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Urban deformation monitoring using persistent scatterer Interferometry and SAR tomography / Michele Crosetto (2019)
Titre : Urban deformation monitoring using persistent scatterer Interferometry and SAR tomography Type de document : Monographie Auteurs : Michele Crosetto, Éditeur scientifique ; Oriol Montserrat, Éditeur scientifique ; Alessandra Budillon, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 308 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-03921-127-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande L
[Termes IGN] déformation d'édifice
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] polarimétrie radar
[Termes IGN] série temporelle
[Termes IGN] surveillance d'ouvrage
[Termes IGN] surveillance géologique
[Termes IGN] télédétection en hyperfréquence
[Termes IGN] zone urbaineRésumé : (éditeur) This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this field. Note de contenu : 1- How groundwater level fluctuations and geotechnical properties lead to asymmetric
subsidence: A PSInSAR analysis of land deformation over a transit corridor in the Los
Angeles metropolitan area
2- Subsidence zonation through satellite interferometry in coastal plain environments of NE Italy: A possible tool for geological and geomorphological mapping in urban areas
3- Measuring urban subsidence in the Rome metropolitan area (Italy) with Sentinel-1
SNAP-StaMPS persistent scatterer interferometry
4- Using TSX/TDX pursuit monostatic SAR stacks for PS-InSAR analysis in urban areas
5- A persistent scatterer interferometry procedure based on stable areas to filter the
atmospheric component
6- Displacement monitoring and health evaluation of two bridges using Sentinel-1 SAR images
7- Multi-sensor InSAR analysis of progressive land subsidence over the coastal city of
Urayasu, Japan
8- A methodology to detect and characterize uplift phenomena in urban areas using
Sentinel-1 data
9- Analysis of secular ground motions in Istanbul from a long-term InSAR time-series
(1992–2017)
10- Spatio-temporal characterization of a reclamation settlement in the Shanghai coastal area with time series analyses of X-, C-, and L-Band SAR datasets
11- Wuhan surface subsidence analysis in 2015–2016 based on Sentinel-1A data by SBAS-InSAR
12- SAR tomography as an add-on to PSI: detection of coherent scatterers in the presence of
phase instabilities
13- Super-resolution multi-look detection in SAR tomography
14- Comparison of persistent scatterer interferometry and SAR tomography using Sentinel-1 in urban environment
15- Urban tomographic imaging using polarimetric SAR dataNuméro de notice : 28506 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-03921-127-2 En ligne : https://doi.org/10.3390/books978-3-03921-127-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97029 Urban morpho-types classification from SPOT-6/7 imagery and Sentinel-2 time series / Arnaud Le Bris (2019)
Titre : Urban morpho-types classification from SPOT-6/7 imagery and Sentinel-2 time series Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Nesrine Chehata , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : GeoSud / Conférence : JURSE 2019, Joint Urban Remote Sensing Event 22/05/2019 24/05/2019 Vannes France Proceedings IEEE Importance : 4 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Sentinel-MSI
[Termes IGN] image SPOT 6
[Termes IGN] image SPOT 7
[Termes IGN] morphologie urbaine
[Termes IGN] série temporelle
[Termes IGN] zone urbaineRésumé : (auteur) This paper aims at detecting several urban morpho-type classes out of SPOT-6/7 imagery and Sentinel-2 time series. Urban classes of Urban Atlas are considered. The proposed strategy is a bottom-up one. It first detects basic urban objects (buildings, roads, vegetation), and use them to calculate multi-scale morphological features. These features are then fed to a Random Forest classifier trained from samples out of Urban Atlas urban classes. Obtained results is optionally merged with a Random Forest classification based on Sentinel-2 time series. Obtained results are promising. Numéro de notice : C2019-004 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : IMAGERIE/URBANISME Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/JURSE.2019.8808988 Date de publication en ligne : 22/08/2019 En ligne : https://doi.org/10.1109/JURSE.2019.8808988 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92209 Utilisation de données Sentinel-2 et SPOT 6/7 pour la classification de l’occupation du sol / Olivier Stocker (2019)
Titre : Utilisation de données Sentinel-2 et SPOT 6/7 pour la classification de l’occupation du sol Type de document : Mémoire Auteurs : Olivier Stocker, Auteur ; Arnaud Le Bris , Encadrant Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2019 Importance : 70 p. Note générale : bibliographie
Rapport de stage Mastère spécialisé Photogrammétrie, Positionnement, Mesure de DéformationsLangues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] fusion d'images
[Termes IGN] image Sentinel-MSI
[Termes IGN] image SPOT 6
[Termes IGN] image SPOT 7
