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Classification of urban tree species using hyperspectral imagery / R. Jensen in Geocarto international, vol 27 n° 5 (August 2012)
[article]
Titre : Classification of urban tree species using hyperspectral imagery Type de document : Article/Communication Auteurs : R. Jensen, Auteur ; P. Hardin, Auteur ; A. Hardin, Auteur Année de publication : 2012 Article en page(s) : pp 443 - 458 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] analyse en composantes principales
[Termes IGN] arbre (flore)
[Termes IGN] arbre urbain
[Termes IGN] espèce végétale
[Termes IGN] flore urbaine
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image infrarouge
[Termes IGN] indice de végétation
[Termes IGN] Utah (Etas-Unis)Résumé : (Auteur) Urban areas serve as humanity's principal habitat. Because of this, it is important to understand the biophysical components of the urban environment – including the urban forest. The goal of this study was to determine the potential to classify individual urban trees as a function of spectral features derived from airborne hyperspectral data. To determine this, 500 urban trees were identified (through fieldwork) in the built-up zone of Provo-Orem, Utah, USA. Visible and near infrared airborne hyperspectral imagery was collected over the same area. The 500 trees were identified on the images, and spectral features of each tree were extracted. Principal components, vegetation indices, band means, and band ratios were all used as features to discriminate between different tree species. The tree classification was 82% accurate when just the six principal components were used. Classification accuracy increased to 91.4% after combining vegetation indices, band mean values and band ratios. Numéro de notice : A2012-373 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.687400 Date de publication en ligne : 24/05/2012 En ligne : https://doi.org/10.1080/10106049.2012.687400 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31819
in Geocarto international > vol 27 n° 5 (August 2012) . - pp 443 - 458[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)
[article]
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)
[article]
Titre : IconMap-based visualisation technique and its application in soil fertility analysis Type de document : Article/Communication Auteurs : X. Zhang, Auteur ; X. Wang, Auteur ; J. Li, Auteur ; M. Pazner, Auteur Année de publication : 2012 Article en page(s) : pp 208 - 217 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] analyse multivariée
[Termes IGN] données localisées
[Termes IGN] données maillées
[Termes IGN] fertilité
[Termes IGN] Setchouan (Chine)
[Termes IGN] sol
[Termes IGN] visualisation de donnéesRésumé : (Auteur) With the development of geographic information science and the progress in the research of scientific visualisation, the visualisation of multivariate geospatial data has attracted much attention. This paper discusses an IconMap-based visualisation technique that enables multiple geospatial variables be represented in a single raster layer. This is achieved by extending the conventional pixel-based image structure to the three-tiered iconic design. Thereby the spatial pattern generated by the interaction between multivariate geographic variables can be disclosed, and the goal of geospatial data mining is achieved. A visualisation case study on soil organic matter and nutrients for the Shuangliu County of Chengdu City, China, was performed using the proposed approach. The result shows that the static IconMap can better display the distribution tendency of the high-end and low-end soil organic matter and nutrients, and that the dynamic IconMap can both reflect the interaction between the organic matter and the nutrients variables, and display the soil fertility levels in a comprehensive way. Thus, the IconMap-based visualisation approach is a non-fused, exploratory analytical approach for multivariate data and valuable for visually analyse the soil fertility condition. Numéro de notice : A2012-536 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1179/1743277412Y.0000000016 Date de publication en ligne : 22/11/2013 En ligne : https://doi.org/10.1179/1743277412Y.0000000016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31982
in Cartographic journal (the) > vol 49 n° 3 (August 2012) . - pp 208 - 217[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 030-2012031 RAB Revue Centre de documentation En réserve L003 Disponible Memory-based cluster sampling for remote sensing image classification / Michele Volpi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
[article]
Titre : Memory-based cluster sampling for remote sensing image classification Type de document : Article/Communication Auteurs : Michele Volpi, Auteur ; Devis Tuia, Auteur ; Mikhail Kanevski, Auteur Année de publication : 2012 Article en page(s) : pp 3096 - 3106 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] apprentissage automatique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image à très haute résolution
[Termes IGN] image hyperspectraleRésumé : (Auteur) In this paper, we address the problem of semi-automatic definition of training sets for the classification of remotely sensed images. We propose two approaches based on active learning aiming at removing both the proximal (low diversity) and the dense (low exploration during iterations) sampling redundancies. The first is encountered when several samples carrying similar spectral information are selected by the algorithm, while the second occurs when the heuristic is unable to explore undiscovered parts of the feature space during iterations. For this purpose, kernel k-means is used to cluster a set of uncertain candidates in the same space spanned by the kernel function defined in the SVM classification step. Two heuristics are proposed to maximize the speed of convergence to high classification accuracies: The first is based on binary hierarchical partitioning of the set of selected uncertain samples, while the second extends this approach by considering memory in the selection and thus dynamically adapts to the problem throughout the iterations. Experiments on both VHR and hyperspectral imagery confirm fast convergence of the algorithm, that outperforms state-of-the-art sampling schemes. Numéro de notice : A2012-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2179661 Date de publication en ligne : 21/02/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2179661 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31829
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3096 - 3106[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012081 RAB Revue Centre de documentation En réserve L003 Disponible Satellite image time series analysis under time warping / F. Petitjean in IEEE Transactions on geoscience and remote sensing, vol 50 n° 8 (August 2012)
[article]
Titre : Satellite image time series analysis under time warping Type de document : Article/Communication Auteurs : F. Petitjean, Auteur ; Jordi Inglada, Auteur ; Pierre Gançarski, Auteur Année de publication : 2012 Article en page(s) : pp 3081 - 3095 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] déformation temporelle dynamique (algorithme)
[Termes IGN] échantillon
[Termes IGN] image optique
[Termes IGN] série temporelleRésumé : (Auteur) Satellite Image Time Series are becoming increasingly available and will continue to do so in the coming years thanks to the launch of space missions which aim at providing a coverage of the Earth every few days with high spatial resolution. In the case of optical imagery, it will be possible to produce land use and cover change maps with detailed nomenclatures. However, due to meteorological phenomena, such as clouds, these time series will become irregular in terms of temporal sampling, and one will need to compare time series with different lengths. In this paper, we present an approach to image time series analysis which is able to deal with irregularly sampled series and which also allows the comparison of pairs of time series where each element of the pair has a different number of samples. We present the dynamic time warping from a theoretical point of view and illustrate its capabilities with two applications to real-time series. Numéro de notice : A2012-382 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2179050 Date de publication en ligne : 31/01/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2179050 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31828
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 8 (August 2012) . - pp 3081 - 3095[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012081 RAB Revue Centre de documentation En réserve L003 Disponible Trees 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)PermalinkSeparation of global time-variable gravity signals into maximally independent components / E. Forootan in Journal of geodesy, vol 86 n° 7 (July 2012)PermalinkDiscovering spatial patterns in origin-destination mobility data / D. Guo in Transactions in GIS, vol 16 n° 3 (June 2012)PermalinkEfficient parallel algorithm for pixel classification in remote sensing imagery / U. Maulik in Geoinformatica, vol 16 n° 2 (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)PermalinkPermalinkCartographie du déboisement à partir de données à haute résolution spatiale / Yannick Philippets (2012)PermalinkDétection et identification de zones de végétation arborée: utilisation conjointe d'images satellite RapidEye et de données BDOrtho / François Tassin (2012)PermalinkJoint processing of Landsat and ALOS-PALSAR data for forest mapping and monitoring / E. Lehmann in IEEE Transactions on geoscience and remote sensing, vol 50 n° 1 (January 2012)PermalinkTraitements numériques des images de télédétection, Vol. 3. Traitements appliqués à la photo-interprétation / Olivier de Joinville (2012)Permalink