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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 BordeauxLangues : 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 hyperfréquenceIndex. 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. PerspectivesNuméro 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 Mapping tropical forest trees across large areas with lightweight cost-effective terrestrial laser scanning / Shengli Tao in Annals of Forest Science, vol 78 n° 4 (December 2021)
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Titre : Mapping tropical forest trees across large areas with lightweight cost-effective terrestrial laser scanning Type de document : Article/Communication Auteurs : Shengli Tao, Auteur ; Nicolas Labrière, Auteur ; Kim Calders, Auteur ; Fabian Jörg Fischer, Auteur ; E-Ping Rau, Auteur ; Laetitia Plaisance, Auteur ; Jérôme Chave, Auteur Année de publication : 2021 Article en page(s) : n° 103 Note générale : bibliographie
This work has benefitted from an “Investissement d'Avenir” grant managed by Agence Nationale de la Recherche (AnaEE France ANR-11-INBS-0001; CEBA, ref. ANR-10-LABX-25–01), the CNRS Nouragues station, and a CNES postdoctoral fellowship granted to S.T.Langues : Anglais (eng) Descripteur : [Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] Guyane (département français)
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] placette d'échantillonnage
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Key message : We used lightweight terrestrial laser scanning (TLS) to detect over 3000 stems per hectare across a 12-ha permanent forest plot in French Guiana, 81% of them Context : Accurate position mapping of tropical rainforest trees is crucial for baseline studies of tropical forest ecology but is labor-intensive. Terrestrial lidar scanning (TLS) is broadly used in temperate forest inventories, but its use in rainforests is restricted to the determination of individual tree volumes within small survey areas.
Aims : Mapping tree stems across one large (12-ha) rainforest plot, including trees less than 10 cm DBH, and evaluating the precision of traditional mapping approaches.
Methods : We used lightweight TLS, co-registered the acquisitions, and developed a new efficient algorithm to process the TLS data.
Results : We detected 36,422 stems of which 29,665 (81%) were Conclusion : Lightweight TLS technology is a promising tool for the estimation of stem tapering and volume. Here, we show that it also facilitates the establishment of large tropical forest inventories, by improving the positioning of trees, thus increasing the accuracy of forest inventories and their cost-effectiveness.Numéro de notice : A2021-954 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s13595-021-01113-9 Date de publication en ligne : 28/12/2021 En ligne : https://doi.org/10.1007/s13595-021-01113-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99998
in Annals of Forest Science > vol 78 n° 4 (December 2021) . - n° 103[article]Automatic tuning of segmentation parameters for tree crown delineation with VHR imagery / Camile Sothe in Geocarto international, vol 36 n° 19 ([01/11/2021])
[article]
Titre : Automatic tuning of segmentation parameters for tree crown delineation with VHR imagery Type de document : Article/Communication Auteurs : Camile Sothe, Auteur ; Claudia Maria de Almeida, Auteur ; Marcos Benedito Schimalski, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2241 - 2259 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] Brésil
[Termes IGN] délimitation
[Termes IGN] forêt tropicale
[Termes IGN] houppier
[Termes IGN] identification de plantes
[Termes IGN] image à très haute résolution
[Termes IGN] image Worldview
[Termes IGN] méthode heuristique
[Termes IGN] orthoimage
[Termes IGN] segmentation d'imageRésumé : (auteur) In the case of tree species delineation with very high spatial resolution (VHR) images, is desirable that each segment corresponds to one individual tree crown (ITC). However, in order to have a segmentation algorithm that generates segments matching to ITCs, its parameters ought to be properly tuned. Aiming to avoid time-consuming trial-and-error procedures associated with this task, some initiatives for the automatic search of segmentation parameters have been developed, such as metaheuristic methods. The objective of this work was to test the automatic tuning of segmentation parameters of three segmentation algorithms for the delineation of ITCs belonging to a native endangered species in a subtropical forest area, comparing this method with the traditional trial-and-error approach. Two datasets (WorldView-2 and an orthoimage) and three segmentation algorithms (multiresolution, mean-shift and graph-based) were tested. For the automatic approach, a hybrid metaheuristic method was applied to accomplish the automatic search of parameters for the segmentation algorithms, while for the trial-and-error, a visual assessment was conducted for each set of parameters tested. Four supervised metrics were used to assess the