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Termes IGN > mathématiques > statistique mathématique
statistique mathématique
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biométrie,
échantillonnage (statistique), probabilité, statistique. >>Terme(s) spécifique(s) : analyse de régression, analyse de variance, analyse des données, analyse multivariée, analyse séquentielle, calcul d'erreur, carré latin, corrélation (statistique), efficacité asymptotique (statistique), fonction pseudo-aléatoire, loi des grands nombres, modèle linéaire (statistique), modèle non linéaire (statistique), moindre carré, physique statistique, plan d'expérience, rang et sélection (statistique), rupture (statistique), SAS (logiciel), série chronologique, statistique non paramétrique, statistique robuste, tableau de contingence, test d'hypothèses (statistique), statistique stellaire. Equiv. LCSH : Mathematical statistics. Domaine(s) : 510. |
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Determining irrigated areas and quantifying blue water use in europe using remote sensing Meteosat Second Generation (MSG) products and Global Land Data Assimilation System (GLDAS) data / Mireia Romaguera in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
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[article]
Titre : Determining irrigated areas and quantifying blue water use in europe using remote sensing Meteosat Second Generation (MSG) products and Global Land Data Assimilation System (GLDAS) data Type de document : Article/Communication Auteurs : Mireia Romaguera, Auteur ; Mireia Romaguera, Auteur ; Maarten S. Krol, Auteur ; Mhd. Suhyb Salama, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 861 - 873 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] cultures irriguées
[Termes IGN] erreur systématique
[Termes IGN] Europe (géographie politique)
[Termes IGN] évapotranspiration
[Termes IGN] image MSGRésumé : (Auteur) In this paper, we propose an innovative method for identifying irrigated areas and quantifying the blue evapotranspiration (ETb), or irrigation water evapotranspired from the field. The method compares actual ET (ETactual), or crop water use, values from the Global Land Data Assimilation System (GLDAS) and remote sensing based ETactual estimates obtained from Meteosat Second Generation (MSG) satellites. Since GLDAS simulations do not account for extra water supply due to irrigation, it is expected that they underestimate ETactual during the cropping season in irrigated areas. However, remote sensing techniques based on the energy balance are able to observe the total ETactual. In order to isolate irrigation effects from other fluctuations that may lead to discrepancies between the different ETactual products, the bias between model simulations and remote sensing observations was estimated using reference targets of rainfed (non-irrigated) croplands on a daily basis in different areas across the study region (Europe). Analysis of the yearly values of ETb (irrigated area and volume obtained for croplands in Europe for 2008) showed that the method identified irrigation when yearly values were higher than 50 mm. The accuracy of the method was assessed by analyzing the spatial representativity of the calculated biases and evaluating the daily ETb values obtained. The irrigated areas were compared with the results provided by Siebert et al.(2007) and Thenkabail et al.(2009b), obtaining a spatial match of 47 and 72 percent, respectively, with overestimation of irrigated area on a country scale. Additional evaluation with the ETb results of Mekonnen and Hoekstra (2011) showed 75 percent of overlap for _50 mm range. Finally, validation with in situ data on irrigation volumes proved the cogency of our method with less than 20 percent difference between derived and measured values. Numéro de notice : A2012-432 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.8.861 En ligne : https://doi.org/10.14358/PERS.78.8.861 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31878
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 8 (August 2012) . - pp 861 - 873[article]Evaluating classification techniques for mapping vertical geology using field-based hyperspectral sensors / R.J. Murphy in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
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Titre : Evaluating classification techniques for mapping vertical geology using field-based hyperspectral sensors Type de document : Article/Communication Auteurs : R.J. Murphy, Auteur ; S. Monteiro, Auteur ; S. Schneider, Auteur Année de publication : 2012 Article en page(s) : pp 3066 - 3080 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Australie occidentale (Australie)
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification Spectral angle mapper
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] mine
[Termes IGN] ombreRésumé : (Auteur) Hyperspectral data acquired from field-based platforms present new challenges for their analysis, particularly for complex vertical surfaces exposed to large changes in the geometry and intensity of illumination. The use of hyperspectral data to map rock types on a vertical mine face is demonstrated, with a view to providing real-time information for automated mining applications. The performance of two classification techniques, namely, spectral angle mapper (SAM) and support vector machines (SVMs), is compared rigorously using a spectral library acquired under various conditions of illumination. SAM and SVM are then applied to a mine face, and results are compared with geological boundaries mapped in the field. Effects of changing conditions of illumination, including shadow, were investigated by applying SAM and SVM to imagery acquired at different times of the day. As expected, classification of the spectral libraries showed that, on average, SVM gave superior results for SAM, although SAM performed better where spectra were acquired under conditions of shadow. In contrast, when applied to hypserspectral imagery of a mine face, SVM did not perform as well as SAM. Shadow, through its impact upon spectral curve shape and albedo, had a profound impact on classification using SAM and SVM. Numéro de notice : A2012-381 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2178419 Date de publication en ligne : 03/02/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2178419 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31827
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3066 - 3080[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012081 RAB Revue Centre de documentation En réserve L003 Disponible Exploring geomorphometry through user generated content: Comparing an unsupervised geomorphometric classification with terms attached to georeferenced images in Great Britain / C. Gschwend in Transactions in GIS, vol 16 n° 4 (August 2012)
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Titre : Exploring geomorphometry through user generated content: Comparing an unsupervised geomorphometric classification with terms attached to georeferenced images in Great Britain Type de document : Article/Communication Auteurs : C. Gschwend, Auteur ; Ross S. Purves, Auteur Année de publication : 2012 Article en page(s) : pp 499 - 522 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse comparative
[Termes IGN] classification non dirigée
[Termes IGN] données localisées de référence
[Termes IGN] données localisées des bénévoles
[Termes IGN] géomorphométrie
[Termes IGN] Grande-Bretagne
[Termes IGN] modèle numérique de surface
[Termes IGN] reliefRésumé : (Auteur) User generated content such as the georeferenced images and their associated tags found in Flickr provides us with opportunities to explore how the world is described in the non-scientific, everyday language used by contributors. Geomorphometry, the quantitative study of landforms, provides methods to classify Digital Elevation Models (DEMs) according to attributes such as slope and convexity. In this article we compare the terms used in Flickr and Geograph in Great Britian to describe georeferenced images to a quantitative, unsupervised classification of a DEM, using a well established method, and explore the variation of terms across geomorphometric classes and space. Anthropogenic terms are primarily associated with more gentle slopes, while terms which refer to objects such as mountains and waterfalls are typical of steeper slopes. Terms vary both across and within classes, and the source of the user generated content has an influence on the type of term used with Geograph, a collection which aims to document the geography of Great Britain, dominated by features which might be observed on a map. Numéro de notice : A2012-364 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01307.x Date de publication en ligne : 03/05/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01307.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31810
in Transactions in GIS > vol 16 n° 4 (August 2012) . - pp 499 - 522[article]Fusion of feature selection and optimized immune networks for hyperspectral image classification of urban landscapes / J. Im in Geocarto international, vol 27 n° 5 (August 2012)
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Titre : Fusion of feature selection and optimized immune networks for hyperspectral image classification of urban landscapes Type de document : Article/Communication Auteurs : J. Im, Auteur ; Zhong Lu, Auteur ; J. Rhee, Auteur ; R. Jensen, Auteur Année de publication : 2012 Article en page(s) : pp 373 - 393 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme génétique
[Termes IGN] classification par réseau neuronal
[Termes IGN] données lidar
[Termes IGN] entropie
[Termes IGN] image AISA+
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] milieu urbain
[Termes IGN] New York (Etats-Unis ; état)Résumé : (Auteur) The urban landscape is dynamic and complex. As improved remote sensing data in terms of spatial and spectral characteristics became available, more sophisticated methods have been adopted for urban applications. This study proposed and evaluated a classification model incorporating feature selection, artificial immune networks and parameter optimization. Information gain, a broadly applied feature selection metric used in data mining techniques such as decision trees, was used for feature selection. Two types of information gain – binary-class entropy and multiple-class entropy – were investigated. Artificial immune networks have been recently applied to remote sensing classification and have been proven useful especially when multiple parameters of the networks are optimized through a genetic algorithm. The proposed model was tested for urban classification using hyperspectral (i.e. AISA and Hyperion) and LiDAR data over two urban study sites. Results show that the model considerably reduced processing time (70%) for classification without significant accuracy decrease. Numéro de notice : A2012-369 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.642898 Date de publication en ligne : 06/01/2012 En ligne : https://doi.org/10.1080/10106049.2011.642898 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31815
