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Extracting urban road networks from high-resolution true orthoimage and Lidar / J. Youn in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 2 (February 2008)
[article]
Titre : Extracting urban road networks from high-resolution true orthoimage and Lidar Type de document : Article/Communication Auteurs : J. Youn, Auteur ; J. Bethel, Auteur ; et al., Auteur Année de publication : 2008 Article en page(s) : pp 227 - 237 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] classification dirigée
[Termes IGN] données lidar
[Termes IGN] extraction automatique
[Termes IGN] lasergrammétrie
[Termes IGN] orthoimage intégrale
[Termes IGN] réseau routier
[Termes IGN] segmentation en régions
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (Auteur) Automated or semi-automated feature extraction from remotely collected, large scale image data has been a challenging issue in digital photogrammetry for many years. In the feature extraction field, fusing different types of data to provide complementary information about the objects is becoming increasingly important. In this paper, we present a newly developed approach for the automatic extraction of urban area road networks from a true orthoimage and lidar assuming the road network to be a semi-grid pattern. The proposed approach starts from the subdivision of a study area into small regions based on homogeneity of the dominant road directions from the true orthoimage. Each region’s road candidates are selected with a proposed free passage measure. This process is called the “acupuncture” method. Features around the road candidates are used as key factors for an advanced “acupuncture method” called the region-based acupuncture method. Extracted road candidates are edited to avoid collocation with non-road features such as buildings and grass fields. In order to produce a building map for the prior step, a first-last return analysis and morphological filter are used with the lidar point cloud. A grass area thematic map is generated by supervised classification techniques from a synthetic image, which contains the three color bands from the true orthoimage and the lidar intensity value. Those non-road feature maps are used as a blocking mask for the roads. The accuracy of the result is evaluated quantitatively with respect to manually compiled road vectors, and a completeness of 80 percent and a correctness of 79 percent are obtained with the proposed algorithm on an area of 1,081,600 square meters. Copyright ASPRS Numéro de notice : A2008-047 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.2.227 En ligne : https://doi.org/10.14358/PERS.74.2.227 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29042
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 2 (February 2008) . - pp 227 - 237[article]Multisource classification using Support Vector Machines: an empirical comparison with Decision Tree and Neural Network classifiers / P. Watanachaturaporn in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 2 (February 2008)
[article]
Titre : Multisource classification using Support Vector Machines: an empirical comparison with Decision Tree and Neural Network classifiers Type de document : Article/Communication Auteurs : P. Watanachaturaporn, Auteur ; M. Arora, Auteur ; K. Varshney, Auteur Année de publication : 2008 Article en page(s) : pp 239 - 246 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] classification par arbre de décision
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données multisources
[Termes IGN] extraction automatique
[Termes IGN] Himalaya
[Termes IGN] image IRS-LISS
[Termes IGN] Kappa de Cohen
[Termes IGN] modèle numérique de surface
[Termes IGN] occupation du solRésumé : (Auteur) Remote sensing image classification has proven to be attractive for extracting useful thematic information such as landcover. However, often for a given application, spectral information acquired by a remote sensing sensor may not be sufficient to derive accurate information. Incorporation of data from other sources such as a digital elevation model (DEM), and geophysical and geological data may assist in achieving more accurate land-cover classification from remote sensing images. Recently, support vector machines (SVM) have been proposed as an alternative for classification of remote sensing data, and the results are promising. In this paper, we employ the SVM algorithm to perform multisource classification. An IRS–1C LISS III image along with normalized differenced vegetation index (NDVI) image and DEM are used to produce a land-cover classification for a region in the Himalayas. The