicitly recognises the element 'homogeneity'. Other standards recognise the importance of documenting the variation in quality, without naming it explicitly as an individual element.
In chapter 3, we quantified the spatial variability in classification accuracy for the agricultural crops in the Dutch national land cover database (LGN). Classification accuracy was significantly correlated with: (1) the crop present according to LGN, (2) the homogeneity of the 8-cell neighbourhood around each cell, (3) the size of the patch in which a cell is located, and (4) the heterogeneity of the landscape in which a cell is located.
In chapter 4, I present methods that use error matrices and change detection error matrices as input to make more accurate land cover change estimates. It was shown that temporal correlation in classification errors has a significant impact and must be taken into account. Producers of lime series land cover data are recommended not only to report error matrices, but also change detection error matrices.
Chapter 5 focuses on positional accuracy and area estimates. From the positional accuracy of vertices delineating polygons, the variance and covariance in area can be derived. Earlier studies derived equations for the variance, this chapter presents a covariance equation. The variance and covariance equation were implemented in a model and applied in a case-study. The case-study consisted of 97 polygons with a small subsidy value (in euros per hectare) assigned to each polygon. With the model we could calculate the uncertainty in the total subsidy value (in euros) of the complete set of polygons as a consequence of uncertainty in the position of vertices.
Chapter 6 explores the relationship between completeness of spatial data and risk in digging activities around underground cables and pipelines. A model is presented for calculating the economic implications of over- and incompleteness. An important element of this model is the relationship between detection lime and costs. The model can be used to calculate the optimal detection time, i.e. the time at which expected costs are at their minimum.
Chapter 7 addresses the question why risk analysis (RA) is so rarely applied to assess the suitability of spatial data prior to using the data. In theory, the use of RA is beneficial because it allows the user to judge if the use of certain spatial data does not produce unacceptable risks. Frequently proposed hypotheses explaining the scarce adoption of RA are all technical and educational. In chapter 7 we propose a new group of hypotheses, based on decision theory. We found that the willingness to spend resources on RA depends (1) on the presence of feedback mechanisms in the decision-making process, (2) on how much is at stake and (3) to a minor extent on how well the decision-making process can be modelled.
Chapter 8 prescrits conclusions on the six research questions (chapters 2-7) and lists recommendations for users, producers and researchers of spatial data. With regard to the description, four recommendations are given. Firstly, spend more effort on documenting the lineage of reference data. Secondly, quantify and report correlation of quality between related data sets. Thirdly, investigate the integration of different forms of uncertainty (error, vagueness, ambiguity). Fourthly, study the implementation and use of spatial data quality standards. With regard to the application of spatial data quality descriptions, I have two main recommendations. Firstly, to continue the line of research followed in this thesis: quantification of implications of spatial data quality, through development of theory along with tangible illustrations in case-studies. Secondly, there is a need for more empirical research into how users cope with spatial data quality.Numéro de notice : 13261 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=54944 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 13261-02 37.00 Livre Centre de documentation Géomatique Disponible 13261-01 37.00 Livre Centre de documentation Géomatique Disponible Scaling net primary production to a MODIS footprint in support of Earth observing system product validation / D. Turner in International Journal of Remote Sensing IJRS, vol 25 n° 10 (May 2004)
[article]
Titre : Scaling net primary production to a MODIS footprint in support of Earth observing system product validation Type de document : Article/Communication Auteurs : D. Turner, Auteur ; S. Ollinger, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 1961 - 1979 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] erreur de classification
[Termes IGN] erreur de mesure
[Termes IGN] hétérogénéité
[Termes IGN] image Terra-MODIS
[Termes IGN] incertitude géométrique
