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Evaluation of Sentinel-1 & 2 time series for the identification and characterization of ecological continuities, from wooded to crop-dominated landscapes / Audrey Mercier (2021)
Titre : Evaluation of Sentinel-1 & 2 time series for the identification and characterization of ecological continuities, from wooded to crop-dominated landscapes Type de document : Thèse/HDR Auteurs : Audrey Mercier, Auteur ; Laurence Hubert-Moy, Directeur de thèse ; Jacques Baudry, Directeur de thèse Editeur : Rennes : Université de Rennes 2 Année de publication : 2021 Importance : 305 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse de Doctorat présentée à l'Université de Rennes 2, Spécialité GéomatiqueLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] caractérisation
[Termes IGN] continuité écologique
[Termes IGN] cultures
[Termes IGN] données polarimétriques
[Termes IGN] forêt
[Termes IGN] habitat (nature)
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] occupation du sol
[Termes IGN] paysage agricole
[Termes IGN] précision de la classification
[Termes IGN] série temporelle
[Termes IGN] utilisation du solIndex. décimale : THESE Thèses et HDR Résumé : (Auteur) Habitat loss is now considered one of the most serious threats to biodiversity. While many studies have focused on the circulation role of woodland features, very few have focused on the role of ecological continuities within agricultural mosaics. The objectives of this thesis were (1) to assess the combined use of Sentinel 1 and 2 time series to identify and characterize the elements of ecological continuities through land cover classifications and crop characterization in wooded and crop-dominated landscapes and (2) to estimate the impact of the spatio-temporal structuring of these landscape on biodiversity using metrics derived from Sentinel time series. The results showed that although S-2 data are more adapted than S-1 data to discriminate between land cover/land use types in wooded landscapes and phenological stages of wheat and rapeseed in crop-dominated landscapes, the combined use of S-2 and S-1 data improves their accuracy of the classifications, with S-1 data also showing a strong interest in cloudy areas. They also showed the interest of polarimetric indicators derived from S-1 data to characterize wheat and rapeseed crops. Finally, they highlighted the interest of the biophysical heterogeneity metrics derived from S-2 data to accurately estimate the distribution of carabid beetle species. The use of this metric, calculated with free images available everywhere on Earth, continuous and consistent from one site to another and from one type of crop to another,
should contribute to the study of the impact of ecological continuities on biodiversity.Note de contenu : General introduction
1. Ecological continuities from wooded to crop-dominated landscapes
2. The use of remote sensing imagery for the identification and characterization of ecological continuities
3. Study areas and data
4. Evaluation of Sentinel-1 and 2 time Series for land cover classification of forest–agriculture mosaics in temperate and tropical landscapes
5. Evaluation of Sentinel-1 and 2 time series for predicting wheat and rapeseed phenological stages
6. Evaluation of Sentinel-1 and 2 time series for estimating LAI and biomass of wheat and rapeseed crop types
7. Sentinel-2 images bring out functional biophysical heterogeneities in crop mosaics
General conclusion and perspectivesNuméro de notice : 26708 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Géomatique : Rennes 2 : 2021 Organisme de stage : Littoral, Environnement, Télédétection, Géomatique LETG nature-HAL : Thèse DOI : sans Date de publication en ligne : 14/10/2021 En ligne : https://tel.hal.science/tel-03377565 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99456 Examining the effectiveness of Sentinel-1 and 2 imagery for commercial forest species mapping / Mthembeni Mngadi in Geocarto international, vol 36 n° 1 ([01/01/2021])
[article]
Titre : Examining the effectiveness of Sentinel-1 and 2 imagery for commercial forest species mapping Type de document : Article/Communication Auteurs : Mthembeni Mngadi, Auteur ; John Odindi, Auteur ; Kabir Peerbhay, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2021 Article en page(s) : pp 1 - 12 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse discriminante
[Termes IGN] carte forestière
[Termes IGN] Eucalyptus (genre)
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] KwaZulu-Natal (Afrique du Sud)
[Termes IGN] Pinus (genre)
[Termes IGN] télédétection spatialeRésumé : (Auteur) The successful launch and operation of the Sentinel satellite platform has provided access to freely available remotely sensed data useful for commercial forest species discrimination. Sentinel – 1 (S1) with a synthetic aperture radar (SAR) sensor and Sentinel – 2 (S2) multi-spectral sensor with additional and strategically positioned bands offer great potential for providing reliable information for discriminating and mapping commercial forest species. In this study, we sought to determine the value of S1 and S2 data characteristics in discriminating and mapping commercial forest species. Using linear discriminant analysis (LDA) algorithm, S2 multi-spectral imagery showed an overall classification accuracy of 84% (kappa = 0.81), with bands such as the red-edge (703.9–740.2 nm), narrow near infrared (835.1–864.8 nm), and short wave infrared (1613.7–2202.4 nm) particularly influential in discriminating individual forest species stands. When Sentinel 2’s spectral wavebands were fused with Sentinel 1’s (SAR) VV and VH polarimetric modes, overall classification accuracies improved to 87% (kappa = 0.83) and 88% (kappa = 0.85), respectively. These findings demonstrate the value of combining Sentinel’s multispectral and SAR structural information characteristics in improving commercial forest species discrimination. These, in addition to the sensors free availability, higher spatial resolution and larger swath width, offer unprecedented opportunities for improved local and large scale commercial forest species discrimination and mapping. Numéro de notice : A2021-050 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1585483 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1585483 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96719
in Geocarto international > vol 36 n° 1 [01/01/2021] . - pp 1 - 12[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2021011 RAB Revue Centre de documentation En réserve L003 Disponible Flood mapping from radar remote sensing using automated image classification techniques / Lisa Landuyt (2021)
