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Automatic detection of suspected sewage discharge from coastal outfalls based on Sentinel-2 imagery / Yuxin Wang in Science of the total environment, vol 853 (December 2022)
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Titre : Automatic detection of suspected sewage discharge from coastal outfalls based on Sentinel-2 imagery Type de document : Article/Communication Auteurs : Yuxin Wang, Auteur ; Xianqiang He, Auteur ; Yan Bai, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 158374 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] Chine
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par nuées dynamiques
[Termes IGN] couleur de l'océan
[Termes IGN] détection automatique
[Termes IGN] eau usée
[Termes IGN] image Sentinel-MSI
[Termes IGN] littoral
[Termes IGN] perturbation écologique
[Termes IGN] qualité des eauxRésumé : (auteur) Terrestrial pollution has a great impact on the coastal ecological environment, and widely distributed coastal outfalls act as the final gate through which pollutants flow into rivers and oceans. Thus, effectively monitoring the water quality of coastal outfalls is the key to protecting the ecological environment. Satellite remote sensing provides an attractive way to monitor sewage discharge. Selecting the coastal areas of Zhejiang Province, China, as an example, this study proposes an innovative method for automatically detecting suspected sewage discharge from coastal outfalls based on high spatial resolution satellite imageries from Sentinel-2. According to the accumulated in situ observations, we established a training dataset of water spectra covering various optical water types from satellite-retrieved remote sensing reflectance (Rrs). Based on the clustering results from unsupervised classification and different spectral indices, a random forest (RF) classification model was established for the optical water type classification and detection of suspected sewage. The final classification covers 14 optical water types, with type 12 and type 14 corresponding to the high eutrophication water type and suspected sewage water type, respectively. The classification result of model training datasets exhibited high accuracy with only one misclassified sample. This model was evaluated by historical sewage discharge events that were verified by on-site observations and demonstrated that it could successfully recognize sewage discharge from coastal outfalls. In addition, this model has been operationally applied to automatically detect suspected sewage discharge in the coastal area of Zhejiang Province, China, and shows broad application value for coastal pollution supervision, management, and source analysis. Numéro de notice : A2022-859 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scitotenv.2022.158374 Date de publication en ligne : 28/08/2022 En ligne : https://doi.org/10.1016/j.scitotenv.2022.158374 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102135
in Science of the total environment > vol 853 (December 2022) . - n° 158374[article]Development and long-term dynamics of old-growth beech-fir forests in the Pyrenees: Evidence from dendroecology and dynamic vegetation modelling / Dario Martín-Benito in Forest ecology and management, vol 524 (November-15 2022)
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Titre : Development and long-term dynamics of old-growth beech-fir forests in the Pyrenees: Evidence from dendroecology and dynamic vegetation modelling Type de document : Article/Communication Auteurs : Dario Martín-Benito, Auteur ; Juan Alberto Molina-Valero, Auteur ; César Pérez-Cruzado, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120541 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba
[Termes IGN] analyse diachronique
[Termes IGN] biomasse forestière
[Termes IGN] dendroécologie
[Termes IGN] dynamique de la végétation
[Termes IGN] Espagne
[Termes IGN] exploitation forestière
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt ancienne
[Termes IGN] forêt tempérée
[Termes IGN] modèle de croissance végétale
[Termes IGN] ombre
[Termes IGN] perturbation écologique
[Termes IGN] Pyrénées (montagne)
[Vedettes matières IGN] ForesterieRésumé : (auteur) Ecological knowledge on long-term forest dynamics and development has been primarily derived from the study of old-growth forests. Centuries of forest management have decreased the extent of temperate old-growth forests in Europe and altered managed forests. Disentangling the effects of past human disturbances and climate on current species composition is crucial for understanding the long-term development of forests under global change. In this study, we investigated disturbance and recruitment dynamics in two forests in the Western Pyrenees (Spain) with contrasting management history: an old-growth forest and a long-untouched forest, both dominated by the two shade-tolerant species Fagus sylvatica (European