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Identification and analysis of groundwater potential zones in Ken-Betwa river linking area using remote sensing and geographic information system / R. Avtar in Geocarto international, vol 25 n° 5 (August 2010)
[article]
Titre : Identification and analysis of groundwater potential zones in Ken-Betwa river linking area using remote sensing and geographic information system Type de document : Article/Communication Auteurs : R. Avtar, Auteur ; C. Singh, Auteur ; A. Singh, Auteur ; S. Mukherjee, Auteur Année de publication : 2010 Article en page(s) : pp 379 - 396 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte thématique
[Termes IGN] eau souterraine
[Termes IGN] exploration
[Termes IGN] hydrogéologie
[Termes IGN] identification automatique
[Termes IGN] image Landsat-ETM+
[Termes IGN] Inde
[Termes IGN] MNS SRTM
[Termes IGN] système d'information géographiqueRésumé : (Auteur) The use of remote sensing data with other ancillary data in a geographic information system (GIS) environment is useful to delineate groundwater potential zonation map of Ken-Betwa river linking area of Bundelkhand. Various themes of information such as geomorphology, land use/land cover, lineament extracted from digital processing of Landsat (ETM+) satellite data of the year 2005 and drainage map were extracted from survey of India topographic sheets, and elevation, slope data were generated from shuttle radar topography mission (SRTM) digital elevation model (DEM). These themes were overlaid to generate groundwater potential zonation (GWPZ) map of the area. The final map of the area shows different zones of groundwater prospects, viz., good (5.22% of the area), moderate (65.83% of the area) poor (15.31% of the area) and very poor (13.64% of area). Numéro de notice : A2010-311 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106041003731318 Date de publication en ligne : 28/05/2010 En ligne : https://doi.org/10.1080/10106041003731318 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30505
in Geocarto international > vol 25 n° 5 (August 2010) . - pp 379 - 396[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2010051 RAB Revue Centre de documentation En réserve L003 Disponible Automatic identification of high streets and classification of urban land use in large scale topographic database / Omair Chaudhry (2010)
contenu dans Proceedings of the GIS Research UK, 18th annual conference, University College London, 14th - 16th April 2010 / Muki M. Haklay (2010)
Titre : Automatic identification of high streets and classification of urban land use in large scale topographic database Type de document : Article/Communication Auteurs : Omair Chaudhry, Auteur ; Médéric Gravelle, Auteur ; Nicolas Regnauld , Auteur Editeur : Geographical Information Science Research - UK GISRUK Année de publication : 2010 Conférence : GISRUK 2010, 18th GIS Research UK annual conference 14/04/2010 16/04/2010 Londres Royaume-Uni Open access proceedings Langues : Anglais (eng) Descripteur : [Termes IGN] autoroute
[Termes IGN] base de données topographiques
[Termes IGN] grande échelle
[Termes IGN] identification automatique
[Termes IGN] utilisation du sol
[Vedettes matières IGN] GénéralisationNuméro de notice : C2010-021 Affiliation des auteurs : COGIT+Ext (1988-2011) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83788 Documents numériques
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Automatic identification of high streetsAdobe Acrobat PDF Artificial immune-based supervised classifier for land-cover classification / M. Pal in International Journal of Remote Sensing IJRS, vol 29 n° 7 (April 2008)
[article]
Titre : Artificial immune-based supervised classifier for land-cover classification Type de document : Article/Communication Auteurs : M. Pal, Auteur Année de publication : 2008 Article en page(s) : pp 2273 - 2291 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification dirigée
[Termes IGN] classification par arbre de décision
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] identification automatique
[Termes IGN] image Landsat-ETM+
[Termes IGN] occupation du sol
[Termes IGN] précision de la classification
