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A new scheme for urban impervious surface classification from SAR images / Hongsheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)
[article]
Titre : A new scheme for urban impervious surface classification from SAR images Type de document : Article/Communication Auteurs : Hongsheng Zhang, Auteur ; Hui Lin, Auteur ; Yunpeng Wang, Auteur Année de publication : 2018 Article en page(s) : pp 103 - 118 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification
[Termes IGN] Hong-Kong
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] Macao
[Termes IGN] polarimétrie radar
[Termes IGN] Shenzhen
[Termes IGN] surface imperméable
[Termes IGN] zone urbaineRésumé : (Auteur) Urban impervious surfaces have been recognized as a significant indicator for various environmental and socio-economic studies. There is an increasingly urgent demand for timely and accurate monitoring of the impervious surfaces with satellite technology from local to global scales. In the past decades, optical remote sensing has been widely employed for this task with various techniques. However, there are still a range of challenges, e.g. handling cloud contamination on optical data. Therefore, the Synthetic Aperture Radar (SAR) was introduced for the challenging task because it is uniquely all-time- and all-weather-capable. Nevertheless, with an increasing number of SAR data applied, the methodology used for impervious surfaces classification remains unchanged from the methods used for optical datasets. This shortcoming has prevented the community from fully exploring the potential of using SAR data for impervious surfaces classification. We proposed a new scheme that is comparable to the well-known and fundamental Vegetation-Impervious surface-Soil (V-I-S) model for mapping urban impervious surfaces. Three scenes of fully polarimetric Radsarsat-2 data for the cities of Shenzhen, Hong Kong and Macau were employed to test and validate the proposed methodology. Experimental results indicated that the overall accuracy and Kappa coefficient were 96.00% and 0.8808 in Shenzhen, 93.87% and 0.8307 in Hong Kong and 97.48% and 0.9354 in Macau, indicating the applicability and great potential of the new scheme for impervious surfaces classification using polarimetric SAR data. Comparison with the traditional scheme indicated that this new scheme was able to improve the overall accuracy by up to 4.6% and Kappa coefficient by up to 0.18. Numéro de notice : A2018-111 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.03.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.03.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89541
in ISPRS Journal of photogrammetry and remote sensing > vol 139 (May 2018) . - pp 103 - 118[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018051 RAB Revue Centre de documentation En réserve L003 Disponible Cartographier le relief sous les forêts, et le substrat sous les déserts de sable : les attentes de la mission radar Biomass / Laurent Polidori in XYZ, n° 154 (mars - mai 2018)
[article]
Titre : Cartographier le relief sous les forêts, et le substrat sous les déserts de sable : les attentes de la mission radar Biomass Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur ; Thierry Koleck, Auteur ; Ludovic Villard, Auteur ; Mhamad El Hage, Auteur ; Philippe Paillou, Auteur ; Thuy Le Toan, Auteur Année de publication : 2018 Article en page(s) : pp 56 - 61 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Missions spatiales
[Termes IGN] bande P
[Termes IGN] Biomass
[Termes IGN] désert
[Termes IGN] forêt
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] modèle numérique de terrain
[Termes IGN] polarimétrie radar
[Termes IGN] radar à antenne synthétique
[Termes IGN] tomographie radarRésumé : (Auteur) La mission spatiale Biomass sera lancée par l'Agence spatiale européenne en 2021 avec un radar à synthèse d'ouverture en bande P dans le but de cartographier la biomasse forestière à l'échelle planétaire, ainsi que la hauteur et les dégradations du couvert forestier. Plusieurs produits secondaires sont aussi envisagés, notamment la cartographie 30 du relief sous les forêts et du substrat sous les déserts de sable, qui devraient bénéficier du pouvoir de pénétration des ondes radar en bande P et de l'aptitude de la tomographie à séparer les contributions des différentes couches dans un profil vertical de rétrodiffusion. Ces possibilités ayant été démontrées lors de campagnes aéroportées, la qualité des modèles 3D attendus de la mission Biomass reste à évaluer. Numéro de notice : A2018-090 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89464
in XYZ > n° 154 (mars - mai 2018) . - pp 56 - 61[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 112-2018011 RAB Revue Centre de documentation En réserve L003 Disponible
Titre : Advances in SAR: Sensors, Methodologies, and Applications Type de document : Monographie Auteurs : Timo Balz, Éditeur scientifique ; Uwe Soergel, Éditeur scientifique ; Mattia Crespi, Éditeur scientifique ; Batuhan Osmanoglu, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2018 Importance : 530 p. Format : 17 x 24 cm ISBN/ISSN/EAN : 978-3-03897-183-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] étalonnage
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] image TanDEM-X
[Termes IGN] image TerraSAR-X
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] polarimétrie radar
