Descripteur
Termes IGN > imagerie > image spatiale > image satellite > image Sentinel > image Sentinel-SAR
image Sentinel-SARSynonyme(s)image Sentinel-1Voir aussi |
Documents disponibles dans cette catégorie (181)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Estimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data / P. Kumar in Geocarto international, vol 33 n° 9 (September 2018)
[article]
Titre : Estimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data Type de document : Article/Communication Auteurs : P. Kumar, Auteur ; R. Prasad, Auteur ; D. K. Gupta, Auteur ; V. N. Mishra, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 942 - 956 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande C
[Termes IGN] blé (céréale)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] croissance végétale
[Termes IGN] cultures
[Termes IGN] données polarimétriques
[Termes IGN] estimation statistique
[Termes IGN] hiver
[Termes IGN] image Sentinel-SAR
[Termes IGN] Leaf Area Index
[Termes IGN] régression
[Termes IGN] régression linéaire
[Termes IGN] réseau neuronal artificiel
[Termes IGN] séparateur à vaste marge
[Termes IGN] teneur en eau de la végétationRésumé : (Auteur) In the present study, Sentinel-1A Synthetic Aperture Radar analysis of time series data at C-band was carried out to estimate the winter wheat crop growth parameters. Five different date images were acquired during January 2015–April 2015 at different growth stages from tillering to ripening in Varanasi district, India. The winter wheat crop parameters, i.e. leaf area index, vegetation water content (VWC), fresh biomass (FB), dry biomass (DB) and plant height (PH) were estimated using random forest regression (RFR), support vector regression (SVR), artificial neural network regression (ANNR) and linear regression (LR) algorithms. The Ground Range Detected products of Interferometric Wide (IW) Swath were used at VV polarization. The three different subplots of 1 m2 area were taken for the measurement of crop parameters at every growth stage. In total, 73 samples were taken as the training data-sets and 39 samples were taken as testing data-sets. The highest sensitivity (adj. R2 = 0.95579) of backscattering with VWC was found using RFR algorithm, whereas the lowest sensitivity (adj. R2 = 0.66201) was found for the PH using LR algorithm. Overall results indicate more accurate estimation of winter wheat parameters by the RFR algorithm followed by SVR, ANNR and LR algorithms. Numéro de notice : A2018-337 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1316781 Date de publication en ligne : 18/04/2017 En ligne : https://doi.org/10.1080/10106049.2017.1316781 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90551
in Geocarto international > vol 33 n° 9 (September 2018) . - pp 942 - 956[article]Synergetic use of Sentinel-1 and Sentinel-2 for assessments of heathland conservation status / Johannes Schmidt in Remote sensing in ecology and conservation, vol 4 n° 3 (September 2018)
[article]
Titre : Synergetic use of Sentinel-1 and Sentinel-2 for assessments of heathland conservation status Type de document : Article/Communication Auteurs : Johannes Schmidt, Auteur ; Fabian E. Fassnacht, Auteur ; Michael Förster, Auteur ; Sebastian Schmidtlein, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Calluna vulgaris
[Termes IGN] directive européenne
[Termes IGN] état de conservation
[Termes IGN] habitat (nature)
[Termes IGN] image Sentinel-SAR
[Termes IGN] site Natura 2000Résumé : (auteur) Habitat quality assessments often demand wall-to-wall information about the state of vegetation. Remote sensing can provide this information by capturing optical and structural attributes of plant communities. Although active and passive remote sensing approaches are considered as complementary techniques, they have been rarely combined for conservation mapping. Here, we combined spaceborne multispectral Sentinel-2 and Sentinel-1 SAR data for a remote sensing-based habitat quality assessment of dwarf shrub heathland, which was inspired by nature conservation field guidelines. Therefore, three earlier proposed quality layers representing (1) the coverage of the key dwarf shrub species, (2) stand structural diversity and (3) an index reflecting co-occurring vegetation were mapped via linking in situ data and remote sensing imagery. These layers were combined in an RGB-representation depicting varying stand attributes, which afterwards allowed for a rule-based derivation of pixel-wise habitat quality classes. The links between field observations and remote sensing data reached correlations between 0.70 and 0.94 for modeling the single quality layers. The spatial patterns shown in the quality layers and the map of discrete quality classes were in line with the field observations. The remote sensing-based mapping of heathland conservation status showed an overall agreement of 76% with field data. Transferring the approach in time (applying a second set of Sentinel-1 and -2 data) caused a decrease in accuracy to 73%. Our findings suggest that Sentinel-1 SAR contains information about vegetation structure that is complimentary to optical data and therefore relevant for nature conservation. While we think that rule-based approaches for quality assessments offer the possibility for gaining acceptance in both communities applied conservation and remote sensing, there is still need for developing more robust and transferable methods. Numéro de notice : A2018-005 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1002/rse2.68 En ligne : https://doi.org/10.1002/rse2.68 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88738