quality of the segmentation results for the optimization approach and for the final set of parameters chosen in the trial-and-error approach. Results showed that none of the algorithms, datasets or approaches differ too much. The evaluation metrics values were lower, indicating that the reference ITCs polygons matched with the segmentation results. Despite the similar results, the automatic tuning of segmentation parameters proved to be a feasible alternative to reduce the subjectivity and the human effort in the choice of segmentation parameters as compared to the trial-and error approach. Numéro de notice : A2021-765 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1690056 Date de publication en ligne : 14/11/2019 En ligne : https://doi.org/10.1080/10106049.2019.1690056 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98810
in Geocarto international > vol 36 n° 19 [01/11/2021] . - pp 2241 - 2259[article]Prioritization of forest fire hazard risk simulation using Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) coupled with multicriteria decision analysis (MCDA) techniques – a comparative study analysis / Michael Stanley Peprah in Geodesy and cartography, vol 47 n° 3 (October 2021)
[article]
Titre : Prioritization of forest fire hazard risk simulation using Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) coupled with multicriteria decision analysis (MCDA) techniques – a comparative study analysis Type de document : Article/Communication Auteurs : Michael Stanley Peprah, Auteur ; Bernard Kumi-Boateng, Auteur ; Edwin Kojo Larbi, Auteur Année de publication : 2021 Article en page(s) : pp 147 - 161 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse des risques
[Termes IGN] analyse multicritère
[Termes IGN] cartographie des risques
[Termes IGN] forêt tropicale
[Termes IGN] Ghana
[Termes IGN] incendie de forêt
[Termes IGN] modèle de simulation
[Termes IGN] prévention des risques
[Termes IGN] processus de hiérarchisation analytique floue
[Termes IGN] rastérisationRésumé : (auteur) Forests are important dynamic systems which are widely attracted by wild fires worldwide. Due to the complexity and non-linearity of the causative forest fire problems, employing sophisticated hybrid evolutionary algorithms is a logical task to achieve a reliable approximation of this environmental threats. This estimate will provide the outline of priority areas for preventing activities and allocation of fire fighters’ stations, seeking to minimize possible damages caused by fires. This study aims at prioritizing the forest fire risk of Wassa West district of Ghana. The study considered static causative factors such as Land use and land cover (which include forest, built-ups and settlement areas), slope, aspect, linear features (water bodies and roads) and dynamic causative factors such as wind speed, precipitation, and temperature were used. The methods employed include a Hybrid Grey Relativity Analysis (HGRA) and Fuzzy Analytical Hierarchy Process (FAHP) techniques. The fuzzy sets integrated with AHP in a decision-making algorithm using geographic information system (GIS) was used to model the fire risk in the study area. FAHP and HGRA methods were used for estimating the importance (weights) of the effective factors in forest fire modelling. Based on their modelling methods, the expert ideas were used to express the relative importance and priority of the major criteria and sub-criteria in forest fire risk in the study area. The expert ideas were analyzed based on FAHP and HGRA. The major criteria models and fire risk model were presented based on these FAHP and HGRA weights. On the other hand, the spatial data of the sub criteria were provided and assembled in GIS environment to obtain the sub-criteria maps. Each sub-criterion map was converted to raster format and it was reclassified based on risks of its classes to fire occurrence. The maps of each major criterion were obtained by weighted overlay of its sub criteria maps considering to major criterion model in GIS environment. Finally, the map of fire risk was obtained by weighted overlay of major criteria maps considering to fire risk model in GIS. The results showed that the FAHP model showed superiority than HGRA in prioritizing forest fire risk of the study area in terms of statistical analysis with a standard deviation of 0.09277 m as compared to 0.1122 m respectively. The obtained fire risk map can be used as a decision support system for predicting of the future trends in the study area. The optimized structures of the proposed models could serve as a good alternative to traditional forest predictive models, and this can be a promisingly testament used for future planning and decision making in the proposed areas. Numéro de notice : A2021-863 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.3846/gac.2021.13028 Date de publication en ligne : 17/08/2021 En ligne : https://doi.org/10.3846/gac.2021.13028 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99079