accuracy of SVM-based multisource classification is compared with several other nonparametric algorithms namely a decision tree classifier, and back propagation and radial basis function neural network classifiers. The well-known kappa coefficient of agreement is used to assess classification accuracy. The differences in the kappa coefficient of classifiers have been statistically evaluated using a pairwise Z-test. The results show a significant increase in the accuracy of the SVM based classifier on incorporation of ancillary data over classification performed solely on the basis of spectral data from remote sensing sensors. Copyright ASPRS Numéro de notice : A2008-048 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.2.239 En ligne : https://doi.org/10.14358/PERS.74.2.239 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29043
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 2 (February 2008) . - pp 239 - 246[article]Multispectral land use classification using neural networks and support vector machines: one or the other, or both? / B. Dixon in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)
[article]
Titre : Multispectral land use classification using neural networks and support vector machines: one or the other, or both? Type de document : Article/Communication Auteurs : B. Dixon, Auteur ; N. Candade, Auteur Année de publication : 2008 Article en page(s) : pp 1185 - 1206 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] occupation du solRésumé : (Auteur) Land use classification is an important part of many remote sensing applications. A lot of research has gone into the application of statistical and neural network classifiers to remote-sensing images. This research involves the study and implementation of a new pattern recognition technique introduced within the framework of statistical learning theory called Support Vector Machines (SVMs), and its application to remote-sensing image classification. Standard classifiers such as Artificial Neural Network (ANN) need a number of training samples that exponentially increase with the dimension of the input feature space. With a limited number of training samples, the classification rate thus decreases as the dimensionality increases. SVMs are independent of the dimensionality of feature space as the main idea behind this classification technique is to separate the classes with a surface that maximizes the margin between them, using boundary pixels to create the decision surface. Results from SVMs are compared with traditional Maximum Likelihood Classification (MLC) and an ANN classifier. The findings suggest that the ANN and SVM classifiers perform better than the traditional MLC. The SVM and the ANN show comparable results. However, accuracy is dependent on factors such as the number of hidden nodes (in the case of ANN) and kernel parameters (in the case of SVM). The training time taken by the SVM is several magnitudes less. Copyright Taylor & Francis Numéro de notice : A2008-009 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701294661 En ligne : https://doi.org/10.1080/01431160701294661 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29004
in International Journal of Remote Sensing IJRS > vol 29 n°3-4 (February 2008) . - pp 1185 - 1206[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-08021 RAB Revue Centre de documentation En réserve L003 Disponible The application of artificial neural networks to the analysis of remotely sensed data / J.F. Mas in International Journal of Remote Sensing IJRS, vol 29 n°3-4 (February 2008)
[article]
Titre : The application of artificial neural networks to the analysis of remotely sensed data Type de document : Article/Communication Auteurs : J.F. Mas, Auteur ; J.J. Flores, Auteur Année de publication : 2008 Article en page(s) : pp 617 - 663 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage automatique
[Termes IGN] classification par réseau neuronal
[Termes IGN] image aérienne
[Termes IGN] image satellite
[Termes IGN] réseau neuronal artificielRésumé : (Auteur) Artificial neural networks (ANNs) have become a popular tool in the analysis of remotely sensed data. Although significant progress has been made in image classification based upon neural networks, a number of issues remain to be resolved. This paper reviews remotely sensed data analysis with neural networks. First, we present an overview of the main concepts underlying ANNs, including the main architectures and learning algorithms. Then, the main tasks that involve ANNs in remote sensing are described. The limitations and crucial issues relating to the application of the neural network approach are discussed. A brief review of the implementation of ANNs in some of the most popular image processing software packages is presented. Finally, we discuss the application perspectives of neural networks in remote sensing image analysis. Copyright Taylor & Francis Numéro de notice : A2008-004 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160701352154 En ligne : https://doi.org/10.1080/01431160701352154 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28999