in Geocarto international > vol 27 n° 5 (August 2012) . - pp 373 - 393[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012051 RAB Revue Centre de documentation En réserve L003 Disponible Hyperspectral band clustering and band selection for urban land cover classification / H. Su in Geocarto international, vol 27 n° 5 (August 2012)
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Titre : Hyperspectral band clustering and band selection for urban land cover classification Type de document : Article/Communication Auteurs : H. Su, Auteur ; Q. Du, Auteur Année de publication : 2012 Article en page(s) : pp 39 - 411 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification semi-dirigée
[Termes IGN] image hyperspectrale
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] précision de la classification
[Termes IGN] signature spectrale
[Termes IGN] valeur aberranteRésumé : (Auteur) The aim of this study is to combine band clustering with band selection for dimensionality reduction of hyperspectral imagery. The performance of dimensionality reduction is evaluated through urban land cover classification accuracy with the dimensionality-reduced data. Different from unsupervised clustering using all the pixels or supervised clustering requiring labelled pixels, the discussed semi-supervised band clustering needs class spectral signatures only; band selection result is used as initial condition for band clustering; after clustering, a cluster selection step is applied to select clusters to be used in the following data analysis. In this article, we propose to conduct band selection by removing outlier bands in each cluster before finalizing cluster centres. The experimental results in urban land cover classification show that the proposed algorithm can further enhance support vector machine (SVM)-based classification accuracy. Numéro de notice : A2012-370 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.643322 Date de publication en ligne : 12/01/2012 En ligne : https://doi.org/10.1080/10106049.2011.643322 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31816
in Geocarto international > vol 27 n° 5 (August 2012) . - pp 39 - 411[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012051 RAB Revue Centre de documentation En réserve L003 Disponible IconMap-based visualisation technique and its application in soil fertility analysis / X. Zhang in Cartographic journal (the), vol 49 n° 3 (August 2012)
PermalinkImproving the estimation of fractional-cycle biases for ambiguity resolution in precise point positioning / J. Geng in Journal of geodesy, vol 86 n° 8 (August 2012)
PermalinkMapping crop types, irrigated areas, and cropping intensities in heterogeneous landscapes of southern India using multi-temporal medium-resolution imagery: implications for assessing water use in agriculture / E. Heller in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
PermalinkMapping fragmented agricultural systems in the Sudano-Sahelian environments of Africa using random forest and ensemble metrics of coarse resolution MODIS imagery / E. Vintrou in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
PermalinkMemory-based cluster sampling for remote sensing image classification / Michele Volpi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
PermalinkMonitoring GOCE gradiometer calibration parameters using accelerometer and star sensor data: methodology and first results / C. Siemes in Journal of geodesy, vol 86 n° 8 (August 2012)
PermalinkOptimal regularization for geopotential model GOCO02S by Monte Carlo methods and multi-scale representation of density anomalies / Karl Rudolf Koch in Journal of geodesy, vol 86 n° 8 (August 2012)
PermalinkPhenology-based crop classification algorithm and its implications on agricultural water use assessments in California's central valley / L. Zhong in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
PermalinkPoint-to-plane registration of terrestrial laser scans / D. Grant in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)
PermalinkSatellite image time series analysis under time warping / F. Petitjean in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
PermalinkSpatio-temporal MODIS EVI gap filling under cloud cover: An example in Scotland / L. Poggio in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)
PermalinkSynthesizing urban remote sensing through application, scale, data and case studies / E.A. Wentz in Geocarto international, vol 27 n° 5 (August 2012)
PermalinkTemporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan / F. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)
PermalinkTotal least squares adjustment in partial errors-in-variables models: algorithm and statistical analysis / P. Xu in Journal of geodesy, vol 86 n° 8 (August 2012)
