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Beach morphology and its dynamism from remote sensing for coastal management support / Carlos Cabezas Rabadán (2021)
Titre : Beach morphology and its dynamism from remote sensing for coastal management support Type de document : Thèse/HDR Auteurs : Carlos Cabezas Rabadán, Auteur ; Josep E. Pardo Pascual, Directeur de thèse ; Miguel Rodilla Alamá, Directeur de thèse Editeur : Valencia : Universitat politécnica de Valencia Année de publication : 2021 Importance : 188 p. Format : 21 x 30 cm Note générale : bibliographie
Thesis dissertation submitted in fulfillment of the requirements for the Degree of Doctor of Philosophy at Universitat Politècnica de ValènciaLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] détection de changement
[Termes IGN] érosion côtière
[Termes IGN] géomorphologie
[Termes IGN] image Landsat
[Termes IGN] image Sentinel-MSI
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] plage
[Termes IGN] sédiment
[Termes IGN] surveillance du littoral
[Termes IGN] trait de côteRésumé : (auteur) Beaches are coastal spaces that perform numerous environmental functions. They provide important benefits to society and coastal communities, including the ecological function, the provision of protection for coastal territories, and constitute a basic resource for the tourism industry. Due to climate change and human actions that alter the natural dynamism of the coast, beaches are experiencing increasingly harmful erosive processes that affect their physical integrity and the maintenance of their ecological functions. Beach management is often not adapted to the particularities of the different coastal segments. Decision-making is not based on sufficient information about characteristics, dynamism, and current state of beaches, resulting in short or ineffective solutions. Geomorphological characteristics are essential in the development of beach functions as they condition their physical dimensions and their behavior in response to the action of the sea. Therefore, their detailed and updated characterization is necessary to carry out efficient actions, allowing a more ecosystemic and sustainable coastal management. Remote sensing techniques have a great capacity for acquiring data from the land surface. In particular, Sentinel-2 and Landsat (5, 7, and 8) satellites freely provide medium resolution images with global coverage and high-revisit frequency. The algorithms for extracting the water/land interface recently developed by the Geo-Environmental Cartography and Remote Sensing Group (CGAT – UPV) allow defining the position of the shoreline on these images, constituting potentially useful data to describe beach morphology and dynamics. Universalizing their application requires testing and validation at different coastal types. For this purpose, the extraction process has been adapted for exploitation in tidal environments, and the resulting shorelines have been assessed under different oceanographic conditions offering an accuracy close to 5 m RMSE (Root-Mean-Square Error). From these shorelines, and taking into account the existing information needs for management, it is proposed to derive indicators to characterize the geomorphology of the beaches and to monitor their changes. To this end, the proposed methodologies ensure the efficient management of large volumes of shorelines, being able to characterize the beaches along broad coastal segments and periods. Thus, beach width and sediment grain size are derived as objective and easily understandable indicators of the beach geomorphology. Spatial-temporal modeling of the state and changes of shoreline position and beach width makes it possible to monitor the response to storms and anthropogenic actions, allowing to analyze changes that occur every few days or over decades. The large spatial coverage together with the integration with other cartographic databases allows characterizing the influence of beach geomorphology in the performance of its functions, offering a holistic view of the coast from a regional scale. The methodologies developed in this thesis and the indicators derived from remote sensing provide support and criteria for prioritizing the actions of managers. This contributes to fill the gap between the availability of techniques to obtain remote information and its application in the coastal decision-making process. Note de contenu : 1- General introduction
2- Assessing user’s expectations and perceptions on different beach types and the need for diverse management frameworks
3- Satellite-derived shorelines at an exposed mesotidal beach
4- Characterizing beach changes using satellite-derived shorelines
5- Detecting problematic beach widths for the recreational function from subpixel shoreline
6- Shoreline variability from Sentinel-2: an approach for estimating beach sediment size?