in International Journal of Remote Sensing IJRS > vol 29 n°3-4 (February 2008) . - pp 617 - 663[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-08021 RAB Revue Centre de documentation En réserve L003 Disponible La géomatique au service de la caractérisation automatique des réseaux hydrographiques / Adrien Paget in Physio-Géo, vol 2 (janvier 2008)
[article]
Titre : La géomatique au service de la caractérisation automatique des réseaux hydrographiques Type de document : Article/Communication Auteurs : Adrien Paget , Auteur ; Julien Perret , Auteur ; Jean-François Gleyze , Auteur Année de publication : 2008 Article en page(s) : pp 147 - 160 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] caractérisation
[Termes IGN] géomorphométrie
[Termes IGN] graphe
[Termes IGN] relation topologique
[Termes IGN] réseau hydrographique
[Termes IGN] segmentationRésumé : (auteur) L'analyse des phénomènes territoriaux est facilitée aujourd'hui par les Systèmes d'Information Géographique, lesquels permettent d'intégrer au sein d'une même plateforme les données géographiques et les données thématiques associées aux phénomènes d'intérêt. En pratique, les outils et les méthodes offerts par les SIG proposent d'analyser les phénomènes de manière intégrée, sans distinguer explicitement les facteurs explicatifs propres à la spatialisation des phénomènes et les facteurs explicatifs contextuels. Pour autant, les données géographiques ne se limitent pas à un simple support cartographique pour représenter les phénomènes territoriaux, mais contiennent en puissance des informations susceptibles de faire comprendre les mécanismes spatiaux qui sous-tendent ces phénomènes. En particulier, les données géographiques représentatives des réseaux hydrographiques décrivent la forme et la topologie de ces réseaux, et peuvent à ce titre fournir des informations complémentaires sur leurs types morphométriques. Sur la base de la typologie établie en géomorphométrie et des caractérisations géométriques fournies par la littérature, cet article montre qu'il est possible d'extraire l'information sémantique relative aux différents types de réseaux en automatisant leur reconnaissance, grâce à des indicateurs structurels quantitatifs construits sur leur représentation topographique. Cette démarche est mise en œuvre sur les réseaux de type parallèle, à partir de l'observation des angles formés par les tronçons hydrographiques au niveau des nœuds de confluence des réseaux. En considérant les directions moyennes empruntées par les tronçons autour de ces nœuds et en étudiant les distributions des angles qu'ils forment sur l'ensemble de la zone d'étude, il est alors possible d'élaborer une méthode de segmentation des réseaux hydrographiques, permettant de faire la part entre les réseaux de type parallèle et ceux relevant de types différents. Numéro de notice : A2008-588 Affiliation des auteurs : IGN (1940-2011) Thématique : GEOMATIQUE Nature : Article DOI : 10.4000/physio-geo.1031 Date de publication en ligne : 20/12/2008 En ligne : https://physio-geo.revues.org/1031 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82003
in Physio-Géo > vol 2 (janvier 2008) . - pp 147 - 160[article]Advances in photogrammetry, remote sensing and spatial information sciences / Z. Li (2008)PermalinkAnalyse et traitement d'ondes Lidar pour la cartographie et la reconnaissance de formes : application au milieu urbain / Clément Mallet (2008)PermalinkPermalinkApplied spatial data analysis with R / R.S. Bivand (2008)PermalinkCartographie thématique, 3. Méthodes quantitatives et transformations attributaires / Colette Cauvin (2008)PermalinkCartographie thématique, 4. Des transformations renouvelées / Colette Cauvin (2008)PermalinkCartographies multi-échelles et multi-temporelles sur l'ile de la grande Comore / Simon Gabolde (2008)PermalinkCSTST 2008, the 5th International conference on soft computing as transdisciplinary science and technology, October 28th - October 31st 2008, University of Cergy-Pontoise, France / Richard Chbeir (2008)PermalinkDetection, segmentation and characterisation of vegetation in high-resolution aerial images for 3D city modelling / Corina Iovan (2008)PermalinkEtude géomorphologique