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Representing multiple spatial statistics in generalized elevation models: moving beyond the variogram / C. Ehlschlaeger in International journal of geographical information science IJGIS, vol 16 n° 3 (april 2002)
[article]
Titre : Representing multiple spatial statistics in generalized elevation models: moving beyond the variogram Type de document : Article/Communication Auteurs : C. Ehlschlaeger, Auteur Année de publication : 2002 Article en page(s) : pp 259 - 285 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] données localisées
[Termes IGN] incertitude géométrique
[Termes IGN] modèle d'incertitude
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] variogrammeNuméro de notice : A2002-052 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810110099116 En ligne : https://doi.org/10.1080/13658810110099116 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21969
in International journal of geographical information science IJGIS > vol 16 n° 3 (april 2002) . - pp 259 - 285[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-02031 RAB Revue Centre de documentation En réserve L003 Disponible Using process models to improve spatial analysis / S.W. Laffan in International journal of geographical information science IJGIS, vol 16 n° 3 (april 2002)
[article]
Titre : Using process models to improve spatial analysis Type de document : Article/Communication Auteurs : S.W. Laffan, Auteur Année de publication : 2002 Article en page(s) : pp 245 - 257 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse spatiale
[Termes IGN] ligne de partage des eaux
[Termes IGN] processus
[Termes IGN] variogrammeNuméro de notice : A2002-051 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810110099107 En ligne : https://doi.org/10.1080/13658810110099107 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21968
in International journal of geographical information science IJGIS > vol 16 n° 3 (april 2002) . - pp 245 - 257[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-02031 RAB Revue Centre de documentation En réserve L003 Disponible Geostatistical modelling of spatial uncertainty using P-field simulation with conditional probability fields / P. Goovaerts in International journal of geographical information science IJGIS, vol 16 n° 2 (march 2002)
[article]
Titre : Geostatistical modelling of spatial uncertainty using P-field simulation with conditional probability fields Type de document : Article/Communication Auteurs : P. Goovaerts, Auteur Année de publication : 2002 Article en page(s) : pp 167 - 178 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] géostatistique
[Termes IGN] histogramme
[Termes IGN] image SPOT
[Termes IGN] incertitude géométrique
[Termes IGN] modèle d'erreur
[Termes IGN] modèle d'incertitude
[Termes IGN] réflectance végétale
[Termes IGN] seuillage d'image
[Termes IGN] simulationRésumé : (Auteur) This paper presents a variant of p-field simulation that allows generation of spatial realizations through sampling of a set of conditional probability distribution functions (ccdf) by sets of probability values, called p-fields. Whereas in the common implementation of the algorithm the p-fields are non conditional realizations of random functions with uniform marginal distributions, they are here conditional to 0.5 probability values at data locations, which entails a preferential sampling of the central part of the ecdf around these locations. The approach is illustrated using a randomly sampled (200 observations of the NIR channel) SPOT scene of a semi-deciduous tropical forest. Results indicate that the use of conditional probability fields improves the reproduction of statistics such as histogram and semi-variogram, while yielding more accurate predictions of reflectance values than the common p-field implementation or the more CPU-intensive sequential indicator simulation. Pixel values are then classified as forest or savannah depending on whether the simulated reflectance value exceeds a given threshold value. In this case study, the proposed approach leads to a more precise and accurate prediction of the size of contiguous areas covered by savannah than the two other simulation algorithms. Numéro de notice : A2002-026 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/13658810110099125 En ligne : https://doi.org/10.1080/13658810110099125 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21943
in International journal of geographical information science IJGIS > vol 16 n° 2 (march 2002) . - pp 167 - 178[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-02021 RAB Revue Centre de documentation En réserve L003 Disponible Fast precise GPS positioning in the presence of ionospheric delays / Dennis Odijk (2002)
Titre : Fast precise GPS positioning in the presence of ionospheric delays Type de document : Monographie Auteurs : Dennis Odijk, Auteur Editeur : Delft : Netherlands Geodetic Commission NGC Année de publication : 2002 Collection : Netherlands Geodetic Commission Publications on Geodesy, ISSN 0165-1706 num. 52 Importance : 242 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-90-6132-278-8 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] ambiguïté entière
[Termes IGN] correction ionosphérique
[Termes IGN] correction troposphérique
[Termes IGN] données GPS
[Termes IGN] interpolation
[Termes IGN] krigeage
[Termes IGN] mesurage de phase
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle de Gauss-Markov
[Termes IGN] modèle ionosphérique
[Termes IGN] modèle stochastique
[Termes IGN] propagation ionosphérique
[Termes IGN] propagation troposphérique
[Termes IGN] réfraction atmosphérique
[Termes IGN] résolution d'ambiguïté
[Termes IGN] signal GPS
[Termes IGN] station virtuelle
[Termes IGN] traitement de données GNSS
[Termes IGN] traitement du signalIndex. décimale : 30.61 Systèmes de Positionnement par Satellites du GNSS Résumé : (Auteur) This thesis deals about geodetic applications of the Global Positioning System (GPS), in which the position of the GPS receiver must be determined with cm precision. This requires a relative measurement setup, together with an advanced processing strategy based on observations of the carrierphase of the signal. To keep it economically interesting, this CPS technique should be based on relatively short time spans in which the satellite observations are collected. The key to precise positioning using short time spans is to take advantage of the integer property of the ambiguities of the phase observations in the processing.