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 EngineeringLangues : 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 hydrologiqueRésumé : (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 outlookNuméro 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
Titre : Forest biomass : from trees to energy Type de document : Monographie Auteurs : Ana Cristina Goncalves, Éditeur scientifique Editeur : London [UK] : IntechOpen Année de publication : 2021 ISBN/ISSN/EAN : 978-1-83962-971-6 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse (combustible)
[Termes IGN] biomasse forestière
[Termes IGN] bois énergie
[Termes IGN] image Sentinel-MSI
[Termes IGN] occupation du sol
[Termes IGN] Pinus pinaster
[Termes IGN] télédétection spatiale
[Termes IGN] utilisation du solIndex. décimale : 35.41 Applications de télédétection - végétation Résumé : (Editeur) Forests are responsible for the largest net biomass carbon production. They store the most standing biomass and carbon and thus they are an important source of bioenergy. Their importance is linked to their relative abundance and uniformity worldwide and the neutrality of CO2 emissions from biomass conversion to energy. Yet, the use of biomass for energy presents risks related to forest system sustainability and demands for new environmentally sustainable strategies for its use. This book provides a comprehensive overview of the current state of the art in a multitude of subjects related to forest bioenergy, ranging from trees, forest stand management, and biomass assessment to waste management, conversion technologies, and routes and energy applications. Note de contenu : 1. Energy Production from Forest Biomass: An Overview / By Ana Cristina Gonçalves, Isabel Malico and Adélia M.O. Sousa
2. The Potential of Sentinel-2 Satellite Images for Land-Cover/Land-Use and Forest Biomass Estimation: A Review / By Crismeire Isbaex and Ana Margarida Coelho
3. Biomass Estimation Using Satellite-Based Data / By Patrícia Lourenço
4. Management of Maritime Pine: Energetic Potential with Alternative Silvicultural Guidelines / By Teresa Fonseca and José Lousada
5. Evergreen Oak Biomass Residues for Firewood / By Isabel Malico, Ana Cristina Gonçalves and Adélia M.O. Sousa
6. Koroch (Pongamia pinnata): A Promising Unexploited Resources for the Tropics and Subtropics / By Abul Kalam Mohammad Aminul Islam, Swapan Chakrabarty, Zahira Yaakob, Mohammad Ahiduzzaman and Abul Kalam Mohammad Mominul Islam
7. Case Study: Pathways from Forest to Energy in a Circular Economy at Lafões / By Ana d’Espiney, Isabel Paula Marques and Helena Maria Pinheiro
8. Methodology for the Evaluation of the Electrical Energy Potential of Residual Biomass from the Wood Industry: A Case Study in Brazil / By Augusto César de Mendonça Brasil
9. Opportunities of Circular Economy in a Complex System of Woody Biomass and Municipal Sewage Plants / By Attila Bai and Zoltán GabnaiNuméro de notice : 26710 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.90324 Date de publication en ligne : 10/02/2021 En ligne : https://doi.org/10.5772/intechopen.90324 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99479 From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 / Yousra Hamrouni in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)
[article]
Titre : From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 Type de document : Article/Communication Auteurs : Yousra Hamrouni, Auteur ; Eric Paillassa, Auteur ; Véronique Chéret, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 76 - 100 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] base de données forestières
[Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] couvert forestier
[Termes IGN] échantillonnage
[Termes IGN] France (administrative)
[Termes IGN] image Sentinel-MSI
[Termes IGN] mise à jour de base de données
[Termes IGN] Populus (genre)
[Termes IGN] série temporelleRésumé : (auteur) Reliable estimates of poplar plantations area are not available at the French national scale due to the unsuitability and low update rate of existing forest databases for this short-rotation species. While supervised classification methods have been shown to be highly accurate in mapping forest cover from remotely sensed images, their performance depends to a great extent on the labelled samples used to build the models. In addition to their high acquisition cost, such samples are often scarce and not fully representative of the variability in class distributions. Consequently, when classification models are applied to large areas with high intra-class variance, they generally yield poor accuracies because of data shift issues. In this paper, we propose the use of active learning to efficiently adapt a classifier trained on a source image to spatially distinct target images with minimal labelling effort and without sacrificing the classification performance. The adaptation consists in actively adding to the initial local model new relevant training samples from other areas in a cascade that iteratively improves the generalisation capabilities of the classifier leading to a global model tailored to these different areas. This active selection relies on uncertainty sampling to directly focus on the most informative pixels for which the algorithm is the least certain of their class labels. Experiments conducted on Sentinel-2 time series revealed their high capacity to identify poplar plantations at a local scale with an average F-score ranging from 89.5% to 99.3%. For large area adaptation, the results showed that when the same number of training samples was used, active learning outperformed random sampling by up to 5% of the overall accuracy and up to 12% of the class F-score. Additionally, and depending on the class considered, the random sampling model required up to 50% more samples to achieve the same performance of an active learning-based model. Moreover, the results demonstrate the suitability of the derived global model to accurately map poplar plantations among other tree species with overall accuracy values up to 14% higher than those obtained with local models. The proposed approach paves the way for a national scale mapping in an operational context. Numéro de notice : A2021-013 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.018 Date de publication en ligne : 20/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.018 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96417
in ISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 76 - 100[article]Réservation
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