[Termes IGN] mise à l'échelleRésumé : (Auteur) Release of an annual global terrestrial net primary production (NPP) data layer has begun in association with the Moderate Imaging Spectroradiometer (MODIS) sensor, a component of the NASA Earth Observing System. The task of validating this product will be complicated by the mismatch in scale between groundbased NPP measurements and the coarse resolution (1 km) of the NPP product. In this paper we describe three relevant approaches to scaling NPP from the plot level to the approximately 25km2 footprint of the sensor, and discuss issues associated with operational comparisons to the MODIS NPP product. All approaches revealed considerable spatial heterogeneity in NPP at scales less than the resolution of the MODIS NPP product. The effort to characterize uncertainty in the validation data layers indicated the importance of treating the combination of classification error, sampling error, and measurement error. Generally, the optimal procedure for scaling NPP to a MODIS footprint will depend on local vegetation type, the scale of spatial heterogeneity, and available resources. In all approaches, high resolution remote sensing can play a critical role in characterizing land cover and relevant biophysical variables. Numéro de notice : A2004-145 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000150013 En ligne : https://doi.org/10.1080/0143116031000150013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26672
in International Journal of Remote Sensing IJRS > vol 25 n° 10 (May 2004) . - pp 1961 - 1979[article]Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 080-04081 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Improving the performance of classifiers in high-dimensional remote sensing applications: an adaptive resampling strategy for error-prone exemplars / C. Bachmann in IEEE Transactions on geoscience and remote sensing, vol 41 n° 9 (September 2003)
[article]
Titre : Improving the performance of classifiers in high-dimensional remote sensing applications: an adaptive resampling strategy for error-prone exemplars Type de document : Article/Communication Auteurs : C. Bachmann, Auteur Année de publication : 2003 Article en page(s) : pp 2101 - 2112 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classificateur
[Termes IGN] échantillonnage d'image
[Termes IGN] erreur de classification
[Termes IGN] image hyperspectrale
[Termes IGN] occupation du sol
[Termes IGN] optimisation (mathématiques)Résumé : (Auteur) In the past, "active learning" strategies have been proposed for improving the convergence and accuracy of statistical classifiers. However, many of these approaches have large storage requirements or unnecessarily large computational burdens and, therefore, have been impractical for the largescale databases typically, found in remote sensing, especially hyperspectral applications. In this paper, we develop a practical online approach with only modest storage requirements. The new approach improves the convergence rate associated with the optimization of adaptive classifiers, especially in highdimensional remote sensing data. We demonstrate the new approach using PROBE2 hyperspectral imagery and find convergence time improvements of two orders of magnitude in the optimization of landcover classifiers. Numéro de notice : A2003-254 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.817207 En ligne : https://doi.org/10.1109/TGRS.2003.817207 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22549
in IEEE Transactions on geoscience and remote sensing > vol 41 n° 9 (September 2003) . - pp 2101 - 2112[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-03091 RAB Revue Centre de documentation En réserve L003 Disponible Expert system house detection in high spatial resolution: Imagery using size, shape, and context / J.A. Tullis in Geocarto international, vol 18 n° 1 (March - May 2003)
[article]
Titre : Expert system house detection in high spatial resolution: Imagery using size, shape, and context Type de document : Article/Communication Auteurs : J.A. Tullis, Auteur ; J.R. Jensen, Auteur Année de publication : 2003 Article en page(s) : pp 5 - 15 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] acquisition de connaissances
[Termes IGN] analyse texturale
[Termes IGN] base de connaissances
[Termes IGN] détection du bâti
[Termes IGN] erreur de classification
[Termes IGN] exploration de données
[Termes IGN] fusion d'images
[Termes IGN] image à résolution métrique
[Termes IGN] image Ikonos
[Termes IGN] image multibande
[Termes IGN] image panchromatique
[Termes IGN] luminance lumineuse
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] photo-interprétation assistée par ordinateur
[Termes IGN] système expertRésumé : (Auteur) IKONOS 1 x 1 m panchromatic data fused with 4 X 4 m multispectral data were used for residential house detection in three 1 X 1 km study areas of Columbia, South Carolina. One study area contained houses built in the 1940s, another in the 1970s, and another in the 1990s. An expert system was developed to extract individual houses from the imagery. The system employed a data mining algorithm as the core of an automated knowledge acquisition module. Separate knowledge bases were generated for each study area using training samples and the data mining algorithm in two sequential stages. In the first stage, brightness values and NDVI yielded a knowledge base that was used to locate candidate house pixels. In the second stage, region metrics including size, shape, and a series of context variables were employed. Regions of asphalt roads mistakenly identified by the expert system as houses were removed using road buffers. Also, separate knowledge bases were generated both with and without the use of context variables. Each scenario was compared with a point map of photointerpreted (reference) houses. The photointerpreted database was verified against in situ housing counts. There was a strong increasing trend in both machine and photointerpreter accuracy as housing age decreased, with the highest accuracies (79 88%) in the 1990s study area. Numéro de notice : A2003-098 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040308542258 En ligne : https://doi.org/10.1080/10106040308542258 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22394
