Centre de documentation
scientifique

Flood mapping from radar remote sensing using automated image classification techniques / Lisa Landuyt (2021)  

Public Titre : Flood mapping from radar remote sensing using automated image classification techniques Type de document : Thèse/HDR Auteurs : Lisa Landuyt, Auteur ; Niko Verhoest, Directeur de thèse ; Frieke Vancoillie, Directeur de thèse Editeur : Gand [Belgique] : Universiteit Gent Année de publication : 2021 Importance : 227 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-94-6357-415-0 Note générale : bibliographie Dissertation submitted in fulfillment of the requirements for the degree of Doctor (PhD) of Bioscience Engineering Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse d'image orientée objet [Termes IGN] bande C [Termes IGN] cartographie des risques [Termes IGN] détection de changement [Termes IGN] extraction de la végétation [Termes IGN] Flandre (Belgique) [Termes IGN] gestion de l'eau [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] inondation [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] modèle de simulation [Termes IGN] surveillance hydrologique Résumé : (auteur) Floods are a hazard of major concern, causing substantial fatalities and eco-nomic losses. These losses are expected to further accumulate in the future, as both the frequency and magnitude of flood events are projected to increase dueto climate change. Insights into the occurrence and dynamics of these disastrous events are thus of paramount importance for the protection of livelihoods across the world, both in the near and far future.Synthetic Aperture Radar (SAR) satellite imagery is particularly suited to observe floods due to the synoptic view, low cost and timely availability ofsatellite imagery and the all-weather imaging capabilities of SAR sensors. The resulting observations are crucial for various purposes, including emergency relief, post-disaster damage assessment, the calibration and validation of floodprediction models, and risk assessment.Despite the clear advantages of SAR imagery, several factors complicate the flood extent retrieval from this imagery type. These include surfaces or land dynamics characterized by a SAR backscatter similar to that of water/flooding,as well as the presence of urban features and vegetation. Moreover, existing approaches often lack the robustness and automation necessary for operational purposes. This thesis aims to contribute to the accuracy and automation of SAR-based flood mapping approaches, by elaborating on several of theremaining challenges. More specifically, the objectives of this thesis are: 1.to investigate the state of the art in SAR-based flood mapping andidentify the strengths and limitations of existing methods, as well as possible trends; 2.to assess the potential of C-band SAR for the delineation of floodedvegetation, and suggested an approach for doing so in an automated way; 3.to identify the main obstacles with respect to automated flood monitoring,and develop an approach that allows putting science into practice. In the process of pursuing these objectives, special attention is given to automation, as this is key for objective and timely observations, and to optimally employing available data, as additional data can substantially improve flood observations but not handling these critically may be have adverse effects. Additionally, the potential of object-based image analysis (OBIA) techniques is investigated, as they have proven their added value using optical imagery but SAR-based applications remain limited. Sentinel-1imagery is the main datasource considered in this thesis, as this medium-resolution C-band imagery is freely available and provides consistent global coverage.First, the state of the art in SAR-based flood mapping is investigated. Distin-guishing between approaches for the retrieval of open water, flooded vegetationand urban flooding, deployed input data and classification techniques are discussed. As it is difficult to draw conclusions regarding the strengths and limitations of these classification techniques based on their scientific publications, an in-depth assessment and comparison of a selection of these is carried out. This selection includes thresholding, active contour modeling and theHSBA-Flood method, and both single scene and change detection-based maps are generated. To tackle the second objective of this thesis, the detectability of both woody and herbaceous vegetation using Sentinel-1 is investigated. Moreover, an automated, object-based clustering approach, making use of globally and freely available data only, is presented and applied on four study areas with varying characteristics. The resulting flood maps discriminate between dryland, permanent water, open flooding and flooded vegetation. Forests are indicated too, in order to underline the uncertainty related to these areas where flooding cannot or only to a limited extent be detected.In the last part of this thesis, an approach for operational flood monitoringin Flanders is presented. This approach was developed for and with input of the local water manager,i.e.the Flanders Environment Agency, and makesuse of high-resolution ancillary data available for the region of interest. By combining a pixel-based and an object-based approach, a discrimination is made between dry land, permanent water, open flooding, probable flooding, flooded vegetation and probably flooded forests. The approach is extensively tested on flood events of different sizes that occurred between 2016 and 2020. Both the detectability of these flood events and the accuracy of the developed algorithm, in the presence and absence of flooding, are assessed and discussed. Note de contenu : 1- Introduction 2- Synthetic aperture radar: theoretical background 3- State of the art in SAR-based flood mapping 4- An assessment of establish ed SAR-based flood mappingapproaches 5- Flood mapping in vegetated areas using an unsupervisedclustering approach on Sentinel-1 and -2 imagery 6- Flood monitoring in Flanders using Sentinel-1 imagery 7- Conclusion and outlook Numéro de notice : 28303 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Thesis : Bioscience Engineering : Universiteit Gent : 2021 DOI : sans En ligne : https://biblio.ugent.be/publication/8709595/file/8709639.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98053