beech) and Abies alba (Silver fir). We used dendroecological methods in seven plots to analyse forest structure, growth patterns and disturbance histories in these forests. We benchmarked these data with the dynamic vegetation model ForClim to examine the effects of natural and human-induced disturbances on forest development, structure and species composition. Disturbance regimes differed between the study forests, but none showed evidence of stand replacing disturbances, either natural or human induced. Low disturbance rates and continuous recruitment of beech and fir dominated the old-growth forest over the last 400 years. In contrast, the long-untouched forest was intensively disturbed in 1700–1780, probably by logging, with lower natural disturbance rates thereafter. Beech and fir recruitment preferentially occurred after more intense disturbances, despite the high shade tolerance of both beech and fir. Higher fir abundance in the long-untouched forest than in the old-growth forest appeared to be related to its human-induced disturbances. ForClim closely simulated forest potential natural vegetation with a dominance of beech over fir, but overestimated the presence of less shade-tolerant species. Previously observed local fir decline may result from natural forest successional processes after logging. Within ∼200 years after logging cessation, some long-untouched forest structural attributes converged towards old-growth forest, but legacy effects still affected species composition and structure. Natural disturbance regimes in beech-fir forests of the Western Pyrenees induce temporal fluctuations between beech and fir abundance, with a natural tendency for beech dominance in advanced developmental stages with low disturbance rates. Numéro de notice : A2022-732 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1016/j.foreco.2022.120541 Date de publication en ligne : 23/09/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120541 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101695
in Forest ecology and management > vol 524 (November-15 2022) . - n° 120541[article]An open science and open data approach for the statistically robust estimation of forest disturbance areas / Saverio Francini in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)
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Titre : An open science and open data approach for the statistically robust estimation of forest disturbance areas Type de document : Article/Communication Auteurs : Saverio Francini, Auteur ; Ronald E. McRoberts, Auteur ; Giovanni d' Amico, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102663 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] coupe rase (sylviculture)
[Termes IGN] détection de changement
[Termes IGN] estimation statistique
[Termes IGN] Fagus sylvatica
[Termes IGN] Google Earth Engine
[Termes IGN] image Sentinel-MSI
[Termes IGN] Italie
[Termes IGN] méthode robuste
[Termes IGN] perturbation écologique
[Termes IGN] Quercus cerris
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus pubescens
[Termes IGN] Quercus sessiliflora
[Termes IGN] surveillance forestièreRésumé : (auteur) Forest disturbance monitoring is critical for understanding forest-related greenhouse gas emissions and for determining the role of forest management in mitigating climate change. Multiple algorithms for the automated mapping of forest disturbance using remotely sensed imagery have been developed and applied; however, variability in natural and anthropogenic disturbance phenomena, as well as image acquisition conditions, can result in maps that may be incomplete or that contain inaccuracies that prevent their use for directly estimating areas of disturbance. To reduce errors in reporting disturbance areas, stratified estimators can be applied to obtain statistically robust area estimates, while simultaneously circumventing the need to conduct a complete census or in situations where such a census may not be possible. We present a semi-automated procedure for implementation in Google Earth Engine, 3I3D-GEE, for regional to global mapping of forest disturbance (including clear-cut harvesting, fire, and wind damage) and sample-based estimation of related areas using data from the processing capacity of Google Earth Engine. Documentation for the application is also provided in Appendix A. Using Sentinel-2 (S2) imagery, our procedure was applied and tested for 2018 in Italy for which the approximately 11 million ha of forests (mostly Q. pubescens, Q. robur, Q. cerris, Q. petraea, and Fagus sylvatica) serve as an appropriate case study because national statistics on forest disturbance areas are not available. To decrease the overall standard errors of the area estimates, the sampling intensities in areas where greater variability in the form of greater commission and omission errors are expected can be increased. To this end, we augmented the predicted forest disturbance map with a buffer