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Support vector machine for spatial variation / C. Andris in Transactions in GIS, vol 17 n° 1 (February 2013)
[article]
Titre : Support vector machine for spatial variation Type de document : Article/Communication Auteurs : C. Andris, Auteur ; D. Cowen, Auteur ; J. Wittenbach, Auteur Année de publication : 2013 Article en page(s) : pp 40 - 61 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse discriminante
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] exploration de données géographiques
[Termes IGN] seuillageRésumé : (Auteur) Large, multivariate geographic datasets have been used to characterize geographic space with the help of spatial data mining tools. In our study, we explore the sufficiency of the Support Vector Machine (SVM), a popular machine-learning technique for unsupervised classification and clustering, to help recognize hidden patterns in a college admissions dataset. Our college admissions dataset holds over 10,000 students applying to an undisclosed university during one undisclosed year. Students are qualified almost exclusively by their standardized test scores and school records, and a known admissions decision is rendered based on these criteria. Given that the university has a number of political, social and geographic econometric factors in its admissions decisions, we use SVM to find implicit spatial patterns that may favor students from certain geographic regions. We first explore the characteristics of the applicants in the college admissions case study. Next, we explain the SVM technique and our unique ‘threshold line’ methodology for both discrete (regional) and continuous (k-neighbors) space. We then analyze the results of the regional and k-neighbor tests in order to respond to the methodological and geographic research questions. Numéro de notice : A2013-039 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01354.x Date de publication en ligne : 09/10/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01354.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32177
in Transactions in GIS > vol 17 n° 1 (February 2013) . - pp 40 - 61[article]
Titre : Classification of water surfaces using airborne topographic lidar data Type de document : Article/Communication Auteurs : Julien Smeeckaert, Auteur ; Clément Mallet , Auteur ; Nicolas David , Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2013 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 40-1/W1 Conférence : ISPRS 2013, Hannover Workshop 21/05/2013 24/05/2013 Hanovre Allemagne OA ISPRS Archives Importance : pp 321 - 326 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] chaîne de traitement
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] cours d'eau
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] eau de surface
[Termes IGN] interpolation
[Termes IGN] littoral
[Termes IGN] modèle numérique de terrain
[Termes IGN] rivage
[Termes IGN] segmentation en régions
[Termes IGN] semis de pointsRésumé : (auteur) Accurate Digital Terrain Models (DTM) are inevitable inputs for mapping areas subject to natural hazards. Topographic airborne laser scanning has become an established technique to characterize the Earth surface: lidar provides 3D point clouds allowing a fine reconstruction of the topography. For flood hazard modeling, the key step before terrain modeling is the discrimination of land and water surfaces within the delivered point clouds. Therefore, instantaneous shoreline, river borders, inland waters can be extracted as a basis for more reliable DTM generation. This paper presents an automatic, efficient, and versatile workflow for land/water classification of airborne topographic lidar data. For that purpose, a classification framework based on Support Vector Machines (SVM) is designed. First, a restricted set of features, based only 3D lidar point coordinates and flightline information, is defined. Then, the SVM learning step is performed on small but well-targeted areas thanks to an automatic region growing strategy. Finally, label probabilities given by the SVM are merged during a probabilistic relaxation step in order to remove pixel-wise misclassification. Results show that survey of millions of points are labelled with high accuracy (>95% in most cases for coastal areas, and >89% for rivers) and that small natural and anthropic features of interest are still well classified though we work at low point densities (0.5-4 pts/m2). Our approach is valid for coasts and rivers, and provides a strong basis for further discrimination of land-cover classes and coastal habitats. Numéro de notice : C2013-055 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprsarchives-XL-1-W1-321-2013 Date de publication en ligne : 02/05/2013 En ligne : https://doi.org/10.5194/isprsarchives-XL-1-W1-321-2013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92183 Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey / L. Wang in Geoinformatica, vol 17 n° 1 (January 2013)
[article]
Titre : Computer-based synthetic data to assess the tree delineation algorithm from airborne LiDAR survey Type de document : Article/Communication Auteurs : L. Wang, Auteur ; A. Birt, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 35 - 61 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle géométrique
[Termes IGN] Pinophyta
[Termes IGN] Pinus taeda