[Termes IGN] segmentation sémantiqueRésumé : (auteur) Cette étude porte sur le développement d’une architecture entièrement convolutive, adaptée au traitement de l’information spatiale apportée par la très haute résolution des capteurs SPOT 6 et 7. Cette architecture s’est montrée plus performante que les approches par fenêtre glissante dans la précision de la détection des objets topographiques, même en zone dense. Parallèlement, ces travaux montrent que l’ajout de contraintes permet de mieux délimiter les objets et que la finesse de la vérité terrain joue un grand rôle dans cette capacité de délimitation. Cette nouvelle architecture a également permis de générer, à partir de produits existants, des cartes de couverture du sol d’une qualité prometteuse. Les différents niveaux de richesse de nomenclatures évalués ont mis en avant une capacité de constance dans la segmentation sémantique. Enfin, ces travaux ont servi d’étude préliminaire à la fusion tardive et précoce des données SPOT 6/7 et Sentinel 2, dans l’objectif d’ajouter à la richesse spatiale, déjà efficace, une dimension spectrale. L’ensemble des contraintes liées à l’implantation entièrement convolutive de la fusion et les modifications à appliquer sur notre architecture ont été listées. Note de contenu : Introduction
1- Classification de l'occupation du sol
2- Données et traitement
3- Algorithmique
4- Segmentation sémantique entièrement convolutive
5- Segmentation par fusion
ConclusionNuméro de notice : 17344 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Mémoire PPMD Organisme de stage : LaSTIG (IGN) DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98316 Documents numériques
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Utilisation de données Sentinel-2 et SPOT 6/7 ... - pdf auteurAdobe Acrobat PDF Variational learning of mixture wishart model for PolSAR image classification / Qian Wu in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)
[article]
Titre : Variational learning of mixture wishart model for PolSAR image classification Type de document : Article/Communication Auteurs : Qian Wu, Auteur ; Biao Hou, Auteur ; Zaidao Wen, Auteur ; Licheng Jiao, Auteur Année de publication : 2019 Article en page(s) : pp 141 - 154 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification
[Termes IGN] image AIRSAR
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] loi de Wishart
[Termes IGN] optimisation (mathématiques)
[Termes IGN] polarimétrie radarRésumé : (Auteur) The phase difference, amplitude product, and amplitude ratio between two polarizations are important discriminators for terrain classification, which derives a significant statistical-distribution-based polarimetric synthetic aperture radar (PolSAR) image classification. Traditionally, statistical-distribution-based PolSAR image classification models pay attention to two aspects: searching for a suitable distribution to model certain PolSAR image and a satisfactory solution for the corresponding distribution model with samples in every terrain. Usually, the described distribution form is too complicated to build. Besides, inaccurate parameter estimation may lead to poor classification performance for PolSAR image. In order to refrain from this phenomenon, a variational thought is adopted for the statistical-distribution-based PolSAR classification method in this paper. First, a mixture Wishart model is built to model the PolSAR image to replace the complicated distribution for the PolSAR image. Second, a learning-based method is suggested instead of inaccurate point estimation of parameters to determine the distribution for every class in the mixture Wishart model. Finally, the proposed learning-based mixture Wishart model will be built as a variational form to realize a parametric model for PolSAR image classification. In the experiments, it will be proved that the class centers are easier to distinguish among different terrains learned from the proposed variational model. In addition, a classification performance on the PolSAR image is superior to the original point estimation Wishart model on both visual classification result and accuracy. Numéro de notice : A2019-104 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2852633 Date de publication en ligne : 16/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2852633 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92410
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 1 (January 2019) . - pp 141 - 154[article]
Titre : Very High Resolution (VHR) satellite imagery : processing and applications Type de document : Monographie Auteurs : Francisco Eugenio, Éditeur scientifique ; Javier Marcello, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 262 p. ISBN/ISSN/EAN : 978-3-03921-757-1 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse texturale
[Termes IGN] détection du bâti
[Termes IGN] forêt alpestre
[Termes IGN] image à très haute résolution
[Termes IGN] image Pléiades
[Termes IGN] image Quickbird
[Termes IGN] image Worldview
[Termes IGN] risque naturel
