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Dynamics of coastal landform features along the southern Tamil Nadu of India by using remote sensing and Geographic Information System / P. Mujabar in Geocarto international, vol 27 n° 4 (July 2012)
[article]
Titre : Dynamics of coastal landform features along the southern Tamil Nadu of India by using remote sensing and Geographic Information System Type de document : Article/Communication Auteurs : P. Mujabar, Auteur ; N. Chandrasekar, Auteur Année de publication : 2012 Article en page(s) : pp 347 - 370 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] détection de changement
[Termes IGN] érosion anthropique
[Termes IGN] érosion côtière
[Termes IGN] image IRS
[Termes IGN] littoral
[Termes IGN] Tamil Nadu (Inde ; état)Résumé : (Auteur) This article reveals an application of multi-spectral satellite data for analysing the dynamics of different coastal landform features along the southern coastal Tamil Nadu of India. An integrated approach comprising visual image interpretation and maximum-likelihood supervised classification has been employed to classify the coastal landforms by using IRS data (during the period 1999–2006). The quality of image classification has been assessed by performing the accuracy assessments with the existing thematic maps and finally the coastal landforms have been mapped. The study reveals that the dynamics of coastal landforms such as sandy beaches, mud-flats, sand dunes and salt marshes along the study area are mostly influenced by the coastal processes, sediment transport, geomorphology and anthropogenic activities. Major anthropogenic sources for the perturbation of beach sediment budgets and a cause of beach erosion along the study area are excessive sand mining, removal of sand dunes, coastal urbanization, tourism and developmental activities. Numéro de notice : A2012-335 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.638988 Date de publication en ligne : 06/01/2012 En ligne : https://doi.org/10.1080/10106049.2011.638988 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31781
in Geocarto international > vol 27 n° 4 (July 2012) . - pp 347 - 370[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012041 RAB Revue Centre de documentation En réserve L003 Disponible The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass / T.M. Basuki in Geocarto international, vol 27 n° 4 (July 2012)
[article]
Titre : The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass Type de document : Article/Communication Auteurs : T.M. Basuki, Auteur ; Andrew K. Skidmore, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 329 - 345 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] biomasse
[Termes IGN] estimation statistique
[Termes IGN] forêt tropicale
[Termes IGN] image Landsat-ETM+
[Termes IGN] Indonésie
[Termes IGN] régressionRésumé : (Auteur) A main limitation of pixel-based vegetation indices or reflectance values for estimating above-ground biomass is that they do not consider the mixed spectral components on the earth's surface covered by a pixel. In this research, we decomposed mixed reflectance in each pixel before developing models to achieve higher accuracy in above-ground biomass estimation. Spectral mixture analysis was applied to decompose the mixed spectral components of Landsat-7 ETM+ imagery into fractional images. Afterwards, regression models were developed by integrating training data and fraction images. The results showed that the spectral mixture analysis improved the accuracy of biomass estimation of Dipterocarp forests. When applied to the independent validation data set, the model based on the vegetation fraction reduced 5–16% the root mean square error compared to the models using a single band 4 or 5, multiple bands 4, 5, 7 and all non-thermal bands of Landsat ETM+. Numéro de notice : A2012-334 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.634928 Date de publication en ligne : 05/12/2011 En ligne : https://doi.org/10.1080/10106049.2011.634928 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31780
in Geocarto international > vol 27 n° 4 (July 2012) . - pp 329 - 345[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012041 RAB Revue Centre de documentation En réserve L003 Disponible Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions / M. Cutler in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
[article]
Titre : Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions Type de document : Article/Communication Auteurs : M. Cutler, Auteur ; D. Boyd, Auteur ; Giles M. Foody, Auteur ; A. Vetrivel, Auteur Année de publication : 2012 Article en page(s) : pp 66 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse comparative
[Termes IGN] analyse texturale
[Termes IGN] biomasse
[Termes IGN] biomasse (combustible)
[Termes IGN] Brésil
[Termes IGN] classification par réseau neuronal
[Termes IGN] déboisement
[Termes IGN] forêt tropicale
[Termes IGN] image JERS
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image radar
[Termes IGN] Malaisie
[Termes IGN] matrice de co-occurrence
[Termes IGN] niveau de gris (image)
[Termes IGN] ondelette
[Termes IGN] texture d'image