des coulées de lave du piton de la fournaise / Astrid Gladys (2008)PermalinkEvaluation de la classification WISHART sur des données radar polarimétriques et application au Gabon / G. Roussel (2008)PermalinkExtraction et Gestion des Connaissances, EGC 2008, 8es journées francophones, 29 janvier 2008, Sophia Antipolis, France / Marie-Aude Aufaure Portier (2008)PermalinkGlobal elevation ancillary data for land-use classification using granular neural networks / D. Stathakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 1 (January 2008)PermalinkPermalinkIntroduction au traitement d'images / D. Lingrand (2008)PermalinkPermalinkModélisation et statistique spatiales / Carlo Gaetan (2008)PermalinkA new computationally efficient stochastic approach for building reconstruction from satellite data / Florent Lafarge (2008)PermalinkSIFT (Scale Invariant Feature Transform) : Un outil pour la mise en correspondance d’images / Arnaud Le Bris (2008)PermalinkSupporting the process of exploring and interpreting space-time multivariate patterns: the visual inquiry toolkit / J. Chen in Cartography and Geographic Information Science, vol 35 n° 1 (January 2008)PermalinkLa télédétection au service de la forêt / Françoise de Blomac in SIG la lettre, n° 93 (janvier 2008)PermalinkTerrain modeling from lidar data: Hierarchical K-means filtering and Markovian regularization / Nesrine Chehata (2008)PermalinkUtilisation de la télédétection optique et radar pour étudier la déforestation en Afrique centrale / Quentin Page (2008)PermalinkVisual analysis of network traffic – interactive monitoring, detection, and interpretation of security threats / Florian Mansmann (ca 2008)PermalinkApport de la télédétection à la cartographie des sols affectés par la salinisation : cas de la Nefzaoua, Tunisie / Ouerchefani Dalel in Revue Française de Photogrammétrie et de Télédétection, n° 187 -188 (Décembre 2007)PermalinkBorder vector detection and adaptation for classification of multispectral and hyperspectral remote sensing images / N.G. Kasapoglu in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkFusion of support vector machines for classification of multisensor data / Björn Waske in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkLand-cover classification in the Brazilian Amazon with the integration of Landsat ETM+ and Radarsat data / Dong Lu in International Journal of Remote Sensing IJRS, vol 28 n°23-24 (December 2007)PermalinkN-FindR method versus independent component analysis for lithological identification in hyperspectral imagery / C. Gomez in International Journal of Remote Sensing IJRS, vol 28 n°23-24 (December 2007)PermalinkUn processus de sélection du réseau hydrographique, base sur la détection de structures / Guillaume Touya in Le monde des cartes, n° 194 (décembre 2007)PermalinkA supervised artificial immune classifier for remote-sensing imagery / Y. Zhong in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)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)PermalinkOrthogonal polynomials supported by regional growing segmentation for the extraction of terrain from lidar data / N.A. Akel in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 11 (November 2007)PermalinkPolarimetric and interferometric SAR image partition into statistically homogeneous regions based on the minimization of the stochastic complexity / J. Morio in IEEE Transactions on geoscience and remote sensing, vol 45 n° 11 Tome 2 (November 2007)PermalinkSea-ice deformation state from synthetic aperture radar imagery: Part 1 comparison of C- and L-band and different polarization / W. Dierking in IEEE Transactions on geoscience and remote sensing, vol 45 n° 11 Tome 2 (November 2007)PermalinkVariability of fire-induced changes in MODIS surface reflectance by land-cover type in Borneo / Jukka Miettinen in International Journal of Remote Sensing IJRS, vol 28 n° 21-22 (November 2007)PermalinkWeighting function alternatives for a subpixel allocation model / Y. Makido in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 11 (November 2007)PermalinkWildfires and remote sensing / Ioannis Z. Gitas in Geoinformatics, vol 10 n° 7 (01/11/2007)PermalinkAccuracy of forest mapping based on Landsat TM data and a kNN-based method / K. Gjertsen in Remote sensing of environment, vol 110 n° 4 (30/10/2007)PermalinkFeature selection by genetic algorithms in object-based classification of Ikonos imagery for forest mapping in Flanders, Belgium / F.M.B. Van Coillie in Remote sensing of environment, vol 110 n° 4 (30/10/2007)Permalinkvol 110 n° 4 - 30/10/2007 - Forestsat 2007 (Bulletin de Remote sensing of environment) / Ronald E. McRobertsPermalinkThe