An edge-based method for registering a graph onto an image with application to cadastre registration / Roger Trias-Sanz (2004)

Public Titre : An edge-based method for registering a graph onto an image with application to cadastre registration Type de document : Article/Communication Auteurs : Roger Trias-Sanz , Auteur Editeur : Gand [Belgique] : Universiteit Gent Année de publication : 2004 Conférence : ACIVS 2004, Advanced Concepts for Intelligent Vision Systems 31/08/2004 03/09/2004 Bruxelles Belgique OA Abstracts only Note générale : bibliographie Langues : Anglais (eng) Résumé : (auteur) In the context of the development of a land use analysis system, we need to register a cadastre graph onto georeferenced color and near-infrared images at 50cm resolution. A registration process is necessary because image edges and cadastre edges do not correspond, since farmers need not strictly follow fiscal divisions. The problem of registering a cadastre graph onto an image is formalized as a graph matching problem, which is solved by simulated annealing. Additionally, a score for each cadastre edge is obtained, which shows which edges can be found in the image and which cannot. Minor geometrical deformations and acquisition errors can also be corrected. Numéro de notice : C2004-040 Affiliation des auteurs : MATIS (1993-2011) Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103011

Using textural and geometric information for an automatic bridge detection system / Roger Trias-Sanz (2004)  

Public Titre : Using textural and geometric information for an automatic bridge detection system Type de document : Article/Communication Auteurs : Roger Trias-Sanz , Auteur ; Nicolas Lomenie, Auteur ; Jérôme Barbeau, Auteur Editeur : Gand [Belgique] : Universiteit Gent Année de publication : 2004 Conférence : ACIVS 2004, Advanced Concepts for Intelligent Vision Systems 31/08/2004 03/09/2004 Bruxelles Belgique OA Abstracts only Importance : pp 325 - 332 Note générale : bibliographie PAS DE DOCUMENT AU CDOS Langues : Anglais (eng) Descripteur : [Termes IGN] classification automatique [Termes IGN] détection automatique [Termes IGN] détection d'objet [Termes IGN] géométrie de l'image [Termes IGN] image Ikonos [Termes IGN] image panchromatique [Termes IGN] image SPOT 5 [Termes IGN] pont [Termes IGN] texture d'image Résumé : (auteur) We present some results on systems for automatically detecting bridges in very high-resolution panchromatic satellite images using texture information and geometric models. The system has been tested on 2.5m per pixel and 1m per pixel aerial images processed to have the characteristics of SPOT 5 and Ikonos output. A system using simple geometric models gives good results for bridges over roads and railroads, and very bad results for bridges over larger regions such as rivers. In contrast, a system using a texture-based classification and hand-made rules applied to that classification gives good results for bridges over rivers and railroads, and bad results for bridges over roads. Numéro de notice : C2004-050 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : sans En ligne : https://hal.science/hal-00136304 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103050