[Termes IGN] ThaïlandeRésumé : (Auteur) Quantifying the above ground biomass of tropical forests is critical for understanding the dynamics of carbon fluxes between terrestrial ecosystems and the atmosphere, as well as monitoring ecosystem responses to environmental change. Remote sensing remains an attractive tool for estimating tropical forest biomass but relationships and methods used at one site have not always proved applicable to other locations. This lack of a widely applicable general relationship limits the operational use of remote sensing as a method for biomass estimation, particularly in high biomass ecosystems. Here, multispectral Landsat TM and JERS-1 SAR data were used together to estimate tropical forest biomass at three separate geographical locations: Brazil, Malaysia and Thailand. Texture measures were derived from the JERS-1 SAR data using both wavelet analysis and Grey Level Co-occurrence Matrix methods, and coupled with multispectral data to provide inputs to artificial neural networks that were trained under four different training scenarios and validated using biomass measured from 144 field plots. When trained and tested with data collected from the same location, the addition of SAR texture to multispectral data showed strong correlations with above ground biomass (r = 0.79, 0.79 and 0.84 for Thailand, Malaysia and Brazil respectively). Also, when networks were trained and tested with data from all three sites, the strength of correlation (r = 0.55) was stronger than previously reported results from the same sites that used multispectral data only. Uncertainty in estimating AGB from different allometric equations was also tested but found to have little effect on the strength of the relationships observed. The results suggest that the inclusion of SAR texture with multispectral data can go someway towards providing relationships that are transferable across time and space, but that further work is required if satellite remote sensing is to provide robust and reliable methodologies for initiatives such as Reducing Emissions from Deforestation and Degradation (REDD+). Numéro de notice : A2012-289 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31735
in ISPRS Journal of photogrammetry and remote sensing > vol 70 (June 2012) . - pp 66 - 77[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012041 SL Revue Centre de documentation Revues en salle Disponible A framework for automatic and unsupervised detection of multiple changes in multitemporal images / Francesca Bovolo in IEEE Transactions on geoscience and remote sensing, vol 50 n° 6 (June 2012)
[article]
Titre : A framework for automatic and unsupervised detection of multiple changes in multitemporal images Type de document : Article/Communication Auteurs : Francesca Bovolo, Auteur ; S. Marchesi, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2012 Article en page(s) : pp 2196 - 2212 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] bande B
[Termes IGN] classification bayesienne
[Termes IGN] détection automatique
[Termes IGN] détection de changement
[Termes IGN] image multibande
[Termes IGN] image multitemporelle
[Termes IGN] seuillage d'imageRésumé : (Auteur) The detection of multiple changes (i.e., different kinds of change) in multitemporal remote sensing images is a complex problem. When multispectral images having B spectral bands are considered, an effective solution to this problem is to exploit all available spectral channels in the framework of supervised or partially supervised approaches. However, in many real applications, it is difficult/impossible to collect ground truth information for either multitemporal or single-date images. On the opposite, unsupervised methods available in the literature are not effective in handling the full information present in multispectral and multitemporal images. They usually consider a simplified subspace of the original feature space having small dimensionality and, thus, characterized by a possible loss of change information. In this paper, we present a framework for the detection of multiple changes in bitemporal and multispectral remote sensing images that allows one to overcome the limits of standard unsupervised methods. The framework is based on the following: 1) a compressed yet efficient 2-D representation of the change information and 2) a two-step automatic decision strategy. The effectiveness of the proposed approach has been tested on two bitemporal and multispectral data sets having different properties. Results obtained on both data sets confirm the effectiveness of the proposed approach. Numéro de notice : A2012-264 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2171493 Date de publication en ligne : 21/11/2011 En ligne : https://doi.org/10.1109/TGRS.2011.2171493 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31710
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 6 (June 2012) . - pp 2196 - 2212[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012061 RAB Revue Centre de documentation En réserve L003 Disponible Geometric unmixing of large hyperspectral images: A barycentric coordinate approach / Paul Honeine in IEEE Transactions on geoscience and remote sensing, vol 50 n° 6 (June 2012)
[article]
Titre : Geometric unmixing of large hyperspectral images: A barycentric coordinate approach Type de document : Article/Communication Auteurs : Paul Honeine, Auteur ; C. Richard, Auteur Année de publication : 2012 Article en page(s) : pp 2185 - 2195 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme du simplexe
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] classification barycentrique