impact of relative radiometric calibration on the accuracy of kNN-predictions of forest attributes / T. Koukal in Remote sensing of environment, vol 110 n° 4 (30/10/2007)PermalinkClassification of floodplain vegetation by data fusion of spectral (CASI) and LiDAR data / G.W. Geerling in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkClassified road detection from satellite images based on perceptual organization / J. Yang in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkMultispectral image classification: a supervised neural computation approach based on rough-fuzzy membership function and weak fuzzy similarity relation / A. Agrawal in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkOptimization in multi-scale segmentation of high-resolution satellite images for artificial feature recognition / Jing Tian in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkRegenerating boreal forest structure estimation using SPOT-5 pan-sharpened imagery / A.L. Wunderle in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)PermalinkA rough set approach to the discovery of classification rules in spatial data / Yee Leung in International journal of geographical information science IJGIS, vol 21 n° 9-10 (october 2007)PermalinkCharacterizing patterns of plant distribution in a southern California salt marsh using remotely sensed topographic and hyperspectral data and local tidal fluctuations / S. Sadro in Remote sensing of environment, vol 110 n° 2 (28/09/2007)PermalinkCarte de consensualité / A. Quirin in Revue internationale de géomatique, vol 17 n° 3-4 (septembre 2007 – février 2008)PermalinkCartographie des zones de haute montagne : essais de cartographie numérique des rochers / Loïc Gondol in Le monde des cartes, n° 193 (septembre - novembre 2007)PermalinkDetection and discrimination between oil spills and look-alike phenomena through neural networks / Konstantinos Topouzelis in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 4 (September 2007)PermalinkEstimation of vegetation parameter for modelling soil erosion using linear spectral mixture analysis of Landsat ETM data / A.M. DE Asis in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 4 (September 2007)PermalinkA geographic visualization approach to multi-criteria evaluation of urban quality of life / Claus Rinner in International journal of geographical information science IJGIS, vol 21 n° 8 (september 2007)PermalinkHigher order vagueness in geographical information: empirical geographical population of type N fuzzy sets / P. Fischer in Geoinformatica, vol 11 n° 3 (September - November 2007)PermalinkLa morphologie mathématique binaire pour l'extraction automatique des bâtiments dans les images THRS / David Sheeren in Revue internationale de géomatique, vol 17 n° 3-4 (septembre 2007 – février 2008)PermalinkA new model for cloud tracking and analysis on satellite images / E. Guilbert in Geoinformatica, vol 11 n° 3 (September - November 2007)PermalinkMultitemporel fuzzy classification model based on class transition possibilities / G.L.A. Mota in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)PermalinkRule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping / Robert Lucas in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)PermalinkBuilding boundary tracing and regularization from airborne lidar point clouds / A. Sampath in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 7 (July 2007)PermalinkDétection des haies et segmentation automatique / A. Dommanget in Géomatique expert, n° 57 (01/07/2007)PermalinkSpatial aspects of MRSA epidemiology: a case study using stochastic simulation, kernel estimation and SaTScan / Lucy Bastin in International journal of geographical information science IJGIS, vol 21 n° 6-7 (july 2007)PermalinkAlgorithms for nearest neighbor search on moving object trajectories / E. Frentzos in Geoinformatica, vol 11 n° 2 (June - August 2007)PermalinkBuilding detection by fusion of airborne laser scanner data and multi-spectral images: performance evaluation and sensitivity analysis / Franz Rottensteiner in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 2 (June 2007)PermalinkGeneralization of 3D building data based on a scale-space approach / A. Forberg in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 2 (June 2007)PermalinkMapping of salt-affected soils using TM images / P. Garcia Rodriguez in International Journal of Remote Sensing IJRS, vol 28 n°11-12 (June 2007)PermalinkMonitoring cross-border trails using airborne digital multispectral imagery and interactive image analysis techniques / L. Cao in Geocarto international, vol 22 n° 2 (June - August 2007)PermalinkTraitement de