7- Conclusions, management implications and future perspectivesNuméro de notice : 28599 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Thesis : Geomatics : Valencia, Spain : 2021 DOI : 10.4995/Thesis/10251/165076 En ligne : https://doi.org/10.4995/Thesis/10251/165076 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99405 Benchmarking of convolutional neural network approaches for vegetation land cover mapping / Benjamin Carpentier (2021)
Titre : Benchmarking of convolutional neural network approaches for vegetation land cover mapping Type de document : Article/Communication Auteurs : Benjamin Carpentier, Auteur ; Antoine Masse , Auteur ; Emeric Lavergne, Auteur ; C. Sannier, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2021 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B2-2021 Conférence : ISPRS 2021, Commission 2, XXIV ISPRS Congress, Imaging today foreseeing tomorrow 05/07/2021 09/07/2021 Nice Virtuel France OA Archives Commission 2 Importance : pp 915 - 922 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] image Sentinel-MSI
[Termes IGN] série temporelleRésumé : (auteur) Satellite Image Time Series (SITS) are becoming available at high spatial, spectral and temporal resolutions across the globe by the latest remote sensing sensors. These series of images can be highly valuable when exploited by classification systems to produce frequently updated and accurate land cover maps. The richness of spectral, spatial and temporal features in SITS is a promising source of data for developing better classification algorithms. However, machine learning methods such as Random Forests (RF), despite their fruitful application to SITS to produce land cover maps, are structurally unable to properly handle intertwined spatial, spectral and temporal dynamics without breaking the structure of the data. Therefore, the present work proposes a comparative study of various deep learning algorithms from the Convolutional Neural Network (CNN) family and evaluate their performance on SITS classification. They are compared to the processing chain coined iota2, developed by the CESBIO and based on a RF model. Experiments are carried out in an operational context using with sparse annotations from 290 labeled polygons. Less than 80 000 pixel time series belonging to 8 land cover classes from a year of Sentinel-2 monthly syntheses are used. Results show on a test set of 131 polygons that CNNs using 3D convolutions in space and time are more accurate than 1D temporal, stacked 2D and RF approaches. Best-performing models are CNNs using spatio-temporal features, namely 3D-CNN, 2D-CNN and SpatioTempCNN, a two-stream model using both 1D and 3D convolutions. Numéro de notice : C2021-017 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Communication DOI : 10.5194/isprs-archives-XLIII-B2-2021-915-2021 Date de publication en ligne : 28/06/2021 En ligne : https://doi.org/10.5194/isprs-archives-XLIII-B2-2021-915-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98069 Centrality and city size effects on NO2 ground and tropospheric concentrations within European cities / Yufei Wei (2021)
contenu dans European Colloquium on Theoretical and Quantitative Geography 2021, Manchester, 3-5 November 2021 / Nuno Pinto (2021)
Titre : Centrality and city size effects on NO2 ground and tropospheric concentrations within European cities Type de document : Article/Communication Auteurs : Yufei Wei, Auteur ; Geoffrey Caruso, Auteur ; Rémi Lemoy, Auteur Editeur : Manchester [Royaume-Uni] : Manchester University Press Année de publication : 2021 Conférence : ECTQG 2021, 22nd European Colloquium on Theoretical and Quantitative Geography 03/11/2021 05/11/2021 Manchester Royaume-Uni Open Access Abstracts Importance : pp 396 - 400 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] centre urbain
[Termes IGN] dioxyde d'azote
[Termes IGN] Europe (géographie politique)
[Termes IGN] image Sentinel-5P-TROPOMI
[Termes IGN] pollution atmosphérique
[Termes IGN] villeNuméro de notice : C2021-078 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Communication DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100065 Documents numériques
en open access
Centrality and city size effects ... - pdf éditeurAdobe Acrobat PDF Change detection of land use and land cover, using landsat-8 and sentinel-2A images / Mohammed Abdulmohsen Alhedyan (2021)
