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Beech and hornbeam dominate oak 20 years after the creation of storm-induced gaps / Lucie Dietz in Forest ecology and management, vol 503 (January-1 2022)
[article]
Titre : Beech and hornbeam dominate oak 20 years after the creation of storm-induced gaps Type de document : Article/Communication Auteurs : Lucie Dietz, Auteur ; Jean-Claude Gégout, Auteur ; Jean-Luc Dupouey, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 119758 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Carpinus betulus
[Termes IGN] croissance des arbres
[Termes IGN] Fagus sylvatica
[Termes IGN] France (administrative)
[Termes IGN] gestion forestière adaptative
[Termes IGN] peuplement forestier
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus sessiliflora
[Termes IGN] régénération (sylviculture)
[Termes IGN] tempête
[Termes IGN] tempête Lothar de 1999
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Oak (Quercus petraea (Matt.) Liebl. and Quercus robur L. grouped), European beech (Fagus sylvatica L.) and hornbeam (Carpinus betulus L.) are three major species of western and central European forests. When conditions are suitable for the three species, silvicultural management often favours oak because of its greater economic interest. Forest managers know that beech and hornbeam are strong competitors for oak during the regeneration phase, but the conditions that influence the relative success of the regeneration of the three species growing in mixture are still poorly characterised. The natural regeneration of the three species 20 years after canopy openings was studied based on 108 study sites established in 2001 in French forests impacted by the windstorms Lothar and Martin in 1999. In spring and summer 2018 and 2019, all saplings over 0.1 m in height were counted, species were identified and diameter at breast height (DBH) was measured for all saplings over 1.30 m. The height of the saplings with the highest and median DBH in each plot was recorded for each species. Mixed models were used to analyse the combined effects of former stand type, distance from the edge of the gap and soil conditions on species presence, sapling abundance, DBH and height. The modelling approach highlighted the preponderant role of the initial seed rain on the presence and sapling density of the three species compared to interspecific competition or distance from the edge. The two latter factors had a secondary effect on sapling DBH and height. Beech and hornbeam saplings were more abundant than oak saplings regardless of soil conditions (on average, 3097, 3063 and 344 saplings ha−1, respectively), suggesting a strong competitive ability of these two species. Oak was present on 22% (43% for hornbeam and 68% for beech) of the studied plots, at a low density but with a height and DBH similar to that of beech or hornbeam. This result highlights the high dissemination capacity of beech and hornbeam, which prevents the establishment of a stand dominated by oak. When seeking to obtain oak-dominated stands in the lowlands of Europe, the abundance of beech and hornbeam can be a limiting factor that could lead to the disappearance of oak from large areas if no silvicultural operations are performed to promote it. Numéro de notice : A2022-012 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119758 Date de publication en ligne : 09/10/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119758 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99069
in Forest ecology and management > vol 503 (January-1 2022) . - n° 119758[article]
Titre : Cartographier l'anthropocène 2022 : Altas IGN - Changer d'échelle pour pouvoir agir Type de document : Atlas/Carte Auteurs : IGN, Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2022 Importance : 86 p. Format : 31 x 21,5 cm Langues : Français (fre) Descripteur : [Vedettes matières IGN] Environnement
[Termes IGN] biodiversité
[Termes IGN] catastrophe naturelle
[Termes IGN] érosion côtière
[Termes IGN] forêt
[Termes IGN] surface imperméableIndex. décimale : 42.40 Histoire IGN Numéro de notice : 24112 Affiliation des auteurs : IGN (2020- ) Thématique : BIODIVERSITE/FORET/GEOMATIQUE/IMAGERIE Nature : Atlas En ligne : https://www.ign.fr/publications-de-l-ign/institut/kiosque/publications/atlas_ant [...] Format de la ressource électronique : URL Sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103615 Réservation
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Atlas Anthropocène 2022Adobe Acrobat PDF Characteristics of taiga and tundra snowpack in development and validation of remote sensing of snow / Henna-Reetta Hannula (2022)
Titre : Characteristics of taiga and tundra snowpack in development and validation of remote sensing of snow Type de document : Thèse/HDR Auteurs : Henna-Reetta Hannula, Auteur Editeur : Helsinki [Finland] : University of Helsinki Année de publication : 2022 Importance : 79 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-952-336-153-9 Note générale : Bibliographie
Academic dissertation, Faculty of Science, University of HelsinkiLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] carte thématique
[Termes IGN] changement climatique
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] distribution spatiale
[Termes IGN] données spatiotemporelles
[Termes IGN] échantillonnage de données
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] image infrarouge
[Termes IGN] manteau neigeux
[Termes IGN] problème inverse