[Termes IGN] télédétection en hyperfréquenceRésumé : (éditeur) The key importance of radar remote sensing for civil applications has been recognized for decades, and enormous scientific and technical developments have been carried out to further improve SAR sensors and SAR data processing. In recent years, SAR satellite constellations, consisting of two or more satellites, are becoming the “new normal” in SAR remote sensing. The present availability of SAR sensor constellations, such as Cosmo SkyMed, TerraSAR-X/TanDEM-X, and the new Copernicus sensors Sentinel-1A and 1B, supply a continuous stream of imagery with a unique short revisit cycle of only six days. Together with many more operational and planned SAR satellite systems, such as Geo-Fen 3 or NASA ISRO SAR (NISAR), this unprecedented amount of high-quality SAR data is suitable for a variety of applications, provided proper data processing methodology are applied. In "Advances in SAR: Sensors, Methodologies, and Applications" advancements in the field of hardware, software, and applications are presented, covering a wide range of topics. Note de contenu : 1- Pre-flight SAOCOM-1A SAR performance assessment by outdoor campaign
2- On the design of radar corner reflectors for deformation monitoring in
multi-frequency InSAR
3- Identification of C-Band radio frequency interferences from Sentinel-1 data
4- An accelerated backprojection algorithm for monostatic and bistatic SAR processing
5- Signal processing for a multiple-input,division frequency-modulated continuous wave (FMCW)
6- Fast and efficient correction of ground moving targets in a Synthetic Aperture Radar, single-look complex image
7- A unified algorithm for channel imbalance and antenna phase center position calibration of a single-pass multi-baseline TomoSAR System
8- InSAR Deformation Analysis with Distributed Scatterers: A Review Complemented by
New Advances
9- Modeling orbital error in InSAR interferogram using frequency and spatial domain
based methods
10- Ionospheric reconstructions using Faraday rotation in spaceborne polarimetric SAR data
11- An efficient maximum likelihood estimation approach of multi-baseline SAR interferometry for refined topographic mapping in mountainous areas
12- Elevation extraction and deformation monitoring by multitemporal InSAR of Lupu Bridge in Shanghai
13- Ground deformations around the Toktogul reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 data - A case study about the impact of atmospheric corrections on InSAR
time series
14- Time series analysis of very slow landslides in the Three Gorges region through small baseline SAR offset tracking
15- Landslide displacement monitoring with split- bandwidth interferometry: A case study of the shuping landslide in the Three Gorges area
16- Split-band interferometry-assisted phase unwrapping for the phase ambiguities correction
17- Better estimated IEM input parameters using random fractal geometry applied on
multi-frequency SAR data
18- The role of resolution in the estimation of fractal dimension maps From SAR data
19- Statistical modeling of polarimetric SAR data: A survey and challenges
20- Multi-feature segmentation for high-resolution polarimetric SAR data based on fractal net evolution approach
21- PolSAR land cover classification based on roll-invariant and selected hidden polarimetric features in the rotation domain
22- A SAR-based index for landscape changes in African savannas
23- Semi-automated surface water detection with Synthetic Aperture Radar Data: A wetland case study
24- Coherence change-detection with Sentinel-1 for natural and anthropogenic disaster
monitoring in urban areas
25- Multi-layer model based on multi-scale and multi-feature fusion for SAR images
26- L-Band temporal coherence assessment and modeling using amplitude and snow depth
over interior AlaskaNuméro de notice : 28510 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03897-183-2 En ligne : https://doi.org/10.3390/books978-3-03897-183-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97066 Complex-valued convolutional neural network and its application in polarimetric SAR image classification / Zhimian Zhang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 12 (December 2017)
[article]
Titre : Complex-valued convolutional neural network and its application in polarimetric SAR image classification Type de document : Article/Communication Auteurs : Zhimian Zhang, Auteur ; Haipeng Wang, Auteur ; Feng Xu, Auteur ; Ya-Qiu Jin, Auteur Année de publication : 2017 Article en page(s) : pp 7177 - 7188 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] apprentissage dirigé
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] polarimétrie radar
[Termes IGN] réseau neuronal convolutifRésumé : (Auteur) Following the great success of deep convolutional neural networks (CNNs) in computer vision, this paper proposes a complex-valued CNN (CV-CNN) specifically for synthetic aperture radar (SAR) image interpretation. It utilizes both amplitude and phase information of complex SAR imagery. All elements of CNN including input-output layer, convolution layer, activation function, and pooling layer are extended to the complex domain. Moreover, a complex backpropagation algorithm based on stochastic gradient descent is derived for CV-CNN training. The proposed CV-CNN is then tested on the typical polarimetric SAR image classification task which classifies each pixel into known terrain types via supervised training. Experiments with the benchmark data sets of Flevoland and Oberpfaffenhofen show that the classification error can be further reduced if employing CV-CNN instead of conventional real-valued CNN with the same degrees of freedom. The performance of CV-CNN is comparable to that of existing state-of-the-art methods in terms of overall classification accuracy. Numéro de notice : A2017-770 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2743222 En ligne : https://doi.org/10.1109/TGRS.2017.2743222 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88810