in Geocarto international > vol 18 n° 1 (March - May 2003) . - pp 5 - 15[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-03011 RAB Revue Centre de documentation En réserve L003 Disponible Modèle d'erreurs dans une base de données géographiques et grandes déviations pour des sommes pondérées / Olivier Bonin (2002)
Titre : Modèle d'erreurs dans une base de données géographiques et grandes déviations pour des sommes pondérées : application à l'estimation d'erreurs sur un temps de parcours Type de document : Thèse/HDR Auteurs : Olivier Bonin , Auteur ; D. Pierre-Loti-Viaud, Directeur de thèse Editeur : Paris : Université de Paris 6 Pierre et Marie Curie Année de publication : 2002 Importance : 145 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse de doctorat de l'université Paris 6, spécialité mathématiques, option statistique
PAS DE DOCUMENT SUR HAL - à demander à Sorbonne Université. Bibliothèque de Sorbonne Université. Bibliothèque Mathématiques-Informatique Recherche.Langues : Français (fre) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données localisées
[Termes IGN] calcul d'itinéraire
[Termes IGN] erreur d'attribut
[Termes IGN] erreur de classification
[Termes IGN] incertitude géométrique
[Termes IGN] modèle d'erreur
[Termes IGN] modèle statistique
[Termes IGN] qualité des données
[Termes IGN] simulation
[Termes IGN] terrain nominalIndex. décimale : THESE Thèses et HDR Note de contenu : 1+++ QUALITE DES BASES DE DONNEES GEOGRAPHIQUES ET APPLICATIONS GEOGRAPHIQUES
1. QUALITE DES DONNEES GEOGRAPHIQUES
1.1. Information géographique
1.2. Cadre de l'étude
1.3. Qualité d'un base de données géographiques
1.4. Terrain nominal
1.5. Composantes de la qualité
1.6. Indicateurs de la qualité sémantique
1.7. Modèles d'incertitude
2. MODELISATION D'ERREURS D'ATTRIBUTS DANS UNE BASE DE DONNEES GEOGRAPHIQUES
2.1. Cadre du modèle
2.2. Estimation des paramètres du modèle
2.3. Hypothèses simplificatrices
2.4. Paramétrisation
2.5. Calcul d'estimateurs
2.6. Étude de contrôles qualité sur des données réelles
3. IMPACT DE LA QUALITE DES DONNEES SUR UNE APPLICATION
3.1. Application géographique
3.2. Exemple : calcul d'itinéraires
3.3. Influence de la qualité sur un calcul d'itinéraires
2+++ ETUDE PAR SIMULATION
1. PRINCIPE DE L'ANALYSE DE SENSIBILITE GEOGRAPHIQUE
2. BRUITAGE CONTROLE D'UNE BASE DE DONNEES GEOGRAPHIQUES
2.1. Bruitage des attributs
2.2. Bruitage de la géométrie
3. ETUDE D'UNE APPLICATION DE CALCUL D'ITINERAIRES
3.1. Introduction
3.2. Methodologie
3.3. Implémentation
3.4. Analyse des données
3.5. Conclusion
3+++ ETUDE DES ERREURS D'ATTRIBUTS
1. MODELE DE L'APPLICATION ET CRITERE DE QUALITE DES RESULTATS
1.1. Modèle de déplacement en zone urbaine
1.2. Critère de qualité des résultats de l'application
2. INTRODUCTION AUX DEVELOPPEMENTS DE GRANDES DEVIATIONS
2.1. Principe de la méthode
2.2. Transformation exponentielle
2.3. Développements d'Edgeworth
3. GRANDES DEVIATIONS POUR DES SOMMES PONDEREES DE VARIABLES I.I.D
3.1. Introduction and statement of the problem
3.2. Geographical model and reduction to a large deviation problem
3.3. Results and discussions
3.4. Large deviation theorems
3.5. Preuves des théorèmes
3.6. Cas i.i.d
3.7. Commentaires sur les résultats obtenus
4+++ ETUDE DES ERREURS D'ATTRIBUTS ET DE GEOMETRIE
1. MODELES D'ERREURS DE LONGUEURS DES TRONÇONS
1.1. Modèle fondé sur les erreurs de position
1.2. Modèle simplifié
2. CALCUL DE TEMPS DE PARCOURS ET CRITERE DE QUALITE
3. APPLICATIONS NUMERIQUES
5+++ ETUDE DE L'INFLUENCE DU CHOIX DE L'ITINERAIRE ET ERREURS SUR DES PARCOURS DE LONGUEUR ALEATOIRE
1. INFLUENCE DU CHOIX DE L'ITINERAIRE
2. ERREURS SUR UN ITINERAIRE TYPE
2.1. Grandes déviations pour lois composées
2.2. Application à une base de données routières
2.3. Développement de l'asymptotique y > ooNuméro de notice : 11812 Affiliation des auteurs : non IGN Autre URL associée : URL sans document Thématique : GEOMATIQUE/INFORMATIQUE Nature : Thèse française Note de thèse : Thèse de doctorat : Mathématiques, statistique : Paris 6 : 2002 Organisme de stage : COGIT (IGN) nature-HAL : Thèse DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=45171 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 11812-01 THESE Livre Centre de documentation Thèses Disponible 11812-02 THESE Livre LASTIG Dépôt en unité Exclu du prêt Using spatial autocorrelation analysis to explore the errors in maps generated from remotely sensed data / Russell G. Congalton in Photogrammetric Engineering & Remote Sensing, PERS, vol 54 n° 5 (may 1988)Permalink