[Termes IGN] réflectance spectrale
[Termes IGN] taïga
[Termes IGN] toundraRésumé : (auteur) Remote sensing of snow is a method to measure snow cover characteristics without direct physical contact with the target from airborne or space-borne platforms. Reliable estimates of snow cover extent and snow properties are vital for several applications including climate change research and weather and hydrological forecasting. Optical remote sensing methods detect the extent of snow cover based on its high reflectivity compared to other natural surfaces. A universal challenge for snow cover mapping is the high spatiotemporal variability of snow properties and heterogeneous landscapes such as the boreal forest biome. The optical satellite sensor’s footprint may extend from tens of meters to a kilometer; the signal measured by the sensor can simultaneously emerge from several target categories within individual satellite pixels. By use of spectral unmixing or inverse model-based methods, the fractional snow cover (FSC) within the satellite image pixel can be resolved from the recorded electromagnetic signal. However, these algorithms require knowledge of the spectral reflectance properties of the targets present within the satellite scene and the accuracy of snow cover maps is dependent on the feasibility of these spectral model parameters. On the other hand, abrupt changes in land cover types with large differences in their snow properties may be located within a single satellite image pixel and complicate the interpretation of the observations. Ground-based in-situ observations can be used to validate the snow parameters derived by indirect methods, but these data are affected by the chosen sampling. This doctoral thesis analyses laboratory-based spectral reflectance information on several boreal snow types for the purpose of the more accurate reflectance representation of snow in mapping method used for the detection of fractional snow cover. Multi-scale reflectance observations representing boreal spectral endmembers typically used in optical mapping of snow cover, are exploited in the thesis. In addition, to support the interpretation of remote sensing observations in boreal and tundra environments, extensive in-situ dataset of snow depth, snow water equivalent and snow density are exploited to characterize the snow variability and to assess the uncertainty and representativeness of these point-wise snow measurements applied for the validation of remote sensing observations. The overall goal is to advance knowledge about the spectral endmembers present in boreal landscape to improve the accuracy of the FSC estimates derived from the remote sensing observations and support better interpretation and validation of remote sensing observations over these heterogeneous landscapes. The main outcome from the work is that laboratory-controlled experiments that exclude disturbing factors present in field circumstances may provide more accurate representation of wet (melting) snow endmember reflectance for the FSC mapping method. The behavior of snow band reflectance is found to be insensitive to width and location differences between visible satellite sensor bands utilized in optical snow cover mapping which facilitates the use of various sensors for the construction of historical data records. The results also reveal the high deviation of snow reflectance due to heterogeneity in snow macro- and microstructural properties. The quantitative statistics of bulk snow properties show that areal averages derived from in-situ measurements and used to validate remote sensing observations are dependent on the measurement spacing and sample size especially over land covers with high absolute snow depth variability, such as barren lands in tundra. Applying similar sampling protocol (sample spacing and sample size) over boreal and tundra land cover types that represent very different snow characteristics will yield to non-equal representativeness of the areal mean values. The extensive datasets collected for this work demonstrate that observations measured at various scales can provide different view angle to the same challenge but at the same time any dataset individually cannot provide a full understanding of the target complexity. This work and the collected datasets directly facilitate further investigation of uncertainty in fractional snow cover maps retrieved by optical remote sensing and the interpretation of satellite observations in boreal and tundra landscapes. Note de contenu : 1. Introduction
2. Snow and its properties
3. Multispectral optical remote sensing of snow
4. Study site, datasets and methods
5. Results and discussion
6. Conclusions and future workNuméro de notice : 24060 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Thesis : Sciences : University of Helsinki : 2022 DOI : 10.35614/isbn.9789523361522 En ligne : https://doi.org/10.35614/isbn.9789523361522 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101997 Classification of mediterranean shrub species from UAV point clouds / Juan Pedro Carbonell-Rivera in Remote sensing, vol 14 n° 1 (January-1 2022)
[article]
Titre : Classification of mediterranean shrub species from UAV point clouds Type de document : Article/Communication Auteurs : Juan Pedro Carbonell-Rivera, Auteur ; Jesus Torralba, Auteur ; Javier Estornell, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 199 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage automatique