class consisting of a two-pixel buffer (20 m) on each side of the disturbance class boundary. We selected a reference sample of 19,300 points: a simple random sample of 9,300 points from the buffer and simple random samples of 5000 from each of the undisturbed and disturbed classes. The reference sample was photointerpreted using fine resolution orthophotos (30 cm) and S2 imagery. While the estimate of the disturbed area obtained by adding the areas of pixels classified as disturbed was 41,732 ha, the estimate obtained using the unbiased stratified estimator was 27% greater at 57,717716 ha. Regarding map accuracy, we found several omission errors in the buffer (53.4%) but none (0%) in the undisturbed map class. Similarly, among the 1035 commission errors, the majority (7 4 4) were in the buffer class. The methods presented herein provide a useful tool that can be used to estimate areas of forest disturbance, which many nations must report as part of their commitment to international conventions and treaties. In addition, the information generated can support forest management, enabling the forest sector to monitor stand-replacing forest harvesting over space and time. Numéro de notice : A2022-072 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2021.102663 En ligne : https://doi.org/10.1016/j.jag.2021.102663 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99437
in International journal of applied Earth observation and geoinformation > vol 106 (February 2022) . - n° 102663[article]Investigating the role of wind disturbance in tropical forests through a forest dynamics model and satellite observations / E-Ping Rau (2022)
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Titre : Investigating the role of wind disturbance in tropical forests through a forest dynamics model and satellite observations Type de document : Thèse/HDR Auteurs : E-Ping Rau, Auteur ; Jérôme Chave, Directeur de thèse Editeur : Toulouse : Université de Toulouse 3 Paul Sabatier Année de publication : 2022 Importance : 184 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse 3 Paul SabatierLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse forestière
[Termes IGN] canopée
[Termes IGN] chablis (sylviculture)
[Termes IGN] cyclone
[Termes IGN] forêt tropicale
[Termes IGN] Guyane française
[Termes IGN] image Sentinel-SAR
[Termes IGN] modèle dynamique
[Termes IGN] perturbation écologique
[Termes IGN] précipitation
[Termes IGN] risque naturel
[Termes IGN] sécheresse
[Termes IGN] traitement d'image radar
[Termes IGN] ventIndex. décimale : THESE Thèses et HDR Résumé : (Auteur) Natural disturbances have an important influence on the structure, composition and functioning of tropical forests and a role in the regulation of biogeochemical cycles. The frequency and intensity of natural disturbances are modified by climate change: a better knowledge of their mechanism of action is necessary to predict the consequences of this modification. Modeling allows us to evaluate the role of each of the ecological processes and their link with environmental factors. Remote sensing tools inform us about the structure and functioning of forests at large scales, and can be useful for the calibration and validation of vegetation models. In this thesis, I employed both approaches to examine how tropical forests are shaped by natural disturbances, particularly wind, which is a major disturbance factor in many tropical regions. First, I evaluated the transferability of a spatially explicit, individual-based model via sensitivity testing and calibration of global parameters. The model correctly predicts forest structure at two contrasting sites, and its response is consistent with variations in climate forcing. Calibration of a small number of key parameters was required, including the parameter controlling mortality and crown allometry. To investigate the sensitivity of the model to mortality, I implemented a wind damage module based on biophysical principles and coupled with wind speed to model forest responses to extreme wind events. With increasing disturbance level, canopy height decreased steadily but biomass showed a non-linear response. Wind intensity had a strong impact on canopy height and biomass, but not the frequency of extreme wind events. Finally, I tested whether radar data from Sentinel-1 satellites could be used to detect gaps due to natural disturbances in French Guiana. The Sentinel-1 data detected more natural gaps above 0.2 ha than the optical satellite data, and they showed a spatial pattern consistent with the optical images. The level of disturbance did not vary with altitude. We found more disturbance during dry seasons, which could be due to the delayed response of precipitation rather than the direct response of drought. In conclusion, this thesis demonstrates that the integration between modeling and remote sensing sheds light on the effects of natural disturbances on tropical forests. The resulting results can be used to study other types of disturbances and their interactions on a large scale. Note de contenu : General introduction