données lidar aéroporté : vers une solution globale / Frédéric Bretar in Revue Française de Photogrammétrie et de Télédétection, n° 186 (Juin 2007)PermalinkLe WI-FI pour le positionnement et la navigation en intérieur / A. Betremieux in XYZ, n° 111 (juin - août 2007)PermalinkPrédiction des catégories commerciales et des implantations optimales des magasins / P. Jensen in Géomatique expert, n° 56 (01/05/2007)PermalinkComparative assessment of the measures of thematic classification accuracy / C. Liu in Remote sensing of environment, vol 107 n° 4 (30/04/2007)PermalinkModelling and mapping potential hooded warbler (Wilsonia citrina) habitat using remotely sensed imagery / J. Pasher in Remote sensing of environment, vol 107 n° 3 (12 April 2007)PermalinkAtmospheric correction algorithm for MERIS above case-2 waters / Th. Schroeder in International Journal of Remote Sensing IJRS, vol 28 n°7-8 (April 2007)PermalinkImproving land-cover classification using recognition threshold neural networks / M.J. Aitkenhead in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 4 (April 2007)PermalinkMapping land cover from detailed aerial photography data using textural and neural network analysis / R. Cots-Folch in International Journal of Remote Sensing IJRS, vol 28 n°7-8 (April 2007)PermalinkAn operational MISR pixel classifier using support vector machines / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkA data-mining approach to associating MISR smoke plume heights with MODIS fire measurements / D. Mazzoni in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkSupport vector machines for recognition of semi-arid vegetation types using MISR multi-angle imagery / L. Su in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkSupport vector machines regression for retrieval of leaf area index from multiangle imaging spectroradiometer / S. Durbha in Remote sensing of environment, vol 107 n° 1-2 (15 March 2007)PermalinkComparison between several feature extraction/classification methods for mapping complicated agricultural land use patches using airborne hyperspectral data / S. Lu in International Journal of Remote Sensing IJRS, vol 28 n°5-6 (March 2007)PermalinkEvaluating the uncertainty caused by Post Office Box addresses in environmental health studies: A restricted Monte Carlo approach / X. Shi in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)PermalinkExtended Hausdorff distance for spatial objects in GIS / D. Min in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)PermalinkFeature extractions for small sample size classification problem / B.C. Kuo in IEEE Transactions on geoscience and remote sensing, vol 45 n° 3 (March 2007)PermalinkMERIS-FR potential for land use-land cover mapping / S. Garcia-Gigorro in International Journal of Remote Sensing IJRS, vol 28 n°5-6 (March 2007)PermalinkNET-DBSCAN: clustering the nodes of a dynamic linear network / Emmanuel Stefanakis in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)PermalinkOil spill detection in Radarsat and Envisat SAR images / A.H. Solberg in IEEE Transactions on geoscience and remote sensing, vol 45 n° 3 (March 2007)PermalinkRaster-network regionalization for watershed data processing / T.L. Whiteaker in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)PermalinkTerrestrial and submerged aquatic vegetation mapping in Fire Island national seashore using high spatial resolution remote sensing data / Y. Wang in Marine geodesy, vol 30 n° 1-2 (March - June 2007)PermalinkGeneration of geometrically and radiometrically terrain corrected SAR image products / A. Loew in Remote sensing of environment, vol 106 n° 3 (15/02/2007)PermalinkAn experiment using a circular neighborhood to calculate slope gradient from a DEM / X. Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 2 (February 2007)PermalinkAnalysis of process variance in remote sensing applications / M. Matur in GIS development, vol 11 n° 2 (February 2007)PermalinkBuilding facade interpretation from uncalibrated wide-baseline image sequences / Helmut Mayer in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 6 (February 2007)PermalinkExtraction of spectral channels from hyperspectral images for classification purposes / S.B. Serpico in IEEE Transactions on geoscience and remote sensing, vol 45 n° 2 (February 2007)PermalinkFFT-enhanced IHS transform method for fusing high-resolution satellite images / Y. Ling in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 6 (February 2007)PermalinkSpatial PSF nonuniformity effects in airborne pushbroom imaging spectrometry data / Daniel Schläpfer in IEEE Transactions on geoscience and remote sensing, vol 45 n° 2 (February 2007)Permalink