[Termes IGN] arbuste
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] Espagne
[Termes IGN] Extreme Gradient Machine
[Termes IGN] forêt méditerranéenne
[Termes IGN] image captée par drone
[Termes IGN] incendie de forêt
[Termes IGN] indice de végétation
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de terrain
[Termes IGN] parc naturel
[Termes IGN] photogrammétrie aérienne
[Termes IGN] semis de pointsRésumé : (auteur) Modelling fire behaviour in forest fires is based on meteorological, topographical, and vegetation data, including species’ type. To accurately parameterise these models, an inventory of the area of analysis with the maximum spatial and temporal resolution is required. This study investigated the use of UAV-based digital aerial photogrammetry (UAV-DAP) point clouds to classify tree and shrub species in Mediterranean forests, and this information is key for the correct generation of wildfire models. In July 2020, two test sites located in the Natural Park of Sierra Calderona (eastern Spain) were analysed, registering 1036 vegetation individuals as reference data, corresponding to 11 shrub and one tree species. Meanwhile, photogrammetric flights were carried out over the test sites, using a UAV DJI Inspire 2 equipped with a Micasense RedEdge multispectral camera. Geometrical, spectral, and neighbour-based features were obtained from the resulting point cloud generated. Using these features, points belonging to tree and shrub species were classified using several machine learning methods, i.e., Decision Trees, Extra Trees, Gradient Boosting, Random Forest, and MultiLayer Perceptron. The best results were obtained using Gradient Boosting, with a mean cross-validation accuracy of 81.7% and 91.5% for test sites 1 and 2, respectively. Once the best classifier was selected, classified points were clustered based on their geometry and tested with evaluation data, and overall accuracies of 81.9% and 96.4% were obtained for test sites 1 and 2, respectively. Results showed that the use of UAV-DAP allows the classification of Mediterranean tree and shrub species. This technique opens a wide range of possibilities, including the identification of species as a first step for further extraction of structure and fuel variables as input for wildfire behaviour models. Numéro de notice : A2022-057 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14010199 En ligne : https://doi.org/10.3390/rs14010199 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99462
in Remote sensing > vol 14 n° 1 (January-1 2022) . - n° 199[article]A comparison of linear-mode and single-photon airborne LiDAR in species-specific forest inventories / Janne Raty in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)
[article]
Titre : A comparison of linear-mode and single-photon airborne LiDAR in species-specific forest inventories Type de document : Article/Communication Auteurs : Janne Raty, Auteur ; Petri Varvia, Auteur ; Lauri Korhonen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4401514 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] altitude
[Termes IGN] analyse comparative
[Termes IGN] capteur linéaire
[Termes IGN] carte de la végétation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] instrumentation Leica
[Termes IGN] instrumentation Riegl
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] photon
[Termes IGN] Pinophyta
[Termes IGN] semis de points
[Termes IGN] signal laserRésumé : (auteur) Single-photon airborne light detection and ranging (LiDAR) systems provide high-density data from high flight altitudes. We compared single-photon and linear-mode airborne LiDAR for the prediction of species-specific volumes in boreal coniferous-dominated forests. The LiDAR data sets were acquired at different flight altitudes using Leica SPL100 (single-photon, 17 points ⋅ m−2 ), Riegl VQ-1560i (linear-mode, 11 points ⋅ m−2 ), and Leica ALS60 (linear-mode, 0.6 points ⋅ m−2 ) LiDAR systems. Volumes were predicted at the plot-level using Gaussian process regression with predictor variables extracted from the LiDAR data sets and aerial images. Our findings showed that the Leica SPL100 produced a greater mean root-mean-squared error (RMSE) value (41.7 m3 ⋅ ha −1 ) than the Leica ALS60 (39.3 m3 ⋅ ha −1 ) in the prediction of species-specific volumes. Correspondingly, the Riegl VQ-1560i (mean RMSE = 33.0 m3 ⋅ ha −1 ) outperformed both the Leica ALS60 and the Leica SPL100. We found that the cumulative distributions of the first echo heights >1.3 m were rather similar among the data sets, whereas the last echo distributions showed larger differences. We conclude that the Leica SPL100 data set is suitable for area-based LiDAR inventory by tree species although the prediction errors are greater than with data obtained using the modern linear-mode LiDAR, such as Riegl VQ-1560i. Numéro de notice : A2022-026 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1109/TGRS.2021.3060670 Date de publication en ligne : 04/03/2021 En ligne : https://doi.org/10.1109/TGRS.2021.3060670 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99257