in Remote sensing in ecology and conservation > vol 4 n° 3 (September 2018)[article]Documents numériques
en open access
Synergetic use of Sentinel-1 and Sentinel-2 - pdf éditeurAdobe Acrobat PDF The 2015 Mw 6.4 Pishan earthquake, China: geodetic modelling inferred from Sentinel-1A TOPS interferometry / Yongsheng Li in Survey review, vol 50 n° 363 (September 2018)
[article]
Titre : The 2015 Mw 6.4 Pishan earthquake, China: geodetic modelling inferred from Sentinel-1A TOPS interferometry Type de document : Article/Communication Auteurs : Yongsheng Li, Auteur ; Yi Luo, Auteur ; Jingfa Zhang, Auteur ; Wenliang Jiang, Auteur Année de publication : 2018 Article en page(s) : pp 522 - 530 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] déformation de la croute terrestre
[Termes IGN] faille géologique
[Termes IGN] image Sentinel-SAR
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] modèle géologique
[Termes IGN] séisme
[Termes IGN] Sinkiang (Chine)Résumé : (Auteur) This study investigates the 3 July 2015 (Mw=6.4) earthquake that affected Pishan County in Xinjiang, China. Using Synthetic Aperture Radar interferometry (InSAR), we mapped the near-field surface displacement of this event to better characterize the seismic source parameters. The inverted results suggest that a conjugate fault system could produce very similar deformation patterns as those observed in both ascending and descending InSAR observations, and the south-dipping fault is selected as the optimal fault responsible for the event. The selected fault was concentrated on a thrust fault with a strike of 112°, a dip of 25° and an average rake angle of 89°. The InSAR analysis reveals a fragmentation of the Western Kunlun north margin fault, and the overall deformation of the seismogenic fault is characterized by thrust motion, which is consistent with the transpressional tectonic characteristics of the major faults in this region. Numéro de notice : A2018-451 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2017.1335381 Date de publication en ligne : 07/06/2017 En ligne : https://doi.org/10.1080/00396265.2017.1335381 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91037
in Survey review > vol 50 n° 363 (September 2018) . - pp 522 - 530[article]Assessment of Sentinel-1A data for rice crop classification using random forests and support vector machines / Nguyen-Thanh Son in Geocarto international, vol 33 n° 6 (June 2018)
[article]
Titre : Assessment of Sentinel-1A data for rice crop classification using random forests and support vector machines Type de document : Article/Communication Auteurs : Nguyen-Thanh Son, Auteur ; Chi-Farn Chen, Auteur ; Cheng-Ru Chen ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 587 - 601 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image Sentinel-SAR
[Termes IGN] Oryza (genre)
[Termes IGN] polarimétrie radar
[Termes IGN] production agricole végétale
[Termes IGN] Viet NamRésumé : (Auteur) This study developed an approach to map rice-cropping systems in An Giang and Dong Thap provinces, South Vietnam using multi-temporal Sentinel-1A (S1A) data. The data were processed through four steps: (1) data pre-processing, (2) constructing smooth time series VH backscatter data, (3) rice crop classification using random forests (RF) and support vector machines (SVM) and (4) accuracy assessment. The results indicated that the smooth VH backscatter profiles reflected the temporal characteristics of rice-cropping patterns in the study region. The comparisons between the classification results and the ground reference data indicated that the overall accuracy and Kappa coefficient achieved from RF were 86.1% and 0.72, respectively, which were slightly more accurate than SVM (overall accuracy of 83.4% and Kappa coefficient of 0.67). These results were reaffirmed by the government’s rice area statistics with the relative error in area (REA) values of 0.2 and 2.2% for RF and SVM, respectively. Numéro de notice : A2018-142 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1289555 Date de publication en ligne : 13/02/2017 En ligne : https://doi.org/10.1080/10106049.2017.1289555 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89700
in Geocarto international > vol 33 n° 6 (June 2018) . - pp 587 - 601[article]
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 Cartographie des déformations de surface sur l’île de Taiwan par interférométrie RADAR Sentinel-1 / Miloud Fekaouni (2018)PermalinkConception d’une méthode radar de suivi bimensuel des déforestations et d’une méthode optique de classification d’occupation des sols / Luc Baudoux (2018)PermalinkDétection de changement par imagerie radar sur les zones naturelles et agricoles en milieu tropical / Jérôme Lebreton (2018)PermalinkEstimation of surface roughness over bare agricultural soil from Sentinel-1 data / Mohammad Choker (2018)PermalinkEtude préalable à l'installation d'un coin radar sur le site de co-localisation de Calern / Guillaume Schmidt (2018)PermalinkExploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region / Tao Zhou in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)PermalinkGeometric multi-wavelet total variation for SAR image time series analysis / Abdourrahmane M. Atto (2018)PermalinkPotential and limits of Sentinel-1 data for small alpine glaciers monitoring / Matthias Jauvin (2018)PermalinkQGIS in Remote Sensing, Volume 2. QGIS and applications in agriculture and forest / Nicolas Baghdadi (2018)PermalinkSatellite remote sensing of the variability of the continental hydrology cycle in the lower Mekong basin over the last two decades / Binh Pham-Duc (2018)Permalink