[Termes IGN] traitement d'imageRésumé : (Editeur) Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing. Numéro de notice : 26310 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Numéro de périodique DOI : 10.3390/books978-3-03921-757-1 Date de publication en ligne : 09/12/2019 En ligne : https://doi.org/10.3390/books978-3-03921-757-1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95071 Atmospheric artifacts correction with a covariance-weighted linear model over mountainous regions / Zhongbo Hu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkAutomatic building rooftop extraction from aerial images via hierarchical RGB-D priors / Shibiao Xu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkLong-term land deformation monitoring using quasi-persistent scatterer (Q-PS) technique observed by sentinel-1A : case study Kelok Sembilan / Pakhrur Razi in Advances in Remote Sensing, vol 7 n° 4 (December 2018)PermalinkA new generation of the United States National Land Cover Database : Requirements, research priorities, design, and implementation strategies / Limin Yang in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)PermalinkPolarimetric radar vegetation index for biomass estimation in desert fringe ecosystems / Jisung Geba Chang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkPotential of Sentinel-1 data for monitoring temperate mixed forest phenology / Pierre-Louis Frison in Remote sensing, vol 10 n° 12 (December 2018)PermalinkScene classification based on multiscale convolutional neural network / Yanfei Liu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkSuper-resolution of Sentinel-2 images : Learning a globally applicable deep neural network / Charis Lanaras in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)PermalinkUrban impervious surface estimation from remote sensing and social data / Yan Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 12 (December 2018)PermalinkApplication of Landsat-8 and ASTER satellite remote sensing data for porphyry copper exploration: a case study from Shahr-e-Babak, Kerman, south of Iran / Morteza Safari in Geocarto international, vol 33 n° 11 (November 2018)PermalinkChange detection based on stacked generalization system with segmentation constraint / Kun Tan in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 11 (November 2018)PermalinkIndividual tree crown delineation in a highly diverse tropical forest using very high resolution satellite images / Fabien Hubert Wagner in ISPRS Journal of photogrammetry and remote sensing, vol 145 - part B (November 2018)PermalinkMulti-scale object detection in remote sensing imagery with convolutional neural networks / Zhipeng Deng in ISPRS Journal of photogrammetry and remote sensing, vol 145 - part A (November 2018)PermalinkPan-sharpening via deep metric learning / Yinghui Xing in ISPRS Journal of photogrammetry and remote sensing, vol 145 - part A (November 2018)PermalinkSemantic labeling in very high resolution images via a self-cascaded convolutional neural network / Yoncheng Liu in ISPRS Journal of photogrammetry and remote sensing, vol 145 - part A (November 2018)PermalinkA 3D convolutional neural network method for land cover classification using LiDAR and multi-temporal Landsat imagery / Zewei Xu in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)PermalinkCartographie des forêts humides dans la région d’El Kala (Algérie) à l’aide des outils d’observation de la Terre / Asma Kahli in Revue d'écologie, vol 73 n° 4 (octobre - décembre 2018)PermalinkEstimation of forest above-ground biomass by geographically weighted regression and machine learning with Sentinel imagery / Lin Chen in Forests, vol 9 n° 10 (October 2018)PermalinkMulti‐scale observations of atmospheric moisture variability in relation to heavy precipitating systems in the northwestern Mediterranean during HyMeX IOP12 / Samiro Khodayar in Quarterly Journal of the Royal Meteorological Society, vol 144 n° 717 (October 2018 Part B)PermalinkNovel fusion approach on automatic object extraction from spatial data: case study Worldview-2 and TOPO5000 / Umut Gunes Sefercik in Geocarto international, vol 33 n° 10 (October 2018)PermalinkObject-based crop classification using multi-temporal SPOT-5 imagery and textural features with a Random Forest classifier / Huanxue Zhang in Geocarto international, vol 33 n° 10 (October 2018)PermalinkPredicting tree diameter distributions from airborne laser scanning, SPOT 5 satellite, and field sample data in the perm region, Russia / Jussi Peuhkurinen in Forests, vol 9 n° 10 (October 2018)PermalinkStand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)PermalinkUnmixing polarimetric radar images based on land cover type identified by higher resolution optical data before target decomposition: application to forest and bare soil / Sébastien Giordano in IEEE Transactions on geoscience and remote sensing, vol 56 n° 10 (October 2018)PermalinkAssessment of Nigeriasat-1 satellite data for urban land use/land cover analysis using object-based image analysis in Abuja, Nigeria / Christopher Ifechukwude Chima in Geocarto international, vol 33 n° 9 (September 2018)PermalinkEffects of a