in Geodesy and cartography > vol 47 n° 3 (October 2021) . - pp 147 - 161[article]Mapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches / He Zhang in Remote sensing, vol 13 n° 18 (September-2 2021)
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Titre : Mapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches Type de document : Article/Communication Auteurs : He Zhang, Auteur ; Marijn Bauters, Auteur ; Pascal Boeckx, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 3777 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage automatique
[Termes IGN] biomasse aérienne
[Termes IGN] Congo (bassin)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] modèle numérique de terrain
[Termes IGN] photogrammétrie aérienne
[Termes IGN] point d'appui
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] surveillance forestièreRésumé : (auteur) Tropical forests are a key component of the global carbon cycle and climate change mitigation. Field- or LiDAR-based approaches enable reliable measurements of the structure and above-ground biomass (AGB) of tropical forests. Data derived from digital aerial photogrammetry (DAP) on the unmanned aerial vehicle (UAV) platform offer several advantages over field- and LiDAR-based approaches in terms of scale and efficiency, and DAP has been presented as a viable and economical alternative in boreal or deciduous forests. However, detecting with DAP the ground in dense tropical forests, which is required for the estimation of canopy height, is currently considered highly challenging. To address this issue, we present a generally applicable method that is based on machine learning methods to identify the forest floor in DAP-derived point clouds of dense tropical forests. We capitalize on the DAP-derived high-resolution vertical forest structure to inform ground detection. We conducted UAV-DAP surveys combined with field inventories in the tropical forest of the Congo Basin. Using airborne LiDAR (ALS) for ground truthing, we present a canopy height model (CHM) generation workflow that constitutes the detection, classification and interpolation of ground points using a combination of local minima filters, supervised machine learning algorithms and TIN densification for classifying ground points using spectral and geometrical features from the UAV-based 3D data. We demonstrate that our DAP-based method provides estimates of tree heights that are identical to LiDAR-based approaches (conservatively estimated NSE = 0.88, RMSE = 1.6 m). An external validation shows that our method is capable of providing accurate and precise estimates of tree heights and AGB in dense tropical forests (DAP vs. field inventories of old forest: r2 = 0.913, RMSE = 31.93 Mg ha−1). Overall, this study demonstrates that the application of cheap and easily deployable UAV-DAP platforms can be deployed without expert knowledge to generate biophysical information and advance the study and monitoring of dense tropical forests. Numéro de notice : A2021-754 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13183777 Date de publication en ligne : 20/09/2021 En ligne : https://doi.org/10.3390/rs13183777 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98746
in Remote sensing > vol 13 n° 18 (September-2 2021) . - n° 3777[article]Multi-task fully convolutional network for tree species mapping in dense forests using small training hyperspectral data / Laura Elena Cué La Rosa in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)PermalinkThe real potential of current passive satellite data to map aboveground biomass in tropical forests / Nidhi Jha in Remote sensing in ecology and conservation, vol 7 n° 3 (September 2021)PermalinkDirect analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) of wood reveals distinct chemical signatures of two species of Afzelia / Peter Kitin in Annals of Forest Science, vol 78 n° 2 (June 2021)PermalinkAboveground biomass estimates of tropical mangrove forest using Sentinel-1 SAR coherence data : The superiority of deep learning over a semi-empirical model / S.M. Ghosh in Computers & geosciences, vol 150 (May 2021)PermalinkPotentialité des données satellitaires Sentinel-2 pour la cartographie de l’impact des feux de végétation en Afrique tropicale : application au Togo / Yawo Konko in Bois et forêts des tropiques, n° 347 ([02/04/2021])PermalinkTropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning / Maryam Pourshamsi in ISPRS Journal of photogrammetry and remote sensing, vol 172 (February 2021)PermalinkIndividual tree diameter growth modeling system for Dalat pine (Pinus dalatensis Ferré) of the upland mixed tropical forests / Bao Huy in Forest ecology and management, vol 480 (15 January 2021)PermalinkApport des données Sentinel-1 pour le suivi continu de la forêt tropicale : Cas de la Guyane / Marie Ballère (2021)PermalinkApport de la modélisation physique pour la cartographie de la biodiversité végétale en forêts tropicales par télédétection optique / Dav Ebengo Mwampongo (2021)PermalinkDétection de changement d’occupation du sol à l’aide de données Sentinel en contexte tropical / Lucas Martelet (2021)Permalink