The above procedure has been applied in a successful way for the last decade to applications in which the distance between the receivers is restricted to about 10 km (the socalled rapidstatic and realtime kinematic GPS techniques over short distances). Above this distance, it is known that certain errors in the GPS observations start to significantly bias the computed receiver position when they are not taken care of. The aim of this research therefore is to develop a processing procedure, taking into account the errors in GPS observations due to propagation of the signals through the ionosphere, the atmospheric layer above about 80 kill. Although other errors (due to troposphere and satellite orbit) are of relevance as well, the research is restricted to an improved modelling of the ionospheric error. since it is by far the largest error. For the other errors standard modelling techniques are applied in this research. Using the procedure, it should be possible to determine the desired receiver positions with cmprecision using a short tinle span. The research is restricted to GPS receivers with a mutual distance of a few hundred km (mediumdistance baselines), located in midlatitude regions.
To facilitate a modelling of the ionospheric error, using the theor ' y of atmospheric refraction it is possible to decompose this error into a firstorder effect, which contains the gross of the error, plus some higherorder effects and a term due to bending of the signal path. Under worstcase conditions. the firstorder term may range up to about 80 m (on the GPS L2 frequency), whereas the accumulated effect of higherorder and bending terms can be tip to 4 cm (for L2). For the future L5 frequency (from 2008) these effects are even larger. Fortunately, because of the relative setup and the assumed medium distances, it is proved for this research it is allowed to neglect the higherorder and bending errors.
In the procedure a stochastic modelling of the firstorder ionospheric errors (referred to as ionospheric delays) is chosen. This means that the ionospheric delays are not modelled as completely unknown parameters, but that stochastic prior information is incorporated by means of ionospheric pseudoobservations. This model is referred to as the ionosphereweighted model: The weight of the ionospheric information can be tuned by the a priori standard deviation of the pseudoobservations. When this standard deviation is chosen zero, the ionosphereweighted model reduces to the ionospherefixed model, which is the usual processing model for shortdistance baselines (for which the ionospheric delays may be neglected). On the other hand, with an infinitely large ionospheric standard deviation, the model will be equivalent to the ionospherefloat model, in which the ionospheric delays are assumed as completely unknown parameters. This latter model is closely related to the ionospherefree combination, for which it is known that it cannot be used to achieve fast positioning results. It is shown that the ionosphereweighted model is only suitable for fast ambiguity resolution (and consequently positioning), when the ionospheric standard deviation is small. This requires very precise a priori ionospheric information.
