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An aggregated graph to qualify historical spatial networks using temporal patterns detection / Benoit Costes (2015)
Titre : An aggregated graph to qualify historical spatial networks using temporal patterns detection Type de document : Article/Communication Auteurs : Benoit Costes , Auteur ; Julien Perret , Auteur ; Bénédicte Bucher , Auteur ; Maurizio Gribaudi, Auteur Editeur : Association of Geographic Information Laboratories in Europe AGILE Année de publication : 2015 Conférence : AGILE 2015, 18th International Conference on Geographic Information Science, Geographic Information Science as an enabler of smarter cities and communities 09/06/2015 12/06/2015 Lisbonne Portugal OA Proceedings Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] carte ancienne
[Termes IGN] cohérence des données
[Termes IGN] détection d'anomalie
[Termes IGN] graphe
[Termes IGN] modèle topologique complet
[Termes IGN] Paris (75)
[Termes IGN] réseau routierRésumé : (auteur) This paper introduces a model of an aggregated graph suitable to study dynamics of city street networks, and a method to build it. Using temporal pattern detection, it allows detecting inconsistencies in historical spatial networks attributable mainly to old maps themselves, without ground truth data but by comparing each data with each other, and helps to take into account their imperfections such as differences in levels of detail, incompleteness, fuzzy temporalisation, geometric inaccuracies and so on, in the objective of performing further spatio-temporal analyses with corrected data. Our model is applied on Paris old street network at five different temporalities. Numéro de notice : C2015-011 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl En ligne : https://agile-online.org/index.php/conference/proceedings/proceedings-2015 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81041 Documents numériques
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An aggregated graphAdobe Acrobat PDF A discriminative metric learning based anomaly detection method / Bo Du in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)
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Titre : A discriminative metric learning based anomaly detection method Type de document : Article/Communication Auteurs : Bo Du, Auteur ; L. Zhang, Auteur Année de publication : 2014 Article en page(s) : pp 6844 - 6857 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage (cognition)
[Termes IGN] détection d'anomalie
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à haute résolutionRésumé : (Auteur) Due to the high spectral resolution, anomaly detection from hyperspectral images provides a new way to locate potential targets in a scene, especially those targets that are spectrally different from the majority of the data set. Conventional Mahalanobis-distance-based anomaly detection methods depend on the background statistics to construct the anomaly detection metric. One of the main problems with these methods is that the Gaussian distribution assumption of the background may not be reasonable. Furthermore, these methods are also susceptible to contamination of the conventional background covariance matrix by anomaly pixels. This paper proposes a new anomaly detection method by effectively exploiting a robust anomaly degree metric for increasing the separability between anomaly pixels and other background pixels, using discriminative information. First, the manifold feature is used so as to divide the pixels into the potential anomaly part and the potential background part. This procedure is called discriminative information learning. A metric learning method is then performed to obtain the robust anomaly degree measurements. Experiments with three hyperspectral data sets reveal that the proposed method outperforms other current anomaly detection methods. The sensitivity of the method to several important parameters is also investigated. Numéro de notice : A2014-541 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2303895 En ligne : https://doi.org/10.1109/TGRS.2014.2303895 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74158
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 11 tome 1 (November 2014) . - pp 6844 - 6857[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014111A RAB Revue Centre de documentation En réserve L003 Disponible Spectroscopic remote sensing of plant stress at leaf and canopy levels using the chlorophyll 680 nm absorption feature with continuum removal / I.D. Sanches in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)
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Titre : Spectroscopic remote sensing of plant stress at leaf and canopy levels using the chlorophyll 680 nm absorption feature with continuum removal Type de document : Article/Communication Auteurs : I.D. Sanches, Auteur ; C.R. Souza Filho, Auteur ; Raymond Floyd Kokaly, Auteur Année de publication : 2014 Article en page(s) : pp 111 – 122 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Airborne Visible/InfraRed Imaging Spectrometer
[Termes IGN] détection d'anomalie
[Termes IGN] indice de végétation
[Termes IGN] spectromètre imageur
[Termes IGN] stress hydrique
[Termes IGN] teneur en chlorophylle des feuillesRésumé : (Auteur) This paper explores the use of spectral feature analysis to detect plant stress in visible/near infrared wavelengths. A time series of close range leaf and canopy reflectance data of two plant species grown in hydrocarbon-contaminated soil was acquired with a portable spectrometer. The ProSpecTIR-VS airborne imaging spectrometer was used to obtain far range hyperspectral remote sensing data over the field experiment. Parameters describing the chlorophyll 680 nm absorption feature (depth, width, and area) were derived using continuum removal applied to the spectra. A new index, the Plant Stress Detection Index (PSDI), was calculated using continuum-removed values near the chlorophyll feature centre (680 nm) and on the green-edge (560 and 575 nm). Chlorophyll feature’s depth, width and area, the PSDI and a narrow-band normalised difference vegetation index were evaluated for their ability to detect stressed plants. The objective was to analyse how the parameters/indices were affected by increasing degrees of plant stress and to examine their utility as plant stress indicators at the remote sensing level (e.g. airborne sensor). For leaf data, PSDI and the chlorophyll feature area revealed the highest percentage (67–70%) of stressed plants. The PSDI also proved to be the best constraint for detecting the stress in hydrocarbon-impacted plants with field canopy spectra and airborne imaging spectroscopy data. This was particularly true using thresholds based on the ASD canopy data and considering the combination of higher percentage of stressed plants detected (across the thresholds) and fewer false-positives. Numéro de notice : A2014-526 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.08.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.08.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74139