[Termes IGN] système immunitaire artificielRésumé : (Auteur) This paper explores the potential of an artificial immune-based supervised classification algorithm for land-cover classification. This classifier is inspired by the human immune system and possesses properties similar to nonlinear classification, self/non-self identification, and negative selection. Landsat ETM+ data of an area lying in Eastern England near the town of Littleport are used to study the performance of the artificial immune-based classifier. A univariate decision tree and maximum likelihood classifier were used to compare its performance in terms of classification accuracy and computational cost. Results suggest that the artificial immune-based classifier works well in comparison with the maximum likelihood and the decision-tree classifiers in terms of classification accuracy. The computational cost using artificial immune based classifier is more than the decision tree but less than the maximum likelihood classifier. Another data set from an area in Spain is also used to compare the performance of immune based supervised classifier with maximum likelihood and decision-tree classification algorithms. Results suggest an improved performance with the immune-based classifier in terms of classification accuracy with this data set, too. The design of an artificial immune-based supervised classifier requires several user-defined parameters to be set, so this work is extended to study the effect of varying the values of six parameters on classification accuracy. Finally, a comparison with a backpropagation neural network suggests that the neural network classifier provides higher classification accuracies with both data sets, but the results are not statistically significant. Copyright Taylor & Francis Numéro de notice : A2008-100 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701408402 En ligne : https://doi.org/10.1080/01431160701408402 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29095
in International Journal of Remote Sensing IJRS > vol 29 n° 7 (April 2008) . - pp 2273 - 2291[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-08051 RAB Revue Centre de documentation En réserve L003 Disponible Species identification of individual trees by combining high resolution LiDAR data with multi-spectral images / Johan Holmgren in International Journal of Remote Sensing IJRS, vol 29 n° 5 (March 2008)
[article]
Titre : Species identification of individual trees by combining high resolution LiDAR data with multi-spectral images Type de document : Article/Communication Auteurs : Johan Holmgren, Auteur ; A. Persson, Auteur ; U. Sodermans, Auteur Année de publication : 2008 Article en page(s) : pp 1537 - 1552 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse discriminante
[Termes IGN] données lidar
[Termes IGN] flore locale
[Termes IGN] houppier
[Termes IGN] identification automatique
[Termes IGN] image multibande
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Suède
[Termes IGN] sylviculture
[Termes IGN] traitement du signalRésumé : (Auteur) The objectives of this study were to identify useful predictive factors for tree species identification of individual trees and to compare classifications based on a combination of LiDAR data and multi-spectral images with classification by the use of each individual data source. Crown segments derived from LiDAR data were mapped to multi-spectral images for extraction of spectral data within individual tree crowns. Several features, related to height distribution of laser returns in the canopy, canopy shape, proportion of different types of laser returns, and intensity of laser returns, were derived from LiDAR data. Data from a test site in southern Sweden were used (lat. 58°30' N, long. 13°40' E). The forest consisted of Norway spruce (Picea abies), Scots pine (Pinus sylvestris), and deciduous trees. Classification into these three tree species groups was validated for 1711 trees that had been detected in LiDAR data within 14 field plots (sizes of 20x50 m or 80x80 m). The LiDAR data were acquired by the TopEye MkII system (50 LiDAR measurements per m) and the multi-spectral images were taken by the Zeiss/Intergraph Digital Mapping Camera. The overall classification accuracy was 96% when both data sources were combined. Copyright Taylor & Francis Numéro de notice : A2008-083 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701736471 En ligne : https://doi.org/10.1080/01431160701736471 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29078
in International Journal of Remote Sensing IJRS > vol 29 n° 5 (March 2008) . - pp 1537 - 1552[article]Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 080-08031 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Spectral reflectance and emissivity features of broad leaf plants: prospects for remote sensing in the thermal infrared (8.0-14.0 um) / B. Ribeiro Da Luz in Remote sensing of environment, vol 109 n° 4 (30 August 2007)
[article]
