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Monitoring suspended particle matter using GOCI satellite data after the Tohoku (Japan) tsunami in 2011 / Audrey Minghelli in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol 12 n° 2 (February 2019)
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Titre : Monitoring suspended particle matter using GOCI satellite data after the Tohoku (Japan) tsunami in 2011 Type de document : Article/Communication Auteurs : Audrey Minghelli, Auteur ; Manchun Lei , Auteur ; Sabine Charmasson, Auteur ; Vincent Rey, Auteur ; Malik Chami, Auteur
Année de publication : 2019 Projets : AMORAD / Radakovitch, Olivier Article en page(s) : pp 567 - 576 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] détection de changement
[Termes IGN] image COMS-GOCI
[Termes IGN] Japon
[Termes IGN] particule
[Termes IGN] risque naturel
[Termes IGN] risque technologique
[Termes IGN] séisme
[Termes IGN] Sendaï
[Termes IGN] surveillance géologique
[Termes IGN] Tohoku (Japon)
[Termes IGN] tsunamiRésumé : (auteur) The Fukushima Daiichi nuclear disaster that occurred on March 11, 2011, was caused by the To̅hoku tsunami, which was itself triggered by the devastating 9.0 Mw moment magnitude earthquake. This study investigates spatial and temporal changes of the suspended particulate matter (SPM) content in the North-Eastern part of Japan (Pacific Ocean) using a geostationary ocean color sensor. The Geostationary Ocean Color Imager (GOCI), which is centered on the Korean peninsula but could also observe the Japanese area, is able to acquire eight images per day, thus allowing the analysis of rapid daily changes in water mass. The analysis of GOCI data shows that SPM concentration notably increased both along the coast and within the Bay of Sendaï shortly after the tsunami. Motionless patterns of SPM were observed at 2, 14, 25, and 37 km from the coast. It is shown that SPM concentration rapidly decreased one month later. The SPM concentration did not remain high the following year, contrary to what was observed for the Sumatra Tsunami in 2004. The origin of SPM is also investigated in this study. Our analysis suggests that some of the SPM originates from the resuspension of bottom sediments due to the reflection of the tsunami on the coastline that leads to the migration of marine particles toward the sea surface. The fate of the SPM concentration is then discussed based on the analysis of meteorological conditions, river discharge, and tsunami wave properties. Numéro de notice : A2019-628 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/JSTARS.2019.2894063 Date de publication en ligne : 22/02/2019 En ligne : https://doi.org/10.1109/JSTARS.2019.2894063 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95365
in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing > vol 12 n° 2 (February 2019) . - pp 567 - 576[article]Near real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors / Pauline Perbet in International Journal of Remote Sensing IJRS, vol 40 n°19 (February 2019)
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Titre : Near real-time deforestation detection in Malaysia and Indonesia using change vector analysis with three sensors Type de document : Article/Communication Auteurs : Pauline Perbet, Auteur ; Michelle Fortin, Auteur ; Anouk Ville, Auteur ; Martin Béland, Auteur Année de publication : 2019 Projets : 1-Pas de projet / Radakovitch, Olivier Article en page(s) : pp 7439 - 7458 Note générale : bibliographie
This work was supported by the Natural Sciences and Engineering Research Council of Canada.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse vectorielle
[Termes IGN] déboisement
[Termes IGN] défrichement
[Termes IGN] détection de changement
[Termes IGN] forêt tropicale
[Termes IGN] image captée par drone
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] Indonésie
[Termes IGN] Malaisie
[Termes IGN] surveillance forestièreRésumé : (auteur) Malaysia and Indonesia have been affected by deforestation caused in great part by the proliferation of oil palm plantations. To survey this loss of forest, several studies have monitored these southeast Asian nations with satellite remote sensing alert systems. The methods used have shown potential for this approach, but they are limited by imagery with coarse spatial resolution, low revisit times, and cloud cover. The objective of this research is to improve near real-time operational deforestation detection by combining three sensors: Sentinel-1, Sentinel-2 and Landsat-8. We used Change Vector Analysis to detect changes between non-affected forest and images under analysis. The results were validated using 166 plots of undisturbed forest and confirmed deforestation events throughout Sabah Malaysian State, and from 70 points from drone pictures in Sumatra, Indonesia. Sentinel-2 and Landsat-8 yielded sufficient results in terms of accuracy (less than 11% of commission and omission error). Sentinel-1 had lower accuracy (14% of commission error and 28% of omission error), probably resulting from geometric distortions and speckle noise. During the high cloud-cover