General methods
1: Transferability of an individual- and trait-based forest dynamics model: a test case across the tropics
1.1 Abstract
1.2 Introduction
1.3 Materials and methods
1.4 Results
1.5 Discussion
1.6 Acknowledgements and author contributions
1.7 Supplementary data
2: Wind speed controls forest structure in subtropical forests exposed to cyclones: a case study using an individual-based model
2.1 Abstract
2.2 Introduction
2.3 Material and methods
2.4 Results
2.5 Discussion
2.6 Acknowledgments and author contributions
2.7 Supplementary data
3: Detecting Natural Disturbances in Tropical Forests Using Sentinel-1 SAR Data: a Test in French Guiana
3.1 Abstract
3.2 Introduction
3.3 Methods
3.4 Results
3.5 Discussions
3.6 Acknowledgments and author contributions
3.7 Supplementary data
General discussion and conclusionsNuméro de notice : 26836 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Ecologie, biodiversité et évolution : Toulouse 3 : 2022 nature-HAL : Thèse DOI : sans Date de publication en ligne : 20/06/2022 En ligne : https://tel.hal.science/tel-03699667 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101075 A spatially explicit database of wind disturbances in European forests over the period 2000–2018 / Giovanni Forzieri in Earth System Science Data, vol 12 n° 1 (January 2020)
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Titre : A spatially explicit database of wind disturbances in European forests over the period 2000–2018 Type de document : Article/Communication Auteurs : Giovanni Forzieri, Auteur ; Matteo Pecchi, Auteur ; Marco Girardello, Auteur ; Achille Mauri, Auteur ; Marcus Klaus, Auteur ; Christo Nikolov, Auteur ; Marius Rüetschi, Auteur ; Barry Gardiner, Auteur ; Julian Tomaštík, Auteur ; David Small, Auteur ; Constantin Nistor, Auteur ; Donatas Jonikavičius, Auteur ; Jonathan Spinoni, Auteur ; Luc Feyen, Auteur ; Francesca Giannetti, Auteur ; Rinaldo Comino, Auteur ; Alessandro Wolynski, Auteur ; Francesco Pirotti, Auteur ; Fabio Maistrelli, Auteur ; Ionut Savulescu, Auteur ; Stéphanie Wurpillot , Auteur ; et al., Auteur
Année de publication : 2020 Projets : 3-projet - voir note / Article en page(s) : pp 257 - 276 Note générale : bibliographie
This research has been supported by the European Commission, Joint Research Centre (project FOREST@RISK).Langues : Anglais (eng) Descripteur : [Termes IGN] base de données localisées
[Termes IGN] capital sur pied
[Termes IGN] données vectorielles
[Termes IGN] écosystème forestier
[Termes IGN] Europe (géographie politique)
[Termes IGN] forêt
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] perturbation écologique
[Termes IGN] tempête
[Termes IGN] tempête Klaus de 2009
[Termes IGN] tempête Lothar de 1999
[Termes IGN] tempête Xynthia de 2010
[Termes IGN] vent
[Termes IGN] vingt-et-unième siècle
[Vedettes matières IGN] ForesterieMots-clés libres : FORWIND Résumé : (auteur) Strong winds may uproot and break trees and represent a major natural disturbance for European forests. Wind disturbances have intensified over the last decades globally and are expected to further rise in view of the effects of climate change. Despite the importance of such natural disturbances, there are currently no spatially explicit databases of wind-related impact at a pan-European scale. Here, we present a new database of wind disturbances in European forests (FORWIND). FORWIND is comprised of more than 80 000 spatially delineated areas in Europe that were disturbed by wind in the period 2000–2018 and describes them in a harmonized and consistent geographical vector format. The database includes all major windstorms that occurred over the observational period (e.g. Gudrun, Kyrill, Klaus, Xynthia and Vaia) and represents approximately 30 % of the reported damaging wind events in Europe. Correlation analyses between the areas in FORWIND and land cover changes retrieved from the Landsat-based Global Forest Change dataset and the MODIS Global Disturbance Index corroborate the robustness of FORWIND. Spearman rank coefficients range between 0.27 and 0.48 (p value Numéro de notice : A2020-874 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/essd-12-257-2020 Date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.5194/essd-12-257-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99655
in Earth System Science Data > vol 12 n° 1 (January 2020) . - pp 257 - 276[article]A systematic evaluation of influence of image selection process on remote sensing-based burn severity indices in North American boreal forest and tundra ecosystems / Dong Chen in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)
PermalinkProperties of boundary-line release criteria in North American tree species / Bryan A. Black in Annals of Forest Science, Vol 66 n° 2 (march 2009)
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