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Mapping tropical forest structure in south-eastern Madagascar using remote sensing and artificial neural networks / J.C. Ingram in Remote sensing of environment, vol 94 n° 4 (28/02/2005)
[article]
Titre : Mapping tropical forest structure in south-eastern Madagascar using remote sensing and artificial neural networks Type de document : Article/Communication Auteurs : J.C. Ingram, Auteur ; T.P. Dawson, Auteur ; R.J. Whittaker, Auteur Année de publication : 2005 Article en page(s) : pp 491 - 507 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des correspondances
[Termes IGN] analyse multibande
[Termes IGN] biodiversité
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal
[Termes IGN] densité
[Termes IGN] forêt tropicale
[Termes IGN] image Landsat-ETM+
[Termes IGN] Madagascar
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] radiance
[Termes IGN] troncRésumé : (Auteur) Tropical forest condition has important implications for biodiversity, climate change and human needs. Structural features of forests can serve as useful indicators of forest condition and have the potential to be assessed with remotely sensed imagery, which can provide quantitative information on forest ecosystems at high temporal and spatial resolutions. Herein, we investigate the utility of remote sensing for assessing, predicting and mapping two important forest structural features, stem density and basal area, in tropical, littoral forests in southeastern Madagascar. We analysed the relationships of basal area and stem density measurements to the Normalised Difference Vegetation Index (NDVI) and radiance measurements in bands 3, 4, 5 and 7 from the Landsat Enhanced Thematic Mapper Plus (ETM+). Strong relationships were identified among all of the individual bands and field based measurements of basal area (p Numéro de notice : A2005-069 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.12.001 En ligne : https://doi.org/10.1016/j.rse.2004.12.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27207
in Remote sensing of environment > vol 94 n° 4 (28/02/2005) . - pp 491 - 507[article]A novel method for generating 3D city models from high resolution and multi-sensor remote sensing data / Jochen Schiewe in International Journal of Remote Sensing IJRS, vol 26 n° 4 (February 2005)
[article]
Titre : A novel method for generating 3D city models from high resolution and multi-sensor remote sensing data Type de document : Article/Communication Auteurs : Jochen Schiewe, Auteur ; Manfred Ehlers, Auteur Année de publication : 2005 Article en page(s) : pp 683 - 698 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] caméra numérique
[Termes IGN] classification
[Termes IGN] classification dirigée
[Termes IGN] image à haute résolution
[Termes IGN] image aérienne
[Termes IGN] image multicapteur
[Termes IGN] modèle 3D de l'espace urbainRésumé : (Auteur) Modelling urban objects and phenomena puts extremely high demands on the acquisition and analysis of the necessary data. In this context, digital airborne camera systems offer very high spatial resolutions and the simultaneous acquisition of elevation data-either through stereo-matching or by laser scanning. However, with these data the user community faces new problems in their analysis. In response, region-based classification approaches have been developed, but these are not yet fully automatic, reliable and transferable. Hence, this paper proposes a novel hybrid and multi-scale methodology which performs a classification on all segmented levels (called 'Classification on multiple Segment levels', ComS). First investigations validate the applicability as well as the accuracy of the proposed methodology compared with conventional approaches, such as a supervised, pixel-based maximum likelihood classification. Numéro de notice : A2005-052 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331316829 En ligne : https://doi.org/10.1080/01431160512331316829 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27190
in International Journal of Remote Sensing IJRS > vol 26 n° 4 (February 2005) . - pp 683 - 698[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05041 RAB Revue Centre de documentation En réserve L003 Exclu du prêt The utility of texture analysis to improve per-pixel classification for high to very high spatial resolution imagery / Anne Puissant in International Journal of Remote Sensing IJRS, vol 26 n° 4 (February 2005)
[article]
Titre : The utility of texture analysis to improve per-pixel classification for high to very high spatial resolution imagery Type de document : Article/Communication Auteurs : Anne Puissant, Auteur ; Jacky Hirsch, Auteur ; Christiane Weber, Auteur Année de publication : 2005 Article en page(s) : pp 733 - 745 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse texturale
[Termes IGN] classification automatique
[Termes IGN] extraction automatique
[Termes IGN] image à haute résolution
[Termes IGN] image à très haute résolution
[Termes IGN] milieu urbain
[Termes IGN] précision de la classification
[Termes IGN] précision géométrique (imagerie)Résumé : (Auteur) Earth observation data are becoming available at increasingly finer resolutions. Sensors already in existence (IKONOS, Quickbird, SPOT 5, Orbview) or due to be launched in the near future will reach 1-5 m resolution. These very high resolution (VHR) data will provide more details of the urban areas, but it seems evident that they will create additional problems in terms of information extraction using automatic classification. In this framework, this paper examines the potential of the spectral/textural approach to improve the classification accuracy of intra-urban land cover types. The utility of the textural analysis was measured in comparison with multi-spectral per-pixel classifications. Haralick's second-order statistics were applied to the co-occurrence matrix. Four texture indices with six window sizes created from panchromatic images were tested on images at high to very high resolutions (10-1 m). The results show that the optimal index improving the global classification accuracy is the homogeneity measure, with a 7 x 7 window size. Moreover, for 1 m images, texture measure of homogeneity allows one to decrease the shadows. Numéro de notice : A2005-053 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331316838 En ligne : https://doi.org/10.1080/01431160512331316838 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27191
in International Journal of Remote Sensing IJRS > vol 26 n° 4 (February 2005) . - pp 733 - 745[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05041 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Urban development in the Athens metropolitan area using remote sensing data with supervised analysis and GIS / Christiane Weber in International Journal of Remote Sensing IJRS, vol 26 n° 4 (February 2005)
