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A multiple-cascade-classifier system for a robust and partially unsupervised updating of land-cover maps / Lorenzo Bruzzone in IEEE Transactions on geoscience and remote sensing, vol 40 n° 9 (September 2002)
[article]
Titre : A multiple-cascade-classifier system for a robust and partially unsupervised updating of land-cover maps Type de document : Article/Communication Auteurs : Lorenzo Bruzzone, Auteur ; R. Cossu, Auteur Année de publication : 2002 Article en page(s) : pp 1984 - 1996 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification non dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] image multitemporelle
[Termes IGN] mise à jour cartographiqueRésumé : (Auteur) A system for a regular updating of landcover maps is proposed that is based on the use of multitemporal remote sensing images. Such a system is able to address the updating problem under the realistic but critical constraint that, for the image to be classified (i.e., the most recent of the considered multitemporal dataset no ground truth information is available. The system is composed of an ensemble of partially unsupervised classifiers integrated in a multipleclassifier architecture. Each classifier of the ensemble exhibits the following novel characteristics: 1) it is developed in the framework of the cascade-classification approach to exploit the temporal correlation existing between images acquired at different times in the considered area; and 2) it is based on a partially unsupervised methodology capable of accomplishing the classification process under the aforementioned critical constraint. Both a parametric maximumlikelihood (ML) classification approach and a nonparametric radial basis function (RBF) neuralnetwork classification approach are used as basic methods for the development of partially unsupervised cascade classifiers. In addition, in order to generate an effective ensemble of classification algorithms, hybrid ML and RBF neuralnetwork cascade classifiers are defined by exploiting the characteristics of the cascadeclassification methodology. The results yielded by the different classifiers are combined by using standard unsupervised combination strategies. This allows the definition of a robust and accurate partially unsupervised classification system capable of analyzing a wide typology of remote sensing data (e.g., images acquired by passive sensors, synthetic aperture radar images, and multisensor and multisource data). Experimental results obtained on a real multitemporal and multisource dataset confirm the effectiveness of the proposed system. Numéro de notice : A2002-287 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.803794 En ligne : https://doi.org/10.1109/TGRS.2002.803794 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22198
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 9 (September 2002) . - pp 1984 - 1996[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02081 RAB Revue Centre de documentation En réserve L003 Disponible Integration of classification methods for improvement of land-cover map accuracy / XiaoHang Liu in ISPRS Journal of photogrammetry and remote sensing, vol 56 n° 4 (July - August 2002)
[article]
Titre : Integration of classification methods for improvement of land-cover map accuracy Type de document : Article/Communication Auteurs : XiaoHang Liu, Auteur ; Andrew K. Skidmore, Auteur ; H.V. Oosten, Auteur Année de publication : 2002 Article en page(s) : pp 257 - 268 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification à base de connaissances
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] occupation du solRésumé : (Auteur) Classifiers, which are used to recognize patterns in remotely sensing images, have complementary capabilities. This study tested whether integrating the results from individual classifiers improves classification accuracy. Two integrated approaches were undertaken. One approach used a consensus builder (CS13) to adjust classification output in the case of disagreement in classification between maximum likelihood classifier (MLC), expert system classifier (ESC) and neural network classifier (NNC). If the output classes for each individual pixel differed, the producer accuracies for each class were compared and the class with the highest producer accuracy was assigned to the pixel. The consensus builder approach resulted in a classification with a slightly lower accuracy (72%) when compared with the neural network classifier (74%), but it did significantly better than the maximum likelihood (62%) and expert system (59%) classifiers. The second approach integrated a rulebased expert system classifier and a neural network classifier. The output of the expert system classifier was used as one additional new input layer of the neural network classifier. A postprocessing using the producer accuracies and some additional expert rules was applied to improve the output of the integrated classifier. This is a relatively new approach in the field of image processing. This second approach produced the highest overall accuracy (80%). Thus, incorporating correct, complete and relevant expert knowledge in a neural network classifier leads to higher classification accuracy. Copyright ISPRS Numéro de notice : A2002-168 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/S0924-2716(02)00061-8 En ligne : https://doi.org/10.1016/S0924-2716(02)00061-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22083
in ISPRS Journal of photogrammetry and remote sensing > vol 56 n° 4 (July - August 2002) . - pp 257 - 268[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-02021 SL Revue Centre de documentation Revues en salle Disponible The utility of very high spatial resolution images to identify urban objects / Anne Puissant in Geocarto international, vol 17 n° 1 (March - May 2002)
[article]
Titre : The utility of very high spatial resolution images to identify urban objects Type de document : Article/Communication Auteurs : Anne Puissant, Auteur ; Christiane Weber, Auteur Année de publication : 2002 Article en page(s) : pp 31 - 41 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] image à résolution métrique
[Termes IGN] image Ikonos
[Termes IGN] image ORBVIEW
[Termes IGN] image SPOT 5
[Termes IGN] image SPOT-HRG
[Termes IGN] milieu urbain
[Termes IGN] morphologie mathématique
[Termes IGN] objet géographique
[Termes IGN] photo-interprétation assistée par ordinateur
[Termes IGN] StrasbourgRésumé : (Auteur) With the diversity of new digital geographic information products and in particular, the new future Very High Spatial Resolution images (1 to 5 m), an evaluation of the capacity of these new data source is necessary in the framework of urban studies. This article aims at assessing the utility of VHSR sensors to provide reliable and useful information for the end-users (city councils, urban community, county) in urban planning, monitoring and management. In fact, which type of end-users must these resolution satisfy, what are the potential applications of these images, what are the characteristics of the information required and finally what type of extraction methods are efficient ? An analysis of these capacities has been carried out for different resolutions and with several extraction methods. This analysis allows on the one hand, to define a " minimal " and a " functional " spatial resolution able to satisfy the needs of end-users, and on the other hand, to determine if this future sensors would provide additional capabilities to study the urban environment. Numéro de notice : A2002-122 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040208542223 En ligne : https://doi.org/10.1080/10106040208542223 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22037
in Geocarto international > vol 17 n° 1 (March - May 2002) . - pp 31 - 41[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-02011 RAB Revue Centre de documentation En réserve L003 Disponible Scale and texture in digital image classification / J.S. Ferro in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 1 (January 2002)
[article]
Titre : Scale and texture in digital image classification Type de document : Article/Communication Auteurs : J.S. Ferro, Auteur ; T.A. Warner, Auteur Année de publication : 2002 Article en page(s) : pp 51 - 63 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] accentuation de contours
[Termes IGN] analyse d'image numérique
[Termes IGN] classification dirigée
[Termes IGN] classification multidimensionnelle
[Termes IGN] classification non dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] image ADAR
[Termes IGN] image multibande
[Termes IGN] incertitude des données
[Termes IGN] qualité d'image
[Termes IGN] superposition d'imagesRésumé : (Auteur) Classification errors using texture are most likely associated with class edges, but investigators often avoid edges when evaluating textures for classification. The large window needed to produce a stable texture measure produce large edge effects. Small windows minimize edge effects, but often do not provide stable texture measures. Simulated data experiments showed that class separability increased when texture was used in addition to spectral information. Texture separability improved with larger windows. This improvement was over estimated when pixels were chosen away from class edges. Airborne Data Acquisition and Registration (ADAR) data showed that separability of class interiors improved with the addition of texture, but that, for the whole class, separability fell. Maximum-likelihood classification of the ADAR data demonstrated the effect of edges and multiple scales in reducing the accuracy of classification incorporating texture. Numéro de notice : A2002-010 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2002journal/january/2002_jan_51-63 [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21927
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 1 (January 2002) . - pp 51 - 63[article]Remote sensing and urban analysis / Jean-Paul Donnay (2001)
Titre : Remote sensing and urban analysis Type de document : Monographie Auteurs : Jean-Paul Donnay, Auteur ; M.J. Barnsley, Auteur ; Paul A. Longley, Auteur Mention d'édition : 1 Editeur : Londres : Taylor & Francis Année de publication : 2001 Collection : GISdata series num. 9 Importance : 268 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-0-7484-0860-3 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] classification
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] croissance urbaine
[Termes IGN] détection de changement
[Termes IGN] géostatistique
[Termes IGN] image satellite
[Termes IGN] milieu urbain
[Termes IGN] modélisation
[Termes IGN] morphologie mathématique
[Termes IGN] morphologie urbaine
[Termes IGN] occupation du sol
[Termes IGN] photographie aérienne
[Termes IGN] reconnaissance de formes
[Termes IGN] segmentation d'image
[Termes IGN] télédétection spatiale
[Termes IGN] texture d'image
[Termes IGN] traitement d'image
[Termes IGN] urbanisation
[Termes IGN] utilisation du sol
[Termes IGN] villeNote de contenu : 1. INTRODUCTION : Remote Sensing and Urban Analysis / J.P. DONNAY, M.J. BARNSLEY & P.A. LONGLEY
2. THE PHYSICAL STRUCTURE AND COMPOSITION OF URBAN AREAS
- Improving the spatial resolution of remotely-sensed images by means of sensor fusion : a general solution using the ARSIS method / T. RANCHIN, L. WALD & M. MANGOLINI
- Urban pattern characterization through geostatistical analysis of satellite images / P.A. BRIVIO & E. ZILIOLI
- Recognizing settlement structure using mathematical morphology and image texture / M. PESARESI & A. BIANCHIN
3. FROM URBAN LAND COVER TO LAND USE
- Modified maximum-likelihood classification algorithms and their application to urban remote sensing / V.MESEV, B. GORTE & P.A. LONGLEY
- Image segmentation for change detection in urban environments / H.P. BAHR
- Inferring urban land use by spatial and structural pattern recognition / M.J. BARNSLEY, L. MOLLER-JENSEN & S.L. BARR
- Urban agglomeration delimitation using remote sensing data / C. WEBER
4. DEFINING URBAN POPULATIONS OVER SPACE AND TIME
- Mesuring urban morphology using remotely-sensed imagery / P.A. LONGLEY & V. MESEV
- Predicting temporal patterns in urban development from remote imagery / M. BATTY & D. HOWES
- Modelling georaphical distributions in urban areas / J.P. DONNAY & D. UNWIN
- Geographical analysis of the population of fast-growing cities in the third world / Y. BAUDOT
5. EPILOGUE
- Remote sensing and urban analysis : a research agenda / P.A. LONGLEY, M.J. BARNSLEY & J.P. DONNAYNuméro de notice : 63934 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=44369 Réservation
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Code-barres Cote Support Localisation Section Disponibilité 63934-01 35.46 Livre Centre de documentation Télédétection Disponible Klassifikation und Interpolation mittels affin invarianter Voronoidiagramme auf der Basis eines Wahrscheinlich- keitsmaßes in großmaßstäbigen Geoinformationssystemen / R. Roschlaub (1999)PermalinkSAR images and ancillary data in crop species interpretation / Leena Matikainen (1998)PermalinkFiltrage du speckle dans les images radar à synthèse d'ouverture polarimétriques et classification supervisée multi-source / Franck Sery (1997)PermalinkLe dépérissement des boisements riverains de la Garonne / M. James (1996)PermalinkIntegration von Form- und Spektralmerkmalen durch künstliche neuronale Netze bei der Satellitenbildklassifizierung / Karl Segl (1996)PermalinkKlassifizierung von multispektralen Bildern unter Verwendung der Clusterformen im Merkmalsraum / M. Zahn (1996)PermalinkUse of error probabilities to improve area estimates based on maximum likelihood classifications / F. Maselli in Remote sensing of environment, vol 31 n° 2 (01/02/1990)PermalinkTélédétection des boisements riverains de la Garonne / G. Gonzales (1988)PermalinkMaximum likelihood classification, optimal or problematic? A comparison with the nearest neighbour classification / F. Ince in International Journal of Remote Sensing IJRS, vol 8 n° 12 (December 1987)PermalinkFast maximum likelihood classification of remotely-sensed imagery / J.J. Settle in International Journal of Remote Sensing IJRS, vol 8 n° 5 (May 1987)Permalink