in ISPRS Journal of photogrammetry and remote sensing > vol 97 (November 2014) . - pp 111 – 122[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014111 RAB Revue Centre de documentation En réserve L003 Disponible
[article]
Titre : On detecting spatial categorical outliers Type de document : Article/Communication Auteurs : X. Liu, Auteur ; Feng Chen, Auteur ; Tien Lu, Auteur Année de publication : 2014 Article en page(s) : pp 501 - 536 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] détection d'anomalie
[Termes IGN] valeur aberranteRésumé : (Auteur)Spatial outlier detection is an important research problem that has received much attentions in recent years. Most existing approaches are designed for numerical attributes, but are not applicable to categorical ones (e.g., binary, ordinal, and nominal) that are popular in many applications. The main challenges are the modeling of spatial categorical dependency as well as the computational efficiency. This paper presents the first outlier detection framework for spatial categorical data. Specifically, a new metric, named as Pair Correlation Ratio (PCR), is measured for each pair of category sets based on their co-occurrence frequencies at specific spatial distance ranges. The relevances among spatial objects are then calculated using PCR values with regard to their spatial distances. The outlierness for each object is defined as the inverse of the average relevance between an object and its spatial neighbors. Those objects with the highest outlier scores are returned as spatial categorical outliers. A set of algorithms are further designed for single-attribute and multi-attribute spatial categorical datasets. Extensive experimental evaluations on both simulated and real datasets demonstrated the effectiveness and efficiency of our proposed approaches. Numéro de notice : A2014-499 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-013-0188-9 Date de publication en ligne : 28/09/2013 En ligne : https://doi.org/10.1007/s10707-013-0188-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74091
in Geoinformatica > vol 18 n° 3 (July 2014) . - pp 501 - 536[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-2014031 RAB Revue Centre de documentation En réserve L003 Disponible Impact of signal contamination on the adaptive detection performance of local hyperspectral anomalies / Stefania Matteoli in IEEE Transactions on geoscience and remote sensing, vol 52 n° 4 (April 2014)
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Titre : Impact of signal contamination on the adaptive detection performance of local hyperspectral anomalies Type de document : Article/Communication Auteurs : Stefania Matteoli, Auteur ; Marco Diani, Auteur ; Giovanni Corsini, Auteur Année de publication : 2014 Article en page(s) : pp 1948 - 1968 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] contamination
[Termes IGN] covariance
[Termes IGN] dégradation du signal
[Termes IGN] détection d'anomalie
[Termes IGN] filtrage du bruit
[Termes IGN] image hyperspectrale
[Termes IGN] rapport signal sur bruit
[Termes IGN] signature spectrale
[Termes IGN] variabilitéRésumé : (Auteur) The effects of signal contamination of secondary data are investigated in the framework of adaptive target detection in remotely sensed hyperspectral images. In contrast to previous studies on signal contamination, the focus of this paper is the detection of targets with unknown spectral signatures (i.e., anomalies) and adaptive detection methods based on a local estimation of the background covariance matrix. Contamination due to the target signal is expected to have a more severe impact when the number of secondary data is limited. An analytical model for signal contamination is developed that allows variability in the extent of contamination. Several parameters, such as the contamination fraction of secondary data and the contaminating signal energy, are introduced, and a contaminating signal-to-interference-plus-noise ratio is derived as an objective measure of contamination. The proposed model is employed to experimentally evaluate signal contamination effects and the impact of its variability on the performance of adaptive detection of local anomalies. The outcomes of the experimental study are substantiated by validation with real hyperspectral data. The results obtained highlight the relevance that the impact of signal contamination, assessed with respect to different system parameters, may have for practical applications. This paper represents a starting point for the development of detection performance forecasting models that consider signal contamination. Numéro de notice : A2014-266 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2256915 En ligne : https://doi.org/10.1109/TGRS.2013.2256915 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33169
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 4 (April 2014) . - pp 1948 - 1968[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014041 RAB Revue Centre de documentation En réserve L003 Disponible Homogénéisation des séries temporelles GPS par la méthode de la segmentation / François Guillamon (2014)PermalinkModels and methods for automated background density estimation in hyperspectral anomaly detection / Stefania Matteoli in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)PermalinkMotifs spatio-temporels de trajectoires, de l'extraction à la détection de comportements inhabituels / Laurent Etienne in Cartes & Géomatique, n° 215 (mars 2013)PermalinkA time-efficient method for anomaly detection in hyperspectral images / O. Duran in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkWide-angle airborne laser range data analysis for relative height determination of ground-based benchmarks / Olivier Bock in Journal of geodesy, vol 76 n° 6-7 (July 2002)PermalinkThe resolution of mean sea level anomalies along the NSM coastline using the Global Positioning System / R.T. Macleod (1990)Permalink