PermalinkStreamed vertical rectangle detection in terrestrial laser scans for facade database / Jérôme Demantké in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)
PermalinkTrees detection from laser point clouds acquired in dense urban areas by a mobile mapping system / Fabrice Monnier in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol I-3 (2012)
PermalinkAn automated approach for updating land cover maps based on integrated change detection and classification methods / X. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
PermalinkApplication of time series Landsat images to examining land-use/land-cover dynamic change / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 7 (July 2012)
PermalinkApplication of time series Landsat images to examining land-use / land-cover dynamic change / Dong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 7 (July 2012)
PermalinkBuilding detection in complex thorough effective separation of buildings from trees / M. Awrangjeb in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 7 (July 2012)
PermalinkDynamics of coastal landform features along the southern Tamil Nadu of India by using remote sensing and Geographic Information System / P. Mujabar in Geocarto international, vol 27 n° 4 (July 2012)
PermalinkError assessment of the initial near real-time METOP ASCAT surface soil moisture product / S. Hahn in IEEE Transactions on geoscience and remote sensing, vol 50 n° 7 Tome 1 (July 2012)
PermalinkA fuzzy index for detecting spatiotemporal outliers / George Grekousis in Geoinformatica, vol 16 n° 3 (July 2012)
PermalinkLatent class modeling for site- and non-site-specific classification accuracy assessment without ground data / Giles M. Foody in IEEE Transactions on geoscience and remote sensing, vol 50 n° 7 Tome 2 (July 2012)
PermalinkLong term land cover and seagrass mapping using Landsat and object-based image analysis from 1972 to 2010 in the coastal environment of South East Queensland, Australia / M. Lyons in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
PermalinkQualitative and quantitative description of multibeam echosounder systematic errors on rocky areas / Nathalie Debese in Marine geodesy, vol 35 n° 3 (July - September 2012)
PermalinkSeparation of global time-variable gravity signals into maximally independent components / E. Forootan in Journal of geodesy, vol 86 n° 7 (July 2012)
PermalinkThe affine constrained GNSS attitude model and its multivariate integer least-squares solution / Peter J.G. Teunissen in Journal of geodesy, vol 86 n° 7 (July 2012)
PermalinkThe potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass / T.M. Basuki in Geocarto international, vol 27 n° 4 (July 2012)
PermalinkVerification of 2D building outlines using oblique airborne images / A. Nyaruhuma in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
Permalink3-D mapping of a multi-layered Mediterranean forest using ALS data / António Ferraz in Remote sensing of environment, vol 121 (June 2012)
PermalinkAnalysis of 4 years (2002-2005) of laser data on Starlette, Stella and LAGEOS-1/2 satellites for stations coordinates and Earth orientations parameters (EOP) / Bachir Gourine in Bulletin des sciences géographiques, n° 27 (juin 2012)
PermalinkApproximation theory applied to DEM vertical accuracy assessment / X. Liu in Transactions in GIS, vol 16 n° 3 (June 2012)
PermalinkA comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region / Dong Lu ; E. Moran ; et al. in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
PermalinkComparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points / Y. Shao in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
PermalinkDiscovering spatial patterns in origin-destination mobility data / D. Guo in Transactions in GIS, vol 16 n° 3 (June 2012)
PermalinkEstimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions / M. Cutler in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
PermalinkA framework for automatic and unsupervised detection of multiple changes in multitemporal images / Francesca Bovolo in IEEE Transactions on geoscience and remote sensing, vol 50 n° 6 (June 2012)
PermalinkA framework for supervised image classification with incomplete training samples / Q. Guo in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 6 (June 2012)
PermalinkGeometric unmixing of large hyperspectral images: A barycentric coordinate approach / Paul Honeine in IEEE Transactions on geoscience and remote sensing, vol 50 n° 6 (June 2012)
PermalinkOn the detectability of synthetic disturbances in FG5 absolute gravimetry data using lomb-scargle analysis / M. Orlob in Geomatica, vol 66 n° 2 (June 2012)
PermalinkQuality assessment of geometric façade models reconstructed from TLS data / Tania Landes in Photogrammetric record, vol 27 n° 138 (June - August 2012)
PermalinkVisibility monitoring using conventional roadside cameras : Emerging applications / Raouf Babari in Transportation Research - Part C: Emerging Technologies, vol 22 (June 2012)
PermalinkEstimating forest attribute parameters for small areas using nearest neighbors techniques / Ronald E. McRoberts in Forest ecology and management, vol 272 (mai 2012)
PermalinkDétermination de la ligne de côte par des images multi-spectrales haute résolution / Valerio Baiocchi in Géomatique expert, n° 86 (01/05/2012)
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