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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)
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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]Change detection techniques / Dong Lu in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)
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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]Exemplaires(1)
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)
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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)
Code-barres Cote Support Localisation Section Disponibilité 080-04091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea / S. Lee in International Journal of Remote Sensing IJRS, vol 25 n° 11 (June 2004)
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Titre : Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea Type de document : Article/Communication Auteurs : S. Lee, Auteur ; J. Choi, Auteur ; K. Min, Auteur Année de publication : 2004 Article en page(s) : pp 2037 - 2052 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] base de données localisées
[Termes IGN] cartographie des risques
[Termes IGN] classification dirigée
[Termes IGN] Corée
[Termes IGN] données de terrain
[Termes IGN] effondrement de terrain
[Termes IGN] image IRS
[Termes IGN] linéament
[Termes IGN] lithologie
[Termes IGN] occupation du sol
[Termes IGN] photo-interprétation assistée par ordinateur
[Termes IGN] photographie aérienne
[Termes IGN] risque naturel
[Termes IGN] système d'information géographique
[Termes IGN] zone à risqueRésumé : (Auteur) The aim of this study is to evaluate the hazard of landslides at Boun, Korea, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the Boun area from interpretation of aerial photographs and field surveys. The topographic, soil, forest, geologic, lineament and land cover data were collected, processed and constructed into a spatial database using GIS and remote sensing data. The factors that influence landslide occurrence, such as slope, aspect and curvature of the topography, were calculated from the topographic database. Texture, material, drainage and effective soil thickness were extracted from the soil database, and type, age, diameter and density of timber were extracted from the forest database. The lithology was extracted from the geological database and lineaments were detected from Indian Remote Sensing (IRS) satellite images. The land cover was classified based on the Landsat Thematic Mapper (TM) satellite image. Landslide hazard areas were analysed and mapped, using the landslide-occurrence factors, by the probability-likelihood ratio method. The results of the analysis were verified using actual landslide location data. The validation results showed satisfactory agreement between the hazard map and the existing data on landslide locations. Numéro de notice : A2004-226 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001618734 En ligne : https://doi.org/10.1080/01431160310001618734 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26753
in International Journal of Remote Sensing IJRS > vol 25 n° 11 (June 2004) . - pp 2037 - 2052[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt An advanced system for the automatic classification of multitemporal SAR images / Lorenzo Bruzzone in IEEE Transactions on geoscience and remote sensing, vol 42 n° 6 (June 2004)
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Titre : An advanced system for the automatic classification of multitemporal SAR images Type de document : Article/Communication Auteurs : Lorenzo Bruzzone, Auteur ; Mattia Marconcini, Auteur ; et al., Auteur Année de publication : 2004 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classification automatique
[Termes IGN] classification par réseau neuronal
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] extraction automatique
[Termes IGN] image ERS-SAR
[Termes IGN] image multitemporelle
[Termes IGN] reconnaissance de formesRésumé : (Auteur) A novel system for the classification of multitemporal synthetic aperture radar (SAR) images is presented. It has been developed by integrating an analysis of the multitemporal SAR signal physics with a pattern recognition approach. The system is made up of a feature-extraction module and a neural-network classifier, as well as a set of standard preprocessing procedures. The feature-extraction module derives a set of features from a series of multitemporal SAR images. These features are based on the concepts of long-term coherence and backscattering temporal variability and have been defined according to an analysis of the multitemporal SAR signal behavior in the presence of different land-cover classes. The neural-network classifier (which is based on a radial basis function neural architecture) properly exploits the multitemporal features for producing accurate land-cover maps. Thanks to the effectiveness of the extracted features, the number of measures that can be provided as input to the classifier is significantly smaller than the number of available multitemporal images. This reduces the complexity of the neural architecture (and consequently increases the generalization capabilities of the classifier) and relaxes the requirements relating to the number of training patterns to be used for classifier learning. Experimental results (obtained on a multitemporal series of European Remote Sensing 1 satellite SAR images) confirm the effectiveness of the proposed system, which exhibits both high classification accuracy and good stability versus parameter settings. These results also point out that properly integrating a pattern recognition procedure (based on machine learning) with an accurate feature extraction phase (based on the SAR sensor physics understanding) represents an effective approach to SAR data analysis. Numéro de notice : A2004-264 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2004.826821 En ligne : https://doi.org/10.1109/TGRS.2004.826821 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26791
in IEEE Transactions on geoscience and remote sensing > vol 42 n° 6 (June 2004)[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-04061 RAB Revue Centre de documentation En réserve L003 Disponible Cartographie de la densité du bâti par analyse granulométrique des images de télédetection / Franck Chopin in Revue Française de Photogrammétrie et de Télédétection, n°173-174 (Juin 2004)
PermalinkÉtude de l'extension du bâti sur le littoral sénégalais à partir des paramètres texturaux de Haralick / G. Ackermann in Revue Française de Photogrammétrie et de Télédétection, n°173-174 (Juin 2004)
PermalinkMapping coastal vegetation using an expert system and hyperspectral imagery / K.S. Schmidt in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 6 (June 2004)
PermalinkTélédétection et géo-archéologie : Comparaison des potentialités naturelles d'accueil des gebels Siman et Zawiye, vis-à-vis des sites antiques romano-byzantins de Syrie du nord / M. Abdulkarim in Photo interprétation, vol 40 n° 2 - 3 (Juin 2004)
PermalinkSub-pixel mapping and sub-pixel sharpening using neural network predicted wavelet coefficients / K.C. Mertens in Remote sensing of environment, vol 91 n° 2 (30/05/2004)
PermalinkAn integrated approach for landslide susceptibility mapping using remote sensing and GIS / S. Sarkar in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 5 (May 2004)
PermalinkNonparametric weighted feature extraction for classification / D.A. Landgrebe in IEEE Transactions on geoscience and remote sensing, vol 42 n° 5 (May 2004)
PermalinkLand cover characterization of temperate east Asia using multi-temporal vegetation sensor data / S.H. Boles in Remote sensing of environment, vol 90 n° 4 (30/04/2004)
PermalinkClassification of remotely sensed imagery stochastic gradient boosting as a refinement of classification tree analysis / R. Lawrence in Remote sensing of environment, vol 90 n° 3 (15/04/2004)
PermalinkClassifying land development in high-resolution panchromatic satellite images using straight-line statistics / C. Unsalan in IEEE Transactions on geoscience and remote sensing, vol 42 n° 4 (April 2004)
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