Titre : Spectral reflectance and emissivity features of broad leaf plants: prospects for remote sensing in the thermal infrared (8.0-14.0 um) Type de document : Article/Communication Auteurs : B. Ribeiro Da Luz, Auteur ; J.K. Crowley, Auteur Année de publication : 2007 Article en page(s) : pp 393 - 405 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] emissivité
[Termes IGN] exitance spectrale
[Termes IGN] feuille (végétation)
[Termes IGN] identification automatique
[Termes IGN] image thermique
[Termes IGN] rapport signal sur bruit
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] réflectance spectrale
[Termes IGN] végétationRésumé : (Auteur) Field emissivity measurements were made of leaves collected from nine deciduous tree and agricultural plant species. The data show, for the first time, that it is possible to discriminate subtle spectral emissivity features of leaves from the natural background emission. Under conditions of controlled measurement geometry (leaves arranged to cover a flat surface), the field emissivity spectra agreed fairly well with emissivity values calculated from laboratory directional hemispherical reflectance measurements. Spectral features associated with a variety of leaf chemical constituents, including cellulose, cutin, xylan, silica, and oleanolic acid could be identified in the field emissivity data. Structural aspects of leaf surfaces also influenced spectral behavior, notably the abundance of trichomes, as well as wax thickness and texture. Field spectral measurements made at increasing distances from natural plant canopies showed progressive attenuation of the spectral emissivity features. This attenuation is ascribed to increased multiple scattering that superimposes an opposite-in-sign reflected component on the emittance, and to the increasing number of canopy voids within the instrument field of view. Errors associated with the removal of atmospheric features and with the non-isotropic thermal characteristics of canopies also contribute to the loss of spectral information at greater measurement distances. In contrast to visible and short-wave infrared data, thermal infrared spectra of broad leaf plants show considerable spectral diversity, suggesting that such data eventually could be utilized to map vegetation composition. However, remotely measuring the subtle emissivity features of leaves still presents major challenges. To be successful, sensors operating in the 8–14 um atmospheric window must have high signal-to-noise and a small enough instantaneous field of view to allow measurements of only a few leaf surfaces. Methods for atmospheric compensation, temperature–emissivity separation, and spectral feature analysis also will need to be refined to allow the recognition, and perhaps, exploitation of leaf thermal infrared spectral properties. Copyright Elsevier Numéro de notice : A2007-318 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2007.01.008 En ligne : https://doi.org/10.1016/j.rse.2007.01.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28681
in Remote sensing of environment > vol 109 n° 4 (30 August 2007) . - pp 393 - 405[article]Fast cluster polygonization and its applications in data-rich environments / I. Lee in Geoinformatica, vol 10 n° 4 (December 2006)PermalinkEvaluation of hyperspectral data for geological mapping / Muneendra Kumar in Geoinformatics, vol 9 n° 6 (01/09/2006)PermalinkThe STRM data "finishing" process and products / J.A. Slater in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 3 (March 2006)PermalinkExtraction of tidal channel networks from aerial photographs alone and combined with laser altimetry / Bharat Lohani in International Journal of Remote Sensing IJRS, vol 27 n°1-2 (January 2006)PermalinkAssesment of manual and automated methods for updating stand-level forest inventories based on aerial photography / Perttu Antilla (2005)PermalinkIdentification des zones d'habitat individuel à l'aide de données topographiques / O. Raimond (2005)PermalinkTélédétection urbaine et résolution spatiale optimale : Intérêt pour les utilisateurs et aide pour les classifications / Anne Puissant in Revue internationale de géomatique, vol 14 n° 3 - 4 (septembre 2004 – février 2005)PermalinkLandsat urban mapping based on a combined spectral-spatial methodology / B. Guindon in Remote sensing of environment, vol 92 n° 2 (15/08/2004)PermalinkEstimation of subpixel target size for remotely sensed imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 42 n° 6 (June 2004)PermalinkComparing geospatial entity classes: an asymmetric and context-dependent similarity measure / M. Andrea Rodríguez in International journal of geographical information science IJGIS, vol 18 n° 3 (april - may 2004)Permalink