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Termes IGN > foresterie > sylviculture
sylviculture
Commentaire :
Arboriculture, Arboriculture forestière, Arbres -- Techniques culturales, Cultures forestières, Forêts -- Techniques culturales, Forêts et sylviculture, Techniques forestières. Agriculture. >> Industrie forestière, Bois, Forêt -- Exploitation, Forêt, Machine forestière. Voir aussi les vedettes commençant par Forêts ; Foresterie ; Sylviculture. >>Terme(s) spécifique(s) : Écorçage, Martelage (sylviculture), Arbre -- Abattage, Déboisement, Déchet d'abattage, Dendrométrie, Inventaire forestier, Route forestière, Station forestière -- Typologie, Sylviculture tropicale, Essartage, Éclaircie (sylviculture), Cloisonnement (sylviculture), Coupe à blanc, Dégagement (sylviculture). Equiv. LCSH : Forest and forestry. |
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Detecting overmature forests with airborne laser scanning (ALS) / Marc Fuhr in Remote sensing in ecology and conservation, vol 8 n° 5 (October 2022)
[article]
Titre : Detecting overmature forests with airborne laser scanning (ALS) Type de document : Article/Communication Auteurs : Marc Fuhr, Auteur ; Etienne Lalechère, Auteur ; Jean-Matthieu Monnet, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 731 - 743 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Abies alba
[Termes IGN] âge du peuplement forestier
[Termes IGN] Bootstrap (statistique)
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] coefficient de corrélation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Fagus sylvatica
[Termes IGN] Picea abies
[Termes IGN] Préalpes (France)
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestierRésumé : (auteur) Building a network of interconnected overmature forests is crucial for the conservation of biodiversity. Indeed, a multitude of plant and animal species depend on forest structural maturity attributes such as very large living trees and deadwood. LiDAR technology has proved to be powerful when assessing forest structural parameters, and it may be a promising way to identify existing overmature forest patches over large areas. We first built an index (IMAT) combining several forest structural maturity attributes in order to characterize the structural maturity of 660 field plots in the French northern Pre-Alps. We then selected or developed LiDAR metrics and applied them in a random forest model designed to predict the IMAT. Model performance was evaluated with the root mean square error of prediction obtained from a bootstrap cross-validation and a Spearman correlation coefficient calculated between observed and predicted IMAT. Predictors were ranked by importance based on the average increase in the squared out-of-bag error when the variable was randomly permuted. Despite a non-negligible RMSEP (0.85 for calibration and validation data combined and 1.26 for validation data alone), we obtained a high correlation (0.89) between the observed and predicted IMAT values, indicating an accurate ranking of the field plots. LiDAR metrics for height (maximum height and height heterogeneity) were among the most important metrics for predicting forest maturity, together with elevation, slope and, to a lesser extent, with metrics describing the distribution of echoes' intensities. Our framework makes it possible to reconstruct a forest maturity gradient and isolate maturity hot spots. Nevertheless, our approach could be considerably strengthened by taking into consideration site fertility, collecting other maturity attributes in the field or developing adapted LiDAR metrics. Including additional spectral or textural metrics from optical imagery might also improve the predictive capacity of the model. Numéro de notice : A2022-880 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1002/rse2.274 Date de publication en ligne : 15/07/2022 En ligne : https://doi.org/10.1002/rse2.274 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102197
in Remote sensing in ecology and conservation > vol 8 n° 5 (October 2022) . - pp 731 - 743[article]Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learning / J.F. Roberts in Computers & geosciences, vol 167 (October 2022)
[article]
Titre : Pyeo: A Python package for near-real-time forest cover change detection from Earth observation using machine learning Type de document : Article/Communication Auteurs : J.F. Roberts, Auteur ; R. Mwangi, Auteur ; F. Mukabi, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 105192 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] carte thématique
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] image Sentinel-MSI
[Termes IGN] informatique en nuage
[Termes IGN] Kenya
[Termes IGN] langage de programmation
[Termes IGN] observation de la Terre
[Termes IGN] Python (langage de programmation)
[Termes IGN] surveillance forestièreRésumé : (auteur) Monitoring forest cover change from Earth observation data streams in near-real-time presents a challenge for automated change detection by way of a continuously updated big dataset. Even though deforestation is a significant global problem, forest cover changes in pairs of subsequent images happen relatively infrequently. Detecting a change can require the download and processing of tens, hundreds or even thousands of images. In geoscientific applications of Earth observation, machine learning algorithms are increasingly used. Once trained, a machine learning model can be applied to new images automatically. This paper introduces the open-access Python 3 package Pyeo - “Python for Earth Observation”. Pyeo provides a set of portable, extensible and modular Python functions for the automation of machine learning applications from Earth observation data streams, including automated search and download functionality, pre-processing and atmospheric correction, re-projection, creation of thematic base layers and machine learning classification or regression. Pyeo enables users to train their own machine learning models and then apply the models to newly downloaded imagery over their area of interest. This paper describes in detail how Pyeo works, its requirements, benefits, and a description of the libraries used. An application to the automated forest cover change detection in a region in Kenya is given. Pyeo can be used on cloud computing architectures such as Amazon Web Services, Microsoft Azure and Google Colