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A split model for extraction of subpixel impervious surface information / Y. Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 7 (July 2004)
[article]
Titre : A split model for extraction of subpixel impervious surface information Type de document : Article/Communication Auteurs : Y. Wang, Auteur ; X. Zhang, Auteur Année de publication : 2004 Article en page(s) : pp 821 - 828 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] banlieue
[Termes IGN] classification par réseau neuronal
[Termes IGN] données multicapteurs
[Termes IGN] image Landsat-TM
[Termes IGN] milieu urbain
[Termes IGN] réseau neuronal artificiel
[Termes IGN] surface imperméable
[Termes IGN] valeur radiométriqueRésumé : (Auteur) This paper introduces a Subpixel Proportional Land cover Information Transformation (SPLIT) model to extract proportions of impervious surfaces in urban and suburban areas. High spatial resolution airborne Digital Multispectral Videography (Dmsv) data provided subpixel information for Landsat TM data. The SPLIT model employed a Modularized Artificial Neural Network (MANN) to integrate multi-sensor remote sensing data and to extract proportions of impervious surfaces and other types of land cover within TM pixels. Through a control unit, the MANN was able to decompose a complex task into multiple subtasks by using a group of sub-networks. The SPLIT model identified spectral relations between TM pixel values and the corresponding DMSV subpixel patterns. The established relationship allows extrapolation of the SPLIT model to the areas beyond DMSV data coverage. We applied five intervals, i.e., 81 percent, to map the subpixel proportions of land cover types. We extrapolated the SPLIT model from training sites that have both TM and DMSV coverage into the entire DuPage County with TM data as the input. The extrapolation received 82.9 percent overall accuracyfor the extracted proportions of urban impervious surface. Numéro de notice : A2004-274 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.70.7.821 En ligne : https://doi.org/10.14358/PERS.70.7.821 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26801
in Photogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 7 (July 2004) . - pp 821 - 828[article]Wavelet for urban spatial feature discrimination: comparisons with fractal, spatial autocorrelation, and spatial co-occurrence approaches / Nina S.N. Lam in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 7 (July 2004)
[article]
Titre : Wavelet for urban spatial feature discrimination: comparisons with fractal, spatial autocorrelation, and spatial co-occurrence approaches Type de document : Article/Communication Auteurs : Nina S.N. Lam, Auteur ; S.W. Myint, Auteur ; J.M. Tyler, Auteur Année de publication : 2004 Article en page(s) : pp 803 - 812 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse fractale
[Termes IGN] autocorrélation spatiale
[Termes IGN] classification dirigée
[Termes IGN] image multibande
[Termes IGN] matrice
[Termes IGN] milieu urbain
[Termes IGN] précision de la classification
[Termes IGN] transformation en ondelettesRésumé : (Auteur) Traditional image processing techniques have proven inadequate for urban mapping using high spatial resolution remote-sensing images. This study examined and evaluated wavelet transforms for urban texture analysis and image classification using high spatial resolution ATLAS imagery. For the purpose of comparison and to evaluate the effectiveness of the wavelet approaches, two different fractal approaches (isarithm and triangular prism), spatial autocorrelation (Moran's I and Geary's C), and spatial co-occurrence matrix of the selected urban classes were examined using 65 X 65, 33 X 33, and 17 X 17 samples with a pixel size of 2.5 m. Results from this study suggest that a multi-band and multi-level wavelet approach can be used to drastically increase the classification accuracy. The fractal techniques did not provide satisfactory classification accuracy. Spatial autocorrelation and spatial co-occurrence techniques were found to be relatively effective when compared to the fractal approaches. It can be concluded that the wavelet transform approach is the most accurate of all four approaches. Numéro de notice : A2004-273 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.70.7.803 En ligne : https://doi.org/10.14358/PERS.70.7.803 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26800
in Photogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 7 (July 2004) . - pp 803 - 812[article]Automatic change detection by evidential fusion of change indices / Sylvie Le Hégarat-Mascle in Remote sensing of environment, vol 91 n° 3 (30/06/2004)
[article]
Titre : Automatic change detection by evidential fusion of change indices Type de document : Article/Communication Auteurs : Sylvie Le Hégarat-Mascle, Auteur ; R. Seltzer, Auteur Année de publication : 2004 Article en page(s) : pp 390 - 404 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse texturale
[Termes IGN] détection de changement
[Termes IGN] dommage matériel
[Termes IGN] fusion de données
[Termes IGN] image optique
[Termes IGN] incendie de forêt
[Termes IGN] théorie de Dempster-Shafer
[Termes IGN] valeur radiométriqueRésumé : (Auteur) The detection of changes affecting continental surfaces has important applications in hydrological, meteorological, and climatic modeling. We propose a way to improve mono-index change detection by a fusion of multi-index change detection results. This fusion is performed in the framework of the Dempster-Shafer evidence theory, which is particularly suited to the representation of imprecision and ignorance at the "no change"/" change" class border. Depending on the change detection index considered, we also need to determine the class number and features. This is done using the a contrario theory approach rather than classical statistical tests. The proposed algorithm is applied to forest fire damage evaluation based on three popular change indices: normalized difference values, texture evolution, and mutual information (MI). We find that change index fusion is effective at reducing both false alarm and misdetection levels, due to the complementary nature of these indices. Numéro de notice : A2004-281 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.04.001 En ligne : https://doi.org/10.1016/j.rse.2004.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26808
in Remote sensing of environment > vol 91 n° 3 (30/06/2004) . - pp 390 - 404[article]Change detection techniques / Dong Lu in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)
[article]
Titre : Change detection techniques Type de document : Article/Communication Auteurs : Dong Lu, Auteur ; P. Mausel, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 2365 - 2407 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse en composantes principales
[Termes IGN] capteur (télédétection)
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] détection de changement
[Termes IGN] limite de résolution géométrique
[Termes IGN] seuillage d'image
[Termes IGN] système d'information géographique
[Termes IGN] traitement d'imageRésumé : (Auteur) Timely and accurate change detection of Earth's surface features is extremely important for understanding relationships and interactions between human and natural phenomena in order to promote better decision making. Remote sensing data are primary sources extensively used for change detection in recent decades. Many change detection techniques have been developed. This paper summarizes and reviews these techniques. Previous literature has shown that image differencing, principal component analysis and post-classification comparison are the most common methods used for change detection. In recent years, spectral mixture analysis, artificial neural networks and integration of geographical information system and remote sensing data have become important techniques for change detection applications. Different change detection algorithms have their own merits and no single approach is optimal and applicable to all cases. In practice, different algorithms are often compared to find the best change detection results for a specific application. Research of change detection techniques is still an active topic and new techniques are needed to effectively use the increasingly diverse and complex remotely sensed data available or projected to be soon available from satellite and airborne sensors. This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature. Numéro de notice : A2004-223 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000139863 En ligne : https://doi.org/10.1080/0143116031000139863 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26750
in International Journal of Remote Sensing IJRS > vol 25 n° 12 (June 2004) . - pp 2365 - 2407[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-04101 RAB Revue Centre de documentation En réserve L003 Disponible Examining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case / D. Chen in International Journal of Remote Sensing IJRS, vol 25 n° 11 (June 2004)
[article]
Titre : Examining the effect of spatial resolution and texture window size on classification accuracy: an urban environment case Type de document : Article/Communication Auteurs : D. Chen, Auteur ; D.A. Stow, Auteur ; P. Gong, Auteur Année de publication : 2004 Article en page(s) : pp 2177 - 2092 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] image multibande
[Termes IGN] limite de résolution géométrique
[Termes IGN] limite de résolution spectrale
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] périphérie urbaine
[Termes IGN] précision de la classification
[Termes IGN] San Diego
[Termes IGN] texture d'imageRésumé : (Auteur) The purpose of this paper is to evaluate spatial resolution effects on image classification. Classification maps were generated with a maximum likelihood (ML) classifier applied to three multi-spectral bands and variance texture images. A total of eight urban land use/cover classes were obtained at six spatial resolution levels based on a series of aggregated Colour Infrared Digital Orthophoto Quarter Quadrangle (DOQQ) subsets in urban and rural fringe areas of the San Diego metropolitan area. The classification results were compared using overall and individual classification accuracies. Classification accuracies were shown to be influenced by image spatial resolution, window size used in texture extraction and differences in spatial structure within and between categories. The more heterogeneous arc the land use/cover units and the more fragmented are the landscapes, the finer the resolution required. Texture was more effective for improving the classification accuracy of land use classes at finer resolution levels. For spectrally homogeneous classes, a small window is preferable. But for spectrally heterogeneous classes, a large window size is required. Numéro de notice : A2004-230 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001618464 En ligne : https://doi.org/10.1080/01431160310001618464 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26757
in International Journal of Remote Sensing IJRS > vol 25 n° 11 (June 2004) . - pp 2177 - 2092[article]Exemplaires(1)
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