large-scale late spring frost on a beech (Fagus sylvatica L.) dominated Mediterranean mountain forest derived from the spatio-temporal variations of NDVI / Angelo Nolè in Annals of Forest Science, vol 75 n° 3 (September 2018)PermalinkEstimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data / P. Kumar in Geocarto international, vol 33 n° 9 (September 2018)PermalinkImprovement of countrywide vegetation mapping over Japan and comparison to existing maps / Ram C. Sharma in Advances in Remote Sensing, vol 7 n° 3 (September 2018)PermalinkIntegration of ZY3-02 satellite laser altimetry data and stereo images for high-accuracy mapping / Guoyuan Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 9 (September 2018)PermalinkInvestigation of the success of monitoring slow motion landslides using Persistent Scatterer Interferometry and GNSS methods / K.O. Hastaoglu in Survey review, vol 50 n° 363 (September 2018)PermalinkSynergetic 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)PermalinkThe 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)PermalinkAn improved temporal mixture analysis unmixing method for estimating impervious surface area based on MODIS and DMSP-OLS data / Li Zhuo in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkComparison of high-density LiDAR and satellite photogrammetry for forest inventory / Grant D. Pearse in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkA generic remote sensing approach to derive operational essential biodiversity variables (EBVs) for conservation planning / Samuel Alleaume in Methods in ecology and evolution, vol 9 n° 8 (August 2018)PermalinkICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkIntra-annual phenology for detecting understory plant invasion in urban forests / Kunwar K. Singh in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkMapping ecosystem services at the regional scale: the validity of an upscaling approach / Solen Le Clec'h in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)PermalinkA method of downscaling temperature maps based on analytical hillshading for use in species distribution modelling / Ángel M. Felicísimo in Cartography and Geographic Information Science, Vol 45 n° 4 (July 2018)PermalinkMulti-scale assessment of invasive plant species diversity using Pléiades 1A, RapidEye and Landsat-8 data / Siddhartha Khare in Geocarto international, vol 33 n° 7 (July 2018)PermalinkSoil moisture estimation in Ferlo region (Senegal) using radar (ENVISAT/ASAR) and optical (SPOT/VEGETATION) data / Gayane Faye in The Egyptian Journal of Remote Sensing and Space Science, Vol. 21 suppl.1 (juillet 2018)PermalinkAssessment 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)PermalinkClassification à très large échelle d’images satellites à très haute résolution spatiale par réseaux de neurones convolutifs / Tristan Postadjian in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)PermalinkFusion tardive d’images SPOT 6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)PermalinkMapping rubber trees based on phenological analysis of Landsat time series data-sets / Janatul Aziera binti Abd Razak in Geocarto international, vol 33 n° 6 (June 2018)PermalinkModeling of inland flood vulnerability zones through remote sensing and GIS techniques in the highland region of Papua New Guinea / Porejane Harley in Applied geomatics, vol 10 n° 2 (June 2018)PermalinkSpatially sensitive statistical shape analysis for pedestrian recognition from LIDAR data / Michalis A. Savelonas in Computer Vision and image understanding, vol 171 (June 2018)PermalinkUncertainties in tree cover maps of Sub-Saharan Africa and their implications for measuring progress towards CBD Aichi Targets / Dorit Gross in Remote sensing in ecology and conservation, vol 4 n° 2 (June 2018)Permalink3D reconstruction from multi-view VHR-satellite images in MicMac / Ewelina Rupnik in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)PermalinkAn object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery / Luis Angel Ruiz in Geocarto international, vol 33 n° 5 (May 2018)PermalinkComparison of total water vapour content in the Arctic derived from GNSS, AIRS, MODIS and SCIAMACHY / Dunya Alraddawi in Atmospheric measurement techniques, vol 11 n° 5 (May 2018)PermalinkImproving the analysis of biogeochemical patterns associated with internal waves in the strait of Gibraltar using remote sensing images / Gabriel Navarro in Estuarine, Coastal and Shelf Science, vol 204 (May 2018)PermalinkA new scheme for urban impervious surface classification from SAR images / Hongsheng Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)PermalinkCartographie des défoliations du massif forestier du Pays des étangs en Lorraine : Apports potentiels de la télédétection / Thierry Bélouard in Revue forestière française, vol 70 n° 5 (2018)PermalinkGeneric rule-sets for automated detection of urban tree species from very high-resolution satellite data / Razieh Shojanoori in Geocarto international, vol 33 n° 4 (April 2018)PermalinkMapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data / Abel Chemura