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 1 (January 2022) . - n° 4401514[article]Contributions of multi-temporal airborne LiDAR data to mapping carbon stocks and fluxes in tropical forests / Claudia Milena Huertas Garcia (2022)PermalinkPermalinkDetection and biomass estimation of phaeocystis globosa blooms off Southern China from UAV-based hyperspectral measurements / Xue Li in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkDetection of windthrown tree stems on UAV-orthomosaics using U-Net convolutional networks / Stefan Reder in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkDeveloping the potential of airborne lidar systems for the sustainable management of forests / Karun Dayal (2022)PermalinkEffets des bryophytes sur les microsites de régénération forestière en climat tempéré / Laura Chevaux (2022)PermalinkÉléments pour l'analyse et le traitement d'images : application à l'estimation de la qualité du bois / Rémy Decelle (2022)PermalinkEstimating aboveground biomass in dense Hyrcanian forests by the use of Sentinel-2 data / Fardin Moradi in Forests, vol 13 n° 1 (January 2022)PermalinkPermalinkExamining the integration of Landsat operational land imager with Sentinel-1 and vegetation indices in mapping southern yellow pines (Loblolly, Shortleaf, and Virginia pines) / Clement E. Akumu in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 1 (January 2022)PermalinkFactors affecting winter damage and recovery of newly planted Norway spruce seedlings in boreal forests / Jaana Luoranen in Forest ecology and management, vol 503 (January-1 2022)PermalinkPermalinkPermalinkPermalinkFungal perspective of pine and oak colonization in Mediterranean degraded ecosystems / Irene Adamo in Forests, vol 13 n° 1 (January 2022)PermalinkGenetic diversity of sessile oak populations in the Czech Republic / Jakub Dvořák in Journal of forest science, vol 68 n° 1 (January 2022)PermalinkGeospatial assessment of urban ecosystem disservices: An example of poisonous urban trees in Berlin, Germany / Peer von Döhren in Urban Forestry & Urban Greening, vol 67 (January 2022)PermalinkGlobal canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles / Nico Lang in Remote sensing of environment, vol 268 (January 2022)PermalinkHigh-resolution canopy height map in the Landes forest (France) based on GEDI, Sentinel-1, and Sentinel-2 data with a deep learning approach / Martin Schwartz (2022)PermalinkPermalinkImportance des facteurs locaux climatiques et édaphiques dans la dynamique de régénération des communautés à hêtre en marge d’aire de répartition / Ludovic Lacombe (2022)PermalinkInvestigating the role of wind disturbance in tropical forests through a forest dynamics model and satellite observations / E-Ping Rau (2022)PermalinkItalian National Forest Inventory: Methods and results of the third survey / Patrizia Gasparini (2022)PermalinkLatent heat flux variability and response to drought stress of black poplar: A multi-platform multi-sensor remote and proximal sensing approach to relieve the data scarcity bottleneck / Flavia Tauro in Remote sensing of environment, vol 268 (January 2022)PermalinkLe mémento inventaire forestier, édition 2021 / Institut national de l'information géographique et forestière (2012 -) (2022)PermalinkMonitoring forest-savanna dynamics in the Guineo-Congolian transition area of the centre region of Cameroon / Le Bienfaiteur Sagang Takougoum (2022)PermalinkMonitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies / Guangqin Song in ISPRS Journal of photogrammetry and remote sensing, vol 183 (January 2022)PermalinkPermalinkPermalinkNew insights in the modeling and simulation of tree and stand level variables in Mediterranean mixed forests in the present context of climate change / Diego Rodríguez de Prado (2022)PermalinkPlanning coastal Mediterranean stone pine (Pinus pinea L.) reforestations as a green infrastructure: combining GIS techniques and statistical analysis to identify management options / Luigi Portoghesi in Annals of forest research, vol 65 n° 1 (January - June 2022)PermalinkPermalinkRegeneration of spruce - fir - beech mixed forests under climate and ungulate pressure / Mithila Unkule (2022)PermalinkPermalinkSelf-attention and generative adversarial networks for algae monitoring / Nhut Hai Huynh in European journal of remote sensing, vol 55 n° 1 (2022)PermalinkSenRVM: A multi-modal deep learning regression methodology for continuous vegetation monitoring with dense temporal NDVI time series / Anatol Garioud (2022)PermalinkLa situation des forêts du monde 2022 : Des solutions forestières pour une relance verte et des économies inclusives, résilientes et durables / Organisation des Nations Unies pour l'alimentation et l'agriculture (Rome, Italie) (2022)PermalinkA square-grid sampling support to reconcile systematicity and adaptivity in the periodic spatial survey of natural resources / Olivier Bouriaud (2022)PermalinkPermalinkThe long-term development of temperate woodland creation sites: from tree saplings to mature woodlands / Elisa Fuentes-Montemayor in Forestry, an international journal of forest research, vol 95 n° 1 (January 2022)PermalinkUnderstory plant community responses to widespread spruce mortality in a subalpine forest / Trevor A. Carter in Journal of vegetation science, vol 33 n° 1 (January 2022)PermalinkVegetation changes in the understory of nitrogen-sensitive temperate forests over the past 70 years / Marina Roth in Forest ecology and management, vol 503 (January-1 2022)PermalinkPermalinkEstimating timber volume loss due to storm damage in Carinthia, Austria, using ALS/TLS and spatial regression models / Arne Nothdurft in Forest ecology and management, vol 502 (December-15 2021)PermalinkMapping temperate forest tree species using dense Sentinel-2 time series / Jan Hemmerling in Remote sensing of environment, vol 267 (December-15 2021)Permalink