Titre : Change detection of land use and land cover, using landsat-8 and sentinel-2A images Type de document : Thèse/HDR Auteurs : Mohammed Abdulmohsen Alhedyan, Auteur Editeur : Leicester [Royaume-Uni] : University of Leicester Année de publication : 2021 Importance : 228 p. Format : 21 x 30 cm Note générale : bibliographie
Thesis submitted for the degree of PhD at the University of LeicesterLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse vectorielle
[Termes IGN] Arabie Saoudite
[Termes IGN] Corine (base de données)
[Termes IGN] détection de changement
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] occupation du sol
[Termes IGN] Royaume-Uni
[Termes IGN] utilisation du solRésumé : (auteur) The main theme of this research is the development of a new hybrid method for change detection of land use and land cover (LULC). LULC change detection is one of most widely used applications of remote sensing. This study used data from two different optical sensors, Landsat-8 images and Sentinel-2A images. Given the newly developed capabilities of these remote sensing satellites, it was necessary to devise appropriate techniques to realise the benefits that they offer. Therefore, three effective change detection methods have been tested, comprehensively analysed, and used to inform the design and development of a new hybrid method of change detection. The studied change detection methods were change vector analysis (CVA), multi-index integrated change analysis (MIICA), and the comprehensive change detection method (CCDM). Case studies were conducted in two regions, Bristol (United Kingdom) and Hail (Saudi Arabia), to provide sufficient variety of inputs to enable the response of more LULC varieties to be recorded. Finally, the Coordination of Information on the Environment (Corine) land cover scheme was used to identify land cover types and LULC changes. In the study area of Bristol, the new hybrid change detection method achieved an overall accuracy of 90% and 0.81 kappa, while the results for the study area of Hail were 74% overall accuracy and 0.40 kappa. The change detection results obtained by the new hybrid method constitute a significant improvement over the implementation of the existing CVA, MIICA and CCDM methods at the two study areas while using Landsat-8 and Sentinel-2A images. Note de contenu : 1- Introduction
2- Literature review
3- Classification system, study areas, data sources and data preparation process
4- Evaluation of existing change detection
5- The hybrid change detection method
6- Discussion
7- ConclusionNuméro de notice : 28466 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD thesis : Leicester : Geography, Geology, and Environment : 2021 DOI : 10.25392/leicester.data.16988440.v1 En ligne : https://doi.org/10.25392/leicester.data.16988440.v1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99094 Characterization of mass variations in Antarctica in response to climatic fluctuations from space-based gravimetry and radar altimetry data / Athul Kaitheri (2021)
Titre : Characterization of mass variations in Antarctica in response to climatic fluctuations from space-based gravimetry and radar altimetry data Titre original : Caractérisation des variations de masse en Antarctique en réponse aux fluctuations climatiques à partir des données de gravimétrie spatiale et d’altimétrie radar Type de document : Thèse/HDR Auteurs : Athul Kaitheri, Auteur ; Anthony Mémin, Directeur de thèse ; Frédérique Rémy, Directeur de thèse Editeur : Nice : Université Côte d'Azur Année de publication : 2021 Importance : 138 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse présentée en vue de l’obtention du grade de docteur de l'Université de Côte d'Azur, Spécialité Sciences de la Planète et de l'UniversLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] altimétrie satellitaire par radar
[Termes IGN] analyse comparative
[Termes IGN] Antarctique
[Termes IGN] calotte glaciaire
[Termes IGN] changement climatique
[Termes IGN] données altimétriques
[Termes IGN] données GRACE
[Termes IGN] image Envisat
[Termes IGN] levé gravimétrique
[Termes IGN] masse
[Termes IGN] oscillation