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 12 (December 2017) . - pp 7177 - 7188[article]Multilayer projective dictionary pair learning and sparse autoencoder for PolSAR image classification / Yanqiao Chen in IEEE Transactions on geoscience and remote sensing, vol 55 n° 12 (December 2017)
[article]
Titre : Multilayer projective dictionary pair learning and sparse autoencoder for PolSAR image classification Type de document : Article/Communication Auteurs : Yanqiao Chen, Auteur ; Licheng Jiao, Auteur ; Yangyang Li, Auteur ; Jin Zhao, Auteur Année de publication : 2017 Article en page(s) : pp 6683 - 6694 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] apprentissage dirigé
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image radar moirée
[Termes IGN] Perceptron multicouche
[Termes IGN] polarimétrie radarRésumé : (Auteur) Polarimetric synthetic aperture radar (PolSAR) image classification is a vital application in remote sensing image processing. In general, PolSAR image classification is actually a high-dimensional nonlinear mapping problem. The methods based on sparse representation and deep learning have shown a great potential for PolSAR image classification. Therefore, a novel PolSAR image classification method based on multilayer projective dictionary pair learning (MDPL) and sparse auto encoder (SAE) is proposed in this paper. First, MDPL is used to extract features, and the abstract degree of the extracted features is high. Second, in order to get the nonlinear relationship between elements of feature vectors in an adaptive way, SAE is also used in this paper. Three PolSAR images are used to test the effectiveness of our method. Compared with several state-of-the-art methods, our method achieves very competitive results in PolSAR image classification. Numéro de notice : A2017-764 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2727067 En ligne : https://doi.org/10.1109/TGRS.2017.2727067 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88800
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 12 (December 2017) . - pp 6683 - 6694[article]Incidence angle dependence of first-year sea ice backscattering coefficient in Sentinel-1 SAR Imagery over the kara sea / Marko P. Mäkynen in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)PermalinkAn information fusion approach for PALSAR data to retrieve soil moisture / Ankita Jain in Geocarto international, vol 32 n° 9 (September 2017)PermalinkCritical analysis of model-based incoherent polarimetric decomposition methods and investigation of deorientation effect / Pooja Mishra in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)PermalinkTrace coherence : a new operator for polarimetric and interferometric SAR images / Armando Marino in IEEE Transactions on geoscience and remote sensing, vol 55 n° 4 (April 2017)PermalinkSatellite-based probabilistic assessment of soil moisture using C-band quad-polarized RISAT1 data / Manali Pal in IEEE Transactions on geoscience and remote sensing, vol 55 n° 3 (March 2017)PermalinkPermalinkTélédétection pour l'observation des surfaces continentales, Volume 2. Observation des surfaces continentales par télédétection micro-onde / Nicolas Baghdadi (2017)PermalinkUrban damage level mapping based on scattering mechanism investigation using fully polarimetric SAR Data for the 3.11 East Japan earthquake / Si-Wei Chen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)PermalinkMeasure of temporal variation of P-Band radar cross section and temporal coherence of a temperate tree / Clément Albinet in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)PermalinkDistance measure based change detectors for polarimetric SAR imagery / Yonghong Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 9 (September 2016)PermalinkThe impacts of building orientation on polarimetric orientation angle estimation and model-based decomposition for multilook polarimetric SAR data in urban areas / Hongzhong Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkSoil moisture retrieval in agricultural fields using adaptive model-based polarimetric decomposition of SAR data / Lian He in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)PermalinkMapping and characterization of hydrological dynamics in coastal marsh using high temporal resolution Sentinel-1 images / Cécile Cazals in Remote sensing, vol 8 n° 7 (July 2016)PermalinkGLORI: A GNSS-R Dual Polarization Airborne Instrument for Land Surface Monitoring / Erwan Motte in Sensors, vol 16 n° 5 (May 2016)PermalinkCompressive sensing for multibaseline polarimetric SAR tomography of forested areas / Xinwu Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkFirst results from the GLORIE polarimetric GNSS-R airborne campaign dedicated to land parameters estimation / Erwan Motte (2016)PermalinkForcing scale invariance in multipolarization SAR change detection / Vincenzo Carotenuto in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkRadar based classification prior to biomass retrieval from P-Band SAR data / Pierre-Louis Frison (2016)PermalinkCorrecting distortion of polarimetric SAR data induced by ionospheric scintillation / Jun Su Kim in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)PermalinkForest height estimation by means of Pol-InSAR data inversion : The role of the vertical wavenumber / Florian Kugler in IEEE Transactions on geoscience and remote sensing, vol 53 n° 10 (October 2015)Permalink