in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkTowards automatic SAR-optical stereogrammetry over urban areas using very high resolution imagery / Chunping Qiu in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkAccuracy assessment of different digital surface models / Ugur Alganci in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkActive tectonics of the onshore Hengchun Fault using UAS DSM combined with ALOS PS-InSAR time series (Southern Taiwan) / Benoit Deffontaines in Natural Hazards and Earth System Sciences, vol 18 n° 3 ([01/03/2018])PermalinkGenerative street addresses from satellite imagery / İlke Demir in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)PermalinkHarmonic regression of Landsat time series for modeling attributes from national forest inventory data / Barry T. Wilson in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)PermalinkMapping tree cover with Sentinel-2 data using the Support Vector Machine (SVM) / Anna Mirończuk in Geoinformation issues, Vol 9 n° 1 (2017)PermalinkRemote estimation of canopy leaf area index and chlorophyll content in Moso bamboo (Phyllostachys edulis (Carrière) J. Houz.) forest using MODIS reflectance data / Xiaojun Xu in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkSensitivity analysis of pansharpening in hyperspectral change detection / Seyd Teymoor Seydi in Applied geomatics, vol 10 n° 1 (March 2018)PermalinkUnderstanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery / Pablo J. Zarco-Tejada in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)PermalinkAnalyse de l'incertitude et de la précision thématique de classifications GEOBIA d'une image WorldView-2 / François Messner in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)PermalinkEstimating forest standing biomass in savanna woodlands as an indicator of forest productivity using the new generation WorldView-2 sensor / Timothy Dube in Geocarto international, vol 33 n° 2 (February 2018)PermalinkEstimation of forest aboveground biomass from HJ1B imagery using a canopy reflectance model and a forest growth model / Xinyun Wang in Geocarto international, vol 33 n° 2 (February 2018)PermalinkNouvelle méthode en cascade pour la classification hiérarchique multi-temporelle ou multi-capteur d'images satellitaires haute résolution / Ihsen Hedhli in Revue Française de Photogrammétrie et de Télédétection, n° 216 (février 2018)PermalinkAdapting an existing semi-automatized image processing chain to enable Sentinel-2 data classification. / Hiyam Elbadri (2018)PermalinkPermalinkAutomated delineation of wildfire areas using Sentinel-2 satellite imagery / Mira Weirather in GI Forum, vol 2018 n° 1 ([01/01/2018])PermalinkCartographie des déformations de surface sur l’île de Taiwan par interférométrie RADAR Sentinel-1 / Miloud Fekaouni (2018)PermalinkCartographier l'occupation du sol à grande échelle : optimisation de la photo-interprétation par segmentation d'image / Maxime Vitter (2018)PermalinkPermalinkClassification à très haute résolution (THR) spatiale et fusion d'occupation des sols (OCS) / Tristan Postadjian (2018)PermalinkClassification à très large échelle d'images satellite à très haute résolution spatiale par réseaux de neurones convolutifs / Tristan Postadjian (2018)PermalinkA comparative analysis of the NDVIg and NDVI3g in monitoring vegetation phenology changes in the Northern Hemisphere / Qing Chang in Geocarto international, vol 33 n° 1 (January 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)PermalinkContribution actuelle de la calotte Antarctique à la variation du niveau marin / Clémence Chupin (2018)PermalinkCrop-rotation structured classification using multi-source sentinel images and LPIS for crop type mapping / Simon Bailly (2018)PermalinkDecision fusion of SPOT6 and multitemporal Sentinel2 images for urban area detection / Cyril Wendl (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)PermalinkEvaluation des performances des modèles numérique d’élévation issus de l’imagerie tri-stéréo Pléiades pour le suivi de l’évolution morphologique des dunes littorales / Mannaïg L'haridon (2018)PermalinkExploring image fusion of ALOS/PALSAR data and LANDSAT data to differentiate forest area / Saygin Abdikan in Geocarto international, vol 33 n° 1 (January 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)PermalinkPermalinkFusion tardive d’images SPOT-6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl (2018)PermalinkGeometric multi-wavelet total variation for SAR image time series analysis / Abdourrahmane M. Atto (2018)PermalinkA hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning / Rasmus M. Houborg in ISPRS Journal of photogrammetry and remote sensing, vol 135 (January 2018)PermalinkUn inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa-Pillai-Vijayakumar (2018)PermalinkLearning multiscale deep features for high-resolution satellite image scene classification / Qingshan Liu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkMapping grassland management intensity using Sentinel-2 satellite data / Marijke Elisabeth Bekkema in GI Forum, vol 2018 n° 1 ([01/01/2018])Permalink