[article]
Titre : Urban development in the Athens metropolitan area using remote sensing data with supervised analysis and GIS Type de document : Article/Communication Auteurs : Christiane Weber, Auteur ; C. Petropoulou, Auteur ; Jacky Hirsch, Auteur Année de publication : 2005 Article en page(s) : pp 785 - 796 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Athènes
[Termes IGN] classification dirigée
[Termes IGN] croissance urbaine
[Termes IGN] image multibande
[Termes IGN] image satellite
[Termes IGN] luminance lumineuse
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] paysage urbain
[Termes IGN] système d'information géographiqueRésumé : (Auteur) In this study, a set of multi-spectral images were used to locate and identify the irregular settlements zones in the Athens metropolitan area. To achieve this goal, indexes-Brightness Index and Normalized Difference Vegetation Index-and supervised classification are computed and applied to the images. In order to locate and identify these regions, common biophysical characteristics related to the urban and suburban landscape structures were identified. Five types of biophysical class were distinguished: (1) inner dense city with high buildings and absence of vegetation; (2) suburban areas with recent construction of buildings and absence of vegetation ; (3) green suburban areas; (4) high-density vegetation zones; and (5) recent forest fire regions. Some limitations are presented and discussed due to confusion of land-cover types between bare land and recent constructed areas, or between various types of vegetation and some urban green zones. Results are integrated within a Geographical Information System (GIS), allowing the user to check the legaI situation of the classified areas using the Urban Plan of Athens (1983-1995) documentation. This facilitates a proposal and representation of topology of irregular settlements. Such techniques might be very fruitful for developing countries or recently industrialized ones to identify speciflic irregular settlements. Numéro de notice : A2005-055 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331316856 En ligne : https://doi.org/10.1080/01431160512331316856 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27193
in International Journal of Remote Sensing IJRS > vol 26 n° 4 (February 2005) . - pp 785 - 796[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05041 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Satellite image classification using genetically guided fuzzy clustering with spatial information / S. Bandyopadhyay in International Journal of Remote Sensing IJRS, vol 26 n° 3 (February 2005)
[article]
Titre : Satellite image classification using genetically guided fuzzy clustering with spatial information Type de document : Article/Communication Auteurs : S. Bandyopadhyay, Auteur Année de publication : 2005 Article en page(s) : pp 579 - 593 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse de groupement
[Termes IGN] Bombay
[Termes IGN] classification floue
[Termes IGN] classification non dirigée
[Termes IGN] image satellite
[Termes IGN] pixel
[Termes IGN] segmentation d'image
[Termes IGN] utilisation du solRésumé : (Auteur) Land-cover classification of satellite images is an important task in analysis of remote sensing imagery. Segmentation is one of the widely used techniques in this regard. One of the important approaches for segmentation of an image is by clustering the pixels in the spectral domain, where pixels that share some common spectral property are put in the same group, or cluster. However, such spectral clustering completely ignores the spatial information contained in the pixels, which is often an important consideration for good segmentation of images. Moreover, the clustering algorithms often provide locally optimal solutions. In this paper, we propose to perform. image segmentation by a genetically guided unsupervised fuzzy clustering technique where some spatial information of the pixels is incorporated. Two ways of incorporating spatial information are suggested. The characteristic of this technique is that it is able to determine automatically the appropriate number of clusters without making any assumptions regarding the dataset. while attempting to provide globally near optimal solutions. In order to evolve the appropriate number of clusters, the chromosome encoding scheme is enhanced to incorporate the don't care symbol (#). Real-coded genetic algorithm with appropriatly defined operators is used. A cluster validity index is used as a measure of the value of the chromosomes. Results, both quantitative and qualitative are demonstrated for several images, including a satellite image of a part of the city of Mumbai. Numéro de notice : A2005-042 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331316432 En ligne : https://doi.org/10.1080/01431160512331316432 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27180
in International Journal of Remote Sensing IJRS > vol 26 n° 3 (February 2005) . - pp 579 - 593[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-05031 RAB Revue Centre de documentation En réserve L003 Disponible Double SIG à Saint-Etienne / Françoise de Blomac in SIG la lettre, n° 64 (février 2005)PermalinkEstimation and monitoring of bare soil/vegetation ratio with SPOT vegetation and HRVIR / Grégoire Mercier in IEEE Transactions on geoscience and remote sensing, vol 43 n° 2 (February 2005)PermalinkSpatio-temporal dynamics in California's central valley: empirical links to urban theory / C. Dietzel in International journal of geographical information science IJGIS, vol 19 n° 2 (february 2005)PermalinkPerformance of different spectral and textural photograph features in multi-source forest inventory / Sakari Tuominen in Remote sensing of environment, vol 94 n° 2 (30/01/2005)Permalink7e conférence francophone sur l'apprentissage automatique, CAp 2005, [Plate-forme AFIA], 30 mai - 3 juin 2005, Nice, France / François Denis (2005)Permalink7es Rencontres des Jeunes Chercheurs en Intelligence Artificielle [Plate-forme AFIA 2005] / Emmanuel Guéré (2005)PermalinkAgriculture classification using PolSAR data / H. Skriver (2005)PermalinkAlternative representations of in-stream habitat: classification using remote sensing, hydraulic modelling, and fuzzy logic / C. Legleiter in International journal of geographical information science IJGIS, vol 19 n° 1 (january 2005)PermalinkAnalysis of the spectral variability of urban materials for classification : A case study over Toulouse (France) / Sophie Lacherade (2005)PermalinkApplication des réseaux bayésiens de classification dans les systèmes d'informatin géographique / Marie-Aline Cavarroc (2005)Permalink