The developed procedure consists of three steps. It is required that a user collects CPS observations in the vicinity of a network of permanent GPS stations. In the first step, the observations at the network stations are processed simultaneously using the ionosphereweighted model. Since in this research the goal is precise positioning within the shortest time span possible, i.e. instantaneous or singleepoch positioning, it is required that the network data is also processed instantaneously. To make instantaneous resolution of the network ambiguities possible, the sample values of the ionospheric pseudoobservations are temporal predictions based on estimates of previous epochs. Test computations using a network with a station spacing of more than 100 km demonstrated that in this way high network ambiguity success rates (close to 100%) can be obtained. In the second step, precise ambiguityfixed network ionospheric delays are spatially interpolated at the approximate location of the user's receiver. In the procedure for this purpose the concept of virtual reference station (VRS) observations is used. In this concept the network estimates (ionospheric delays and other parameters) are transformed to VRS observations. which should correspond to the data a real receiver would have collected at the user's location. The processing of the user's observations relative to this VRS is the third step of the procedure. Because of the presence of possible residual ionospheric delays also in this step the ionosphereweighted model is applied. The difference with the application in the network processing is that the sample values of the pseudoobservations are now taken zero. and the ionospheric standard deviation is computed as a function of the distance to the closest real network station. Using this, test computations demonstrated that instantaneous ambiguity success rates of 90% are feasible. When the ionospherefixed model would be applied, the success rates would not be higher than about 60%.Numéro de notice : 13101 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Monographie Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=54884 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 13101-01 30.61 Livre Centre de documentation Géodésie Disponible Artificial neural networks as a tool for spatial interpolation / J.P. Rigol in International journal of geographical information science IJGIS, vol 15 n° 4 (june 2001)
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Titre : Artificial neural networks as a tool for spatial interpolation Type de document : Article/Communication Auteurs : J.P. Rigol, Auteur ; C.H. Jarvis, Auteur ; N. Stuart, Auteur Année de publication : 2001 Article en page(s) : pp 323 - 343 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] covariance
[Termes IGN] interpolation
[Termes IGN] krigeage
[Termes IGN] modèle de simulation
[Termes IGN] prédiction
[Termes IGN] réseau neuronal artificiel
[Termes IGN] température de l'airRésumé : (Auteur) This paper describes the spatial interpolation of daily minimum air temperature using a feedforward backpropagation neural network. Simple network configurations were trained to predict minimum temperature using as inputs: (1) date and terrain variables; (2) temperature observations at a number of neighbouring locations; (3) date, terrain variables and neighbouring temperature observations. This is the first time that trend and spatial association are explicitly considered together when interpolating using a neural network. The internal weights given to different inputs to the network were analysed to estimate the degree of spatial correlation between neighbouring stations in addition to the most influential variables contributing to the underlying trend. The spatial distribution of daily minimum temperature was estimated with the greatest accuracy by a network trained on the most comprehensive data set (3). The best model for the prediction of temperature accounts for 93% of the variance, measured by the correlation between independent estimated and observed values over a full year. This is comparable to accuracies reported in the literature using other approaches such as ordinary kriging of the residuals of multi-variate linear regression or partial thin plate splines. An advantage of this method is that the guiding variables are not assumed necessarily to be linearly related with the data being interpolated, and combinative effects are taken into account. Analysis of the internal network weights confirms that the networks are able to select adaptively between trend and covariance components of the interpolation function. Example interpolated daily minimum temperature surfaces for a 100 km x 100 km area in Yorkshire, UK, were generated using the selected network architectures to illustrate the results achievable with an ANN. Numéro de notice : A2001-041 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/13658810110038951 En ligne : https://doi.org/10.1080/13658810110038951 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21743
in International journal of geographical information science IJGIS > vol 15 n° 4 (june 2001) . - pp 323 - 343[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-01041 RAB Revue Centre de documentation En réserve L003 Disponible Spatial prediction and uncertainty assessment of topographic factor for revised universal soil loss equation using digital elevation models / G. Wang in ISPRS Journal of photogrammetry and remote sensing, vol 56 n° 1 (May - June 2001)PermalinkGeomatics for environmental applications, geoENV III, Avignon, France, November 22-24 2000 / Pascal Monestiez (2001)PermalinkRemote sensing and urban analysis / Jean-Paul Donnay (2001)PermalinkCartogenèse numérique des types de sols et de leurs incertitudes par la combinaison de corrélations sur les facteurs environnementaux et des géostatistiques : application aux sols des environs de La Rochelle / F. Carre in Photo interprétation, vol 38 n° 3-4 (Septembre 2000)PermalinkCartographie de la pollution de l'air : une nouvelle approche basée sur la télédétection et les bases de données géographiques, applications à la ville de Strasbourg / A. Ung in Photo interprétation, vol 38 n° 3-4 (Septembre 2000)PermalinkEstimation et interpolation spatiale / Michel Arnaud (2000)PermalinkMéthodologie d'identification, d'évaluation et de protection des ressources en eau des aquifères régionaux par la combinaison des SIG, de la géophysique et de la géostatistique / M. Sinan (2000)PermalinkA casebook for spatial statistical data analysis / Daniel A. Griffith (1999)PermalinkSimulation d'erreurs dans une base de données géographique / Lucie Fouqué (1999)PermalinkDescription des incertitudes géométriques de l'information géographique / François Vauglin (1998)Permalink