[Termes IGN] régressionIndex. décimale : THESE Thèses et HDR Résumé : (Auteur) Quantifying the mass balance of the Antarctic Ice Sheet (AIS), and the resulting sea level rise, requires an understanding of inter-annual variability and associated causal mechanisms. This has become more complex and challenging in the backdrop of global climate change. Very few studies have been exploring the influence of climate anomalies on the AIS and only a vague estimate of its impact is available. Usually changes to the ice sheet are quantified using observations from space-borne altimetry and gravimetry missions. In this study, we use data from Envisat (2002 to 2010) and Gravity Recovery and Climate Experiment (GRACE) (2002 to 2016) missions to estimate monthly elevation changes and mass changes, respectively. Similar estimates of the changes are made using weather variables (surface mass balance (SMB) and temperature) from a regional climate model (RACMO2.3p2) as inputs to a firn compaction (FC) model. Using the firn compaction model we were able to model the transformation of snow into glacial ice and hence estimate changes in the elevation of the ice sheet using climate parameters. Elevation changes estimated from different techniques are in good agreement with each other across the AIS especially in West Antarctica, Antarctic Peninsula, and along the coasts of East Antarctica. Inter-annual height change patterns are then extracted using for the first time an empirical mode decomposition followed by a reconstruction of modes. These signal on applying least square method revealed a sub-4-year periodic signal in the all the three distinct height change patterns. This was indicative of the influence of the El Niño Southern Oscillation (ENSO), a climate anomaly that alters, among other parameters, moisture transport, sea surface temperature, precipitation, in and around the AIS at similar frequency by alternating between warm and cold conditions. But there existed altering periodic behavior among inter annual height change patterns in the Antarctic Pacific (AP) sector which was found possibly by the influence of multiple climate drivers, like the Amundsen Sea Low (ASL) and the Southern Annular Mode (SAM). A combined analysis of the three distinct estimates using a PCA (principal component analysis) along the coast revealed similar findings. Height change anomaly also appears to traverse eastwards from Coats Land to Pine Island Glacier (PIG) regions passing through Dronning Maud Land (DML) and Wilkes Land (WL) in 6 to 8 years. This is indicative of climate anomaly traversal due to the Antarctic Circumpolar Wave (ACW) which propagates anomalies through the Southern Ocean in 8 to 10 years. Altogether, inter-annual variability in the SMB of the AIS is found to be modulated by multiple competing climate anomalies. Note de contenu : 1. Introduction
1.1 Climate change scenario
1.2 Antarctica
1.3 Thesis overview
2. Height changes from satellite observations
2.1 Observations
2.2 Satellite gravimetry
2.3 Satellite altimetry
3. Height changes from modelling
3.1 Climate Model
3.2 Height changes from RACMO2.3p2 outputs
3.3 Firn densification model
4. Inter-annual variability
4.1 Comparison between height changes
4.2 Extraction of inter annual signals
4.3 Characterizing inter-annual signals
4.4 Principal component analysis
5. Influence of climate anomalies
5.1 El Ni˜no Southern Oscillation
5.2 Southern Annular Mode
5.3 Amundsen Sea Low
5.4 Antarctic Circumpolar Wave
6. General conclusions
6.1 Conclusions
6.2 Future perspectivesNuméro de notice : 26825 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Thèse française Note de thèse : Thèse de doctorat : Sciences de la Planète et de l'Univers : Côte d'Azur : 2021 Organisme de stage : Géoazur nature-HAL : Thèse DOI : sans Date de publication en ligne : 19/04/2022 En ligne : https://tel.hal.science/tel-03644306/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100655 PermalinkPermalinkPermalinkPermalinkDeep learning for wildfire progression monitoring using SAR and optical satellite image time series / Puzhao Zhang (2021)PermalinkDétection de changement d’occupation du sol à l’aide de données Sentinel en contexte tropical / Lucas Martelet (2021)PermalinkDéterminants de la composition floristique et estimations des stocks de carbone des peuplements forestiers matures de Uma (Tshopo, RDC) / John Katembo Mukirania (2021)PermalinkDiurnal cycles of C-band temporal coherence and backscattering coefficient over an olive orchard in a semi-arid area: Comparison of in situ and Sentinel-1 radar observations / Adnane Chakir (2021)PermalinkDiurnal cycles of C-band temporal coherence and backscattering coefficient over a wheat field in a semi-arid area / Nadia Ouaadi (2021)PermalinkDynamics of inundation events in the rivers-estuaries-ocean continuum in Bengal delta : synergy between hydrodynamic modelling and spaceborne remote sensing / Md Jamal Uddin Kahn (2021)Permalink