season optical sensors took about twice the time to detect deforestation compared to Sentinel-1 which was not affected by cloud cover. By combining the three sensors, we detected deforestations about 8 days after forest clearing events. Deforestations were only detectable during approximately the first 100 days, before bare soils were often coved by legume crop. Our results indicate that near real-time deforestation detection can reveal most events, but the number of false detections could be improved using a multiple event detection process. Numéro de notice : A2019-321 Affiliation des auteurs : ENSG+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2019.1579390 Date de publication en ligne : 17/02/2019 En ligne : https://doi.org/10.1080/01431161.2019.1579390 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93295
in International Journal of Remote Sensing IJRS > vol 40 n°19 (February 2019) . - pp 7439 - 7458[article]
Titre : 3D remote sensing applications in forest ecology : Composition, structure and function Type de document : Monographie Auteurs : Hooman Latifi, Éditeur scientifique ; Rubén Valbuena, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 188 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-03921-782-3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spatio-temporelle
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données TLS (télémétrie)
[Termes IGN] écologie forestière
[Termes IGN] fusion de données
[Termes IGN] hauteur des arbres
[Termes IGN] image multibande
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] structure d'un peuplement forestierRésumé : (auteur) The composition, structure and function of forest ecosystems are the key features characterizing their ecological properties, and can thus be crucially shaped and changed by various biotic and abiotic factors on multiple spatial scales. The magnitude and extent of these changes in recent decades calls for enhanced mitigation and adaption measures. Remote sensing data and methods are the main complementary sources of up-to-date synoptic and objective information of forest ecology. Due to the inherent 3D nature of forest ecosystems, the analysis of 3D sources of remote sensing data is considered to be most appropriate for recreating the forest's compositional, structural and functional dynamics. In this Special Issue of Forests, we published a set of state-of-the-art scientific works including experimental studies, methodological developments and model validations, all dealing with the general topic of 3D remote sensing-assisted applications in forest ecology. We showed applications in forest ecology from a broad collection of method and sensor combinations, including fusion schemes. All in all, the studies and their focuses are as broad as a forest's ecology or the field of remote sensing and, thus, reflect the very diverse usages and directions toward which future research and practice will be directed. Note de contenu : 1- Current trends in forest ecological applications of three-dimensional remote sensing: transition from experimental to operational solutions?
2- Improving estimation accuracy of growing stock by multi-frequency SAR and multi-spectral data over Iran’s heterogeneously-structured broadleaf hyrcanian forests
3- Fractional cover mapping of invasive plant species by combining very high-resolution stereo and multi-sensor multispectral imageries
4- Relationships between satellite-based spectral burned ratios and terrestrial laser scanning
5- Mapping maximum tree height of the Great Khingan Mountain, inner Mongolia Using the
allometric scaling and resource limitations model
6- Can field crews telecommute? varied data quality from citizen science tree inventories conducted using street-level imagery
7- Do high-voltage power transmission lines affect forest landscape and vegetation growth: evidence from a case for Southeastern of China
8- Mapping forest canopy height in mountainous areas using ZiYuan-3 stereo images and
Landsat data
9- Application of terrestrial laser scanner to evaluate the influence of root collar geometry on stump height after mechanized forest operations
10- Sensitivity of codispersion to noise and error in ecological and environmental data
11- Estimating individual tree height and diameter at breast height (DBH) from terrestrial laser scanning (TLS) data at plot levelNuméro de notice : 25931 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Monographie En ligne : https://doi.org/10.3390/books978-3-03921-783-0 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96212 Advanced Remote Sensing Technology for Synthetic Aperture Radar Applications, Tsunami Disasters, and Infrastructure / Maged Marghany (2019)
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Titre : Advanced Remote Sensing Technology for Synthetic Aperture Radar Applications, Tsunami Disasters, and Infrastructure Type de document : Monographie Auteurs : Maged Marghany, Éditeur scientifique Editeur : Rijeka [Croatie] : InTech Année de publication : 2019 ISBN/ISSN/EAN : 978-1-78985-618-7 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage profond
[Termes IGN] cartographie des risques
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] géologie
[Termes IGN] géophysique
[Termes IGN] image 3D
[Termes IGN] image captée par drone
[Termes IGN] image radar moirée
[Termes IGN] image satellite
[Termes IGN] interférométrie
[Termes IGN] surveillance du littoral
[Termes IGN] tsunamiRésumé : (éditeur) The advance in space machineries has created a novel technology for observing and monitoring the Earth from space. Most earth observation remote sensing considerations focus on using conventional image processing algorithms or classic edge detection tools. Nevertheless, these techniques do not implement modern physics, applied mathematics, signal communication, remote sensing data, and innovative space technologies. This book provides readers with methods to comprehend how to monitor coastal environments, disaster areas, and infrastructure from space with advanced talent remote sensing technology to bridge the gaps between modern space technology, image processing algorithms, mathematical models and the critical issue of the coastal and infrastructure investigations. Note de contenu : 1- Advanced Ocean Current Simulation from TanDEM Satellite Data
2- On Feature-Based SAR Image Registration: Appropriate Feature and Retrieval Algorithm
3- L-Band SAR Disaster Monitoring for Harbor Facilities Using Interferometric Analysis
4- Utilization of Deep Convolutional Neural Networks for Remote Sensing Scenes Classification
5- Sub-Pixel Technique for Time Series Analysis of Shoreline Changes Based on Multispectral Satellite Imagery
6- Utilization of Dynamic and Static Sensors for Monitoring Infrastructures
7- Geo Spatial Analysis for Tsunami Risk Mapping
8- Utilization of Unmanned Aerial Vehicle for Accurate 3D ImagingNuméro de notice : 25814 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.5772/intechopen.78525 En ligne : https://www.intechopen.com/books/advanced-remote-sensing-technology-for-syntheti [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95077
Titre : Advances in environmental monitoring and assessment Type de document : Monographie Auteurs : Suriyanarayanan Sarvajayakesavalu, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2019 Importance : 108 p. Format : 19 x 27 cm ISBN/ISSN/EAN : 978-1-83881-010-8 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] algue
[Termes IGN] apprentissage automatique
[Termes IGN] capteur spatial
[Termes IGN] changement climatique
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MISR
[Termes IGN] mangrove
[Termes IGN] phénomène climatique extrême
[Termes IGN] plancton
[Termes IGN] stress hydrique
[Termes IGN] surveillance de la végétationRésumé : (éditeur) The book Advances in Environmental Monitoring and Assessment is a collection of the latest research techniques on environmental monitoring and assessments. I believe that the information contained in this book will enhance the skills of environmental scientists and decision makers and contribute to the exchange of best practices for developing and implementing optimum methods for environmental assessment and management. Note de contenu : 1- Hydrological stress and climate change impact in arid regions with agricultural valleys in Northern Mexico
2- Evaluation of water quality indices: Use, evolution and future perspectives
3- A survey of satellite biological sensor application for terrestrial and aquatic ecosystems
4- Atmospheric aerosols monitoring: Ground and satellite-based instruments
5- Extreme value analysis and risk communication for a changing climateNuméro de notice : 25963 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.75847 En ligne : https://doi.org/10.5772/intechopen.75847 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96540 Ailanthus altissima mapping from multi-temporal very high resolution satellite images / Cristina Tarantino in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)
PermalinkAnalysis and modelling of remote sensing reflectance during anoxic crisis in the Thau lagoon using satellite images / Manchun Lei (2019)
PermalinkApport des mesures du radar à synthèse d'ouverture de Sentinel-1 pour l'étude des propriétés du manteau neigeux / Gaëlle Veyssière (2019)
PermalinkApports de l'imagerie satellitaire pour caractériser les évolutions morphologiques de l'embouchure du Tage / Anne Jaouen (2019)
PermalinkAssessment of different vegetation parameters for parameterizing the coupled water cloud model and advanced integral equation model for soil moisture retrieval using time series Sentinel-1A data / Long Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)
PermalinkPermalinkCaractérisation des déplacements liés aux coulées de lave au Piton de la Fournaise à partir de données InSAR / Alexis Hrysiewicz (2019)
PermalinkClimate variability and climate change impacts on land surface, hydrological processes and water management / Yongqiang Zhang (2019)
PermalinkConstruction of bulk temperature/salinity from surface temperature and atlas profiles for monitoring water volume variations in the Caspian Sea / Ayoub Moradi (2019)
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