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Radar backscatter contribution to tropical forest disturbance monitoring / Bertrand Ygorra (2022)  

Public Titre : Radar backscatter contribution to tropical forest disturbance monitoring Type de document : Thèse/HDR Auteurs : Bertrand Ygorra, Auteur ; Jean-Pierre Wigneron, Directeur de thèse ; Serge Riazanoff, Directeur de thèse ; Frédéric Frappart, Directeur de thèse Editeur : Bordeaux : Université de Bordeaux Année de publication : 2022 Importance : 253 p. Format : 21 x 30 cm Note générale : Bibliographie Thèse en vue de l'obtention du Doctorat de l'Université de Bordeaux Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection [Termes IGN] couvert forestier [Termes IGN] déboisement [Termes IGN] détection de changement [Termes IGN] forêt tropicale [Termes IGN] image Sentinel-SAR [Termes IGN] nébulosité [Termes IGN] télédétection en hyperfréquence Index. décimale : THESE Thèses et HDR Résumé : (Auteur) Earth Observations are increasingly used to monitor environmental problems. Its interests lie in the ability of sensors aboard satellites to provide information at global, regional and local scales. Optical remote sensing has shown great potential for the monitoring of forest disturbances. Until recently, deforestation monitoring systems were mainly based on remotely sensed optical images. In the intertropical latitudes, such images often face limitations of frequent cloud cover, leading to late detection or misdetections due to the low temporal availability of new images uncontaminated by clouds. In tropical humid forests, regrowth can close canopy gaps between two non-cloud-contaminated optical images used for detection.New SAR (Synthetic Aperture Radar) systems have opened new perspectives for forest disturbance monitoring in tropical humid forests (Sentinel-1, PALSAR-2). These active sensors penetrate the clouds. The availability of Sentinel-1 C-band images at high spatial and temporal resolutions makes it a potential substitute of optical systems for monitoring disturbances in forest covers.This work is articulated around three parts. The first part consists in the development of a new change detection method for monitoring disturbances in forest cover, based on the Cumulative Sum algorithm (CuSum) combined with a bootstrap analysis. The method was applied to time-series of Sentinel-1 Ground-Range Detected (GRD) dual polarization (VV, VH) images obtained in a legal forest concession near Kisangani in the Democratic Republic of the Congo. The results from VV and VH polarization were intersected in VV x VH result map, and a spatial recombination of a high Critical Threshold (Tc) with a low critical threshold was performed. The second part of this work is to develop a multiple-breakpoints version of the CuSum cross-Tc called ReCuSum to further enhance the ability to monitor changes in forest cover. The development was made by applying the CuSum cross-Tc over a time-series in an iterative manner, in the State of Parà, Brazilian Amazon. The third axis of this thesis is to develop a Near-Real-Time (NRT) version of the CuSum cross-Tc and to compare it with the state-of-the-art NRT algorithms (RADD, JJ-FAST GLAD, DETER-B, DETER-R). Note de contenu : Chapter 1. General introduction 1.1. Introduction 1.2. Thesis objectives and outline Chapter 2. Radar remote sensing 2.1. The RADAR technique 2.2. Instrumental parameters 2.3. Scattering mechanisms 2.4. Synthetic Aperture Radar 2.5. Sentinel-1 Chapter 3. Methods for monitoring forest cover change using spaceborne SAR sensors 3.1. Introduction 3.2. Publication 3.3. Contribution and perspectives Chapter 4. Monitoring forest disturbances from Sentinel-1 time-series: a CuSum?based approach 4.1. Introduction 4.2. Publication 4.3. Conference note: IGARSS 2021 4.4. Contribution to this work and perspectives in the PhD course Chapter 5. Multiple breakpoints Evolution of the cross-Tc CuSum: ReCuSum 5.1. Introduction 5.2. Publication 5.3. Conference note: IGARSS 2022 5.4. Contribution to this work and perspective Chapter 6. Development of the CuSum cross-Tc as an NRT algorithm 6.1. Introduction 6.2. Publication 6.3. Contribution and perspectives Chapter 7. Conclusion and perspectives 7.1. Conclusion 7.2. Perspectives Numéro de notice : 26964 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Physique de l’environnement : Bordeaux : 2022 Organisme de stage : INRAE nature-HAL : Thèse DOI : sans Date de publication en ligne : 16/02/2023 En ligne : https://theses.hal.science/tel-03991973v1/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103001