[Termes IGN] image hyperspectraleRésumé : (Auteur) In hyperspectral imaging, spectral unmixing is one of the most challenging and fundamental problems. It consists of breaking down the spectrum of a mixed pixel into a set of pure spectra, called endmembers, and their contributions, called abundances. Many endmember extraction techniques have been proposed in literature, based on either a statistical or a geometrical formulation. However, most, if not all, of these techniques for estimating abundances use a least-squares solution. In this paper, we show that abundances can be estimated using a geometric formulation. To this end, we express abundances with the barycentric coordinates in the simplex defined by endmembers. We propose to write them in terms of a ratio of volumes or a ratio of distances, which are quantities that are often computed to identify endmembers. This property allows us to easily incorporate abundance estimation within conventional endmember extraction techniques, without incurring additional computational complexity. We use this key property with various endmember extraction techniques, such as N-Findr, vertex component analysis, simplex growing algorithm, and iterated constrained endmembers. The relevance of the method is illustrated with experimental results on real hyperspectral images. Numéro de notice : A2012-263 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2188408 Date de publication en ligne : 14/11/2011 En ligne : https://doi.org/10.1109/TGRS.2012.2188408 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31709
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 6 (June 2012) . - pp 2185 - 2195[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012061 RAB Revue Centre de documentation En réserve L003 Disponible A geometry and texture coupled flexible generalization of urban building models / M. Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)PermalinkSpatial resolution imagery requirements for identifying structure damage in a hurricane disaster: A cognitive approach / S. Battersby in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 6 (June 2012)PermalinkUtilisation de l'imagerie radar TerraSar-X THRS pour le suivi de la coupe de canne à sucre à l'île de la Réunion / Nicolas Baghdadi in Revue Française de Photogrammétrie et de Télédétection, n° 197 (Juin 2012)PermalinkEvaluation of bayesian despeckling and texture extraction methods based on Gauss–Markov and auto-binomial gibbs random fields: Application to TerraSAR-X data / D. Espinoza Molina in IEEE Transactions on geoscience and remote sensing, vol 50 n° 5 Tome 2 (May 2012)PermalinkUrban tree cover mapping with relief-corrected aerial imagery and lidar / B. Lehrbass in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 5 (May 2012)PermalinkPotential of texture measurements of two-date dual polarization PALSAR data for the improvement of forest biomass estimation / M. Sarker in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)PermalinkDétection et localisation 3D de panneaux de signalisation [diaporama] / Bahman Soheilian (08/03/2012)PermalinkBuilding-damage detection using pre- and post-seismic high-resolution satellite stereo imagery: A case study of the May 2008 Wenchuan earthquake / X. Tong in ISPRS Journal of photogrammetry and remote sensing, vol 68 (March 2012)PermalinkDevelopment of a network-based method for unmixing of hyperspectral data / V. Karathanassi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)PermalinkExtraction of building roof contours from LiDAR data using a Markov-random-field-based approach / E. Dos Santos Galvanin in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)PermalinkHyperspectral unmixing based on mixtures of Dirichlet components / J. Nascimento in IEEE Transactions on geoscience and remote sensing, vol 50 n° 3 (March 2012)PermalinkIntegrated point and edge matching on poor textural images constrained by self-adaptive triangulations / B. Wu in ISPRS Journal of photogrammetry and remote sensing, vol 68 (March 2012)PermalinkMonitoring disasters with a constellation of satellites - type examples from the International Charter ‘Space and Major Disasters’ / A. Mahmood in Geocarto international, vol 27 n° 2 (March 2012)PermalinkRoad network extraction in suburban areas / A. Grote in Photogrammetric record, vol 27 n° 137 (March - May 2012)PermalinkCoupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion / N. Yokoya in IEEE Transactions on geoscience and remote sensing, vol 50 n° 2 (February 2012)PermalinkFiltering and segmentation of polarimetric SAR data based on binary partition trees / A. Alonso-Gonzalez in IEEE Transactions on geoscience and remote sensing, vol 50 n° 2 (February 2012)PermalinkMeasuring historical coastal change using GIS and the change polygon approach / M. Smith in Transactions in GIS, vol 16 n° 1 (February 2012)PermalinkPermalinkAutomated detection of prehistorical rock art features aided by TLS and 2D data co-registration / Jean-Baptiste Lamontre (2012)PermalinkCartographie du déboisement à partir de données à haute résolution spatiale / Yannick Philippets (2012)PermalinkPermalinkChange detection of trees in urban areas using multi-temporal airborne lidar point clouds / Wen Xiao (2012)PermalinkDétection et identification de zones de végétation arborée: utilisation conjointe d'images satellite RapidEye et de données BDOrtho / François Tassin (2012)PermalinkModelling the Zn emissions from roofing materials at Créteil city scale : Defining a methodology / Emna Sellami-Kaaniche (2012)PermalinkPermalinkRecovering quasi-real occlusion-free textures for facade models by exploiting fusion of image and laser street data and image inpainting / Karim Hammoudi (2012)PermalinkSegmentation d'images de façades de bâtiments acquises d'un point de vue terrestre / Jean-Pascal Burochin (2012)PermalinkThe unmixing of atmospheric trace gases from hyperspectral satellite data / P. 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