[Termes IGN] segmentationRésumé : (Auteur) Small Footprint LiDAR (Light Detection And Ranging) has been proposed as an effective tool for measuring detailed biophysical characteristics of forests over broad spatial scales. However, by itself LiDAR yields only a sample of the true 3D structure of a forest. In order to extract useful forestry relevant information, this data must be interpreted using mathematical models and computer algorithms that infer or estimate specific forest metrics. For these outputs to be useful, algorithms must be validated and/or calibrated using a sub-sample of ‘known’ metrics measured using more detailed, reliable methods such as field sampling. In this paper, we describe a novel method for delineating and deriving metrics of individual trees from LiDAR data based on watershed segmentation. Because of the costs involved with collecting both LiDAR data and field samples for validation, we use synthetic LiDAR data to validate and assess the accuracy of our algorithm. This synthetic LiDAR data is generated using a simple geometric model of Loblolly pine (Pinus taeda) trees and a simulation of LiDAR sampling. Our results suggest that point densities greater than 2 and preferably greater than 4 points per m2 are necessary to obtain accurate forest inventory data from Loblolly pine stands. However the results also demonstrate that the detection errors (i.e. the accuracy and biases of the algorithm) are intrinsically related to the structural characteristics of the forest being measured. We argue that experiments with synthetic data are directly useful to forest managers to guide the design of operational forest inventory studies. In addition, we argue that the development of LiDAR simulation models and experiments with the data they generate represents a fundamental and useful approach to designing, improving and exploring the accuracy and efficiency of LiDAR algorithms. Numéro de notice : A2013-046 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s10707-011-0148-1 Date de publication en ligne : 29/11/2011 En ligne : https://doi.org/10.1007/s10707-011-0148-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32184
in Geoinformatica > vol 17 n° 1 (January 2013) . - pp 35 - 61[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-2013011 RAB Revue Centre de documentation En réserve L003 Disponible Tree species discrimination in tropical forests using airborne imaging spectroscopy / Jean-Baptiste Féret in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 1 (January 2013)
[article]
Titre : Tree species discrimination in tropical forests using airborne imaging spectroscopy Type de document : Article/Communication Auteurs : Jean-Baptiste Féret, Auteur ; Gregory P. Asner, Auteur Année de publication : 2013 Article en page(s) : pp 73 - 84 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse discriminante
[Termes IGN] arbre (flore)
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] distance de Bhattacharyya
[Termes IGN] espèce végétale
[Termes IGN] forêt tropicale
[Termes IGN] Hawaii (Etats-Unis)
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] segmentation
[Termes IGN] spectroscopieRésumé : (Auteur) We identify canopy species in a Hawaiian tropical forest using supervised classification applied to airborne hyperspectral imagery acquired with the Carnegie Airborne Observatory-Alpha system. Nonparametric methods (linear and radial basis function support vector machine, artificial neural network, and k-nearest neighbor) and parametric methods (linear, quadratic, and regularized discriminant analysis) are compared for a range of species richness values and training sample sizes. We find a clear advantage in using regularized discriminant analysis, linear discriminant analysis, and support vector machines. No unique optimal classifier was found for all conditions tested, but we highlight the possibility of improving support vector machine classification with a better optimization of its free parameters. We also confirm that a combination of spectral and spatial information increases accuracy of species classification: we combine segmentation and species classification from regularized discriminant analysis to produce a map of the 17 discriminated species. Finally, we compare different methods to assess spectral separability and find a better ability of Bhattacharyya distance to assess separability within and among species. The results indicate that species mapping is tractable in tropical forests when using high-fidelity imaging spectroscopy. Numéro de notice : A2013-010 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2199323 Date de publication en ligne : 16/07/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2199323 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32148
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 1 Tome 1 (January 2013) . - pp 73 - 84[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013011A RAB Revue Centre de documentation En réserve L003 Disponible Image matching of satellite data based on quadrilateral control networks / A. Sedaghat in Photogrammetric record, vol 27 n° 140 (December 2012 - February 2013)
[article]
Titre : Image matching of satellite data based on quadrilateral control networks Type de document : Article/Communication Auteurs : A. Sedaghat, Auteur ; H. Ebadi, Auteur ; M. Mokhtazarde, Auteur Année de publication : 2012 Article en page(s) : pp 423 - 442 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] coin réflecteur
[Termes IGN] détection de coins Harris
[Termes IGN] point d'appui
[Termes IGN] réseau de contrôle
[Termes IGN] SIFT (algorithme)Résumé : (Auteur) Automatic image matching of satellite data is a difficult process due to the complex characteristics of such image pairs, including significant translation, rotation, scaling and illumination differences. A new method is proposed where, initially, a pre-registration is performed to coarsely align the input and reference images. Next, a dense set of corner points are extracted using the Harris operator. The strongest conjugate corner points are determined and the accuracy is improved by using least squares matching to construct a precise braced quadrilateral control network in the two images. Once the consistency of the established network pairs has been determined, it is used as a framework to match the remaining corner points. Comprehensive evaluations of the proposed method on a variety of image pairs from different sensors prove its efficiency with sub-pixel positional accuracy. Numéro de notice : A2012-625 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/j.1477-9730.2012.00699.x Date de publication en ligne : 11/10/2012 En ligne : https://doi.org/10.1111/j.1477-9730.2012.00699.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32071
in Photogrammetric record > vol 27 n° 140 (December 2012 - February 2013) . - pp 423 - 442[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 106-2012041 RAB Revue Centre de documentation En réserve L003 Disponible 3-D mapping of a multi-layered Mediterranean forest using ALS data / António Ferraz in Remote sensing of environment, vol 121 (June 2012)PermalinkQuality assessment of geometric façade models reconstructed from TLS data / Tania Landes in Photogrammetric record, vol 27 n° 138 (June - August 2012)PermalinkAutomatic extraction of road markings from mobile Lidar point clouds / B. Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 4 (April 2012)PermalinkFuzzy analysis for modeling regional delineation and development: The case of the Sardinian mining geopark / G. Manca in Transactions in GIS, vol 16 n° 1 (February 2012)PermalinkAutomatic cloud detection from multi-temporal satellite images: towards the use of Pléiades time series / Nicolas Champion (2012)PermalinkCARTOLIS : Vers un outil géomatique pour identifier et caractériser les segments de lisières forestières / Audrey Alignier in Revue internationale de géomatique, vol 21 n° 4 (décembre 2011 – février 2012)PermalinkObject-based image analysis of high-resolution satellite images using modified cloud basis function neural network and probabilistic relaxation labeling process / A. Rizvi in IEEE Transactions on geoscience and remote sensing, vol 49 n° 12 Tome 1 (December 2011)PermalinkLes principes fondamentaux de la lasergrammétrie terrestre : Acquisition, traitement des données et applications (partie 2/2) / Tania Landes in XYZ, n° 129 (décembre - février 2011)PermalinkIncremental segmentation of lidar point clouds with an octree-structured voxel space / M. Wang in Photogrammetric record, vol 26 n° 133 (March - May 2011)PermalinkHow to enhance cartographic visualisations of natural hazards assessment results / M. Kunz in Cartographic journal (the), vol 48 n° 1 (February 2011)PermalinkDonnées géographiques / Pierre Dumolard (2011)PermalinkPermalinkRecalage d'un nuage de points de scanner laser terrestre avec une image de bâtiment / Abdelhamid Bennis (2011)PermalinkA semantic and language-based representation of an environmental scene / J.M. Le Yaouanc in Geoinformatica, vol 14 n° 3 (July 2010)PermalinkReconstruction de façades par des primitives géométriques à partir de données laser terrestres / Hakim Boulaassal in Revue Française de Photogrammétrie et de Télédétection, n° 191 (Mai 2010)PermalinkSegmentation et interprétation de nuages de points pour la modélisation d'environnements urbains / J. Hernandez in Revue Française de Photogrammétrie et de Télédétection, n° 191 (Mai 2010)PermalinkAutomatic segmentation of Lidar data into coplanar point clusters using an octree-based split-and-merge algorithm / M. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 4 (April 2010)PermalinkSegmentation and reconstruction of polyhedral building roofs from aerial lidar points clouds / A. Sampath in IEEE Transactions on geoscience and remote sensing, vol 48 n° 3 Tome 2 (March 2010)Permalink3D segmentation of forest structure using an adaptive mean shift based procedure / António Ferraz (2010)PermalinkPermalinkConception et développement d'un outil de modification de la segmentation routière / K. Guillotte in Geomatica, vol 63 n° 4 (December 2009)PermalinkPositioning localities based on spatial assertions / Y. 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Visvalingam in Cartography and geographic information systems, vol 22 n° 4 (December 1995)PermalinkThe importance of geometric modeling in linear feature generalization / Corinne Plazanet in Cartography and geographic information systems, vol 22 n° 4 (December 1995)PermalinkPermalinkMeasurement, characterization and classification for automated line feature generalization / Corinne Plazanet (1995)PermalinkSegmentation d'images : coopération, fusion, évaluation / Riad Kara-Falah (1995)PermalinkSegmentation de photographies aériennes numérisées : délimitation globale de la végétation et extraction d’informations structurelles / Rémi Jayer (1995)PermalinkPermalinkUne architecture d'aide à la construction de croquis d'interprétation géographique / Mauro Gaio (1994)PermalinkDescription et paramétrisation de contours : application à l'image satellitaire pour une reconnaissance des structures géologiques / Hind Taud (1993)PermalinkMécanismes de segmentation d'images : de la modélisation à la création d'algorithmes / Christophe Thomas (1992)PermalinkCIME, une application des systèmes experts à la télédétection / Catherine Mering (30/05/1988)PermalinkContribution à la modélisation et à la résolution du problème de la vision passive tridimensionnelle par ordinateur / Philippe Marthon (1987)PermalinkRecherche automatique des réseaux linéaires sur les images SPOT / D. 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