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Applications of remote sensing and geographic information systems for urban land-cover change studies in Mongolia / D. Amarsaikhan in Geocarto international, vol 24 n° 4 (August - September 2009)
[article]
Titre : Applications of remote sensing and geographic information systems for urban land-cover change studies in Mongolia Type de document : Article/Communication Auteurs : D. Amarsaikhan, Auteur ; H. Blotevogel, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 257 - 271 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] changement d'occupation du sol
[Termes IGN] classificateur paramétrique
[Termes IGN] détection de changement
[Termes IGN] fusion d'images
[Termes IGN] image multitemporelle
[Termes IGN] milieu urbain
[Termes IGN] Mongolie
[Termes IGN] occupation du sol
[Termes IGN] système d'information géographiqueRésumé : (Auteur) The aim of this study is to compare the changes that occurred in the main urban land-cover classes of Ulaanbaatar city, Mongolia, during a centralized economy with those that occurred during a market economy and to describe the socio-economic reasons for the changes. For this purpose, multi-temporal remote sensing and geographical information system (GIS) data sets, as well as census data, are used. To extract the reliable urban land-cover information from the selected remotely sensed data sets, a refined parametric classification algorithm that uses spatial thresholds defined from local and contextual knowledge is constructed. Before applying the classification decision rule, some image fusion techniques are applied to the selected remotely sensed data sets to define the most efficient fusion method for training sample selection and for defining local and contextual knowledge. Overall, the study indicates that during the centralized economy significant changes occurred in a ger area of the city, whereas during the market economy the changes occurred in all areas. Copyright Taylor & Francis Numéro de notice : A2009-305 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040802556173 Date de publication en ligne : 23/07/2009 En ligne : https://doi.org/10.1080/10106040802556173 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29935
in Geocarto international > vol 24 n° 4 (August - September 2009) . - pp 257 - 271[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-09041 RAB Revue Centre de documentation En réserve L003 Disponible Developing collaborative classifiers using an Expert-based Model / Giorgos Mountrakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 7 (July 2009)
[article]
Titre : Developing collaborative classifiers using an Expert-based Model Type de document : Article/Communication Auteurs : Giorgos Mountrakis, Auteur ; R. Watts, Auteur ; L. Luo, Auteur ; Jing Wang, Auteur Année de publication : 2009 Article en page(s) : pp 831 - 843 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classificateur
[Termes IGN] classification à base de connaissances
[Termes IGN] image Landsat
[Termes IGN] Las Vegas
[Termes IGN] mise à l'échelle
[Termes IGN] précision de la classification
[Termes IGN] surface imperméable
[Termes IGN] système expertRésumé : (Auteur) This paper presents a hierarchical, multi-stage adaptive strategy for image classification. We iteratively apply various classification methods (e.g., decision trees, neural networks), identify regions of parametric and geographic space where accuracy is low, and in these regions, test and apply alternate methods repeating the process until the entire image is classified. Currently, classifiers are evaluated through human input using an expert-based system; therefore, this paper acts as the proof of concept for collaborative classifiers. Because we decompose the problem into smaller, more manageable sub-tasks, our classification exhibits increased flexibility compared to existing methods since classification methods are tailored to the idiosyncrasies of specific regions. A major benefit of our approach is its scalability and collaborative support since selected low-accuracy classifiers can be easily replaced with others without affecting classification accuracy in high accuracy areas. At each stage, we develop spatially explicit accuracy metrics that provide straightforward assessment of results by non-experts and point to areas that need algorithmic improvement or ancillary data. Our approach is demonstrated in the task of detecting impervious surface areas, an important indicator for human-induced alterations to the environment, using a 2001 Landsat scene from Las Vegas, Nevada. Copyright ASPRS Numéro de notice : A2009-263 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.7.831 En ligne : https://doi.org/10.14358/PERS.75.7.831 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29893
in Photogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 7 (July 2009) . - pp 831 - 843[article]An adaptive thresholding multiple classifiers system for remote sensing image classification / Y. Tzeng in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 6 (June 2009)
[article]
Titre : An adaptive thresholding multiple classifiers system for remote sensing image classification Type de document : Article/Communication Auteurs : Y. Tzeng, Auteur ; K. Fan, Auteur ; K.S. Chen, Auteur Année de publication : 2009 Article en page(s) : pp 679 - 687 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] classificateur
[Termes IGN] classification automatique
[Termes IGN] classification hybride
[Termes IGN] ensachage
[Termes IGN] image optique
[Termes IGN] image radar
[Termes IGN] seuillage d'imageRésumé : (Auteur) A multiple classifiers system which adopts an effective weighting policy to combine the output of several classifiers, generally leads to a better performance in image classification. The two most commonly used weighting policies are Bagging and Boosting algorithms. However, their performance is limited by high levels of ambiguity among classes. To overcome this difficulty, an adaptive thresholding criterion was proposed. By applying it to SAR and optical images for terrain cover classification, comparisons between the multiple classifiers systems using the Bagging and/or Boosting algorithms with and without the adaptive thresholding criterion were made. Experimental results showed that the classification substantially improved when the adaptive thresholding criterion was used, especially when the level of ambiguity of targets was high. Copyright ASPRS Numéro de notice : A2009-260 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.6.679 En ligne : https://doi.org/10.14358/PERS.75.6.679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29890
in Photogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 6 (June 2009) . - pp 679 - 687[article]Feature reduction using a singular value decomposition for the iterative guided spectral class rejection hybrid classifier / R. Philipps in ISPRS Journal of photogrammetry and remote sensing, vol 64 n° 1 (January - February 2009)
[article]
Titre : Feature reduction using a singular value decomposition for the iterative guided spectral class rejection hybrid classifier Type de document : Article/Communication Auteurs : R. Philipps, Auteur ; L. Watson, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 107 - 116 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse en composantes principales
[Termes IGN] classificateur paramétrique
[Termes IGN] classification hybride
[Termes IGN] décomposition d'image
[Termes IGN] image Landsat-ETM+
[Termes IGN] image multitemporelle
[Termes IGN] précision de la classification
[Termes IGN] Rondonia (Brésil)
[Termes IGN] Virginie (Etats-Unis)Résumé : (Auteur) Feature reduction in a remote sensing dataset is often desirable to decrease the processing time required to perform a classification and improve overall classification accuracy. This paper introduces a feature reduction method based on the singular value decomposition (SVD). This SVD-based feature reduction method reduces the storage and processing requirements of the SVD by utilizing a training dataset. This feature reduction technique was applied to training data from two multitemporal datasets of Landsat TM/ETM+ imagery acquired over a forested area in Virginia, USA and Rondônia, Brazil. Subsequent parallel iterative guided spectral class rejection (pIGSCR) forest/non-forest classifications were performed to determine the quality of the feature reduction. The classifications of the Virginia data were five times faster using SVD-based feature reduction without affecting the classification accuracy. Feature reduction using the SVD was also compared to feature reduction using principal components analysis (PCA). The highest average accuracies for the Virginia dataset (88.34%) and for the Rondônia dataset (93.31%) were achieved using the SVD. The results presented here indicate that SVD-based feature reduction can produce statistically significantly better classifications than PCA. Copyright ISPRS Numéro de notice : A2009-030 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2008.03.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2008.03.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29660
in ISPRS Journal of photogrammetry and remote sensing > vol 64 n° 1 (January - February 2009) . - pp 107 - 116[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-09011 SL Revue Centre de documentation Revues en salle Disponible A Polygonal approach for automation in extraction of serial modular roofs / Y. Avrahami in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 11 (November 2008)
[article]
Titre : A Polygonal approach for automation in extraction of serial modular roofs Type de document : Article/Communication Auteurs : Y. Avrahami, Auteur ; Y. Raizman, Auteur ; Y. Doytsher, Auteur Année de publication : 2008 Article en page(s) : pp 1365 - 1378 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] base de connaissances
[Termes IGN] classificateur paramétrique
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] polygone
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] toit
[Termes IGN] visualisation 3DRésumé : (Auteur) This paper presents a novel approach for automation in roof extraction from two solved aerial images. The approach assumes that roofs are composed of several spatial polygons, and that they can be obtained by extracting all or even only some of them if the model is known. In view of this assumption, innovative algorithms for semi-automatic spatial polygon extraction were developed. These algorithms are based on a 2D approach to solving the 3D reality. Based on these algorithms, an interactive and semi-automatic modelbased approach for automation in roof extraction was developed. The approach is composed of two phases: manual (interactive) and automatic. In the manual (interactive) phase, the operator needs to choose an Expanded Parameterized Model (EPM) from a knowledge base and select one pre-prepared Interactive Option for Extraction (IOE) of the roof. Then, the operator needs to point according to the guidelines of the chosen option in the left image space. In the automatic phase, the selected spatial polygons are extracted, the parameters of the selected model are calculated and the roof is reconstructed. The approach was examined and the results we obtained had standard accuracy. It appears that the approach can be implemented on many types of roofs and under diverse photographic conditions. In this paper, the algorithms, the experiments and the results are detailed. Copyright ASPRS Numéro de notice : A2008-409 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.11.1365 En ligne : https://doi.org/10.14358/PERS.74.11.1365 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29401
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 11 (November 2008) . - pp 1365 - 1378[article]Urban-trees extraction from Quickbird imagery using multiscale spectex-filtering and non-parametric classification / Y.O. Ouma in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 3 (May - June 2008)PermalinkFusion of support vector machines for classification of multisensor data / Björn Waske in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkA supervised artificial immune classifier for remote-sensing imagery / Y. Zhong in IEEE Transactions on geoscience and remote sensing, vol 45 n° 12 Tome 1 (December 2007)PermalinkCarte de consensualité / A. Quirin in Revue internationale de géomatique, vol 17 n° 3-4 (septembre 2007 – février 2008)PermalinkComparative assessment of the measures of thematic classification accuracy / C. Liu in Remote sensing of environment, vol 107 n° 4 (30/04/2007)PermalinkConversion altimétrique des hauteurs ellipsoïdales par GPS / A. Zeggai in XYZ, n° 109 (décembre 2006 - février 2007)PermalinkSome issues in the classification of DAIS hyperspectral data / M. Pal in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkOn the integration of object-based models and field-based models in GIS / K. Kjenstad in International journal of geographical information science IJGIS, vol 20 n° 5 (may 2006)PermalinkMonitoring active volcanism with the autonomous sciencecraft experiment on EO-1 / A.G. Chien in Remote sensing of environment, vol 101 n° 4 (30/04/2006)PermalinkSpectral filtering and classification of terrestrial laser scanner point clouds / Derek D. Lichti in Photogrammetric record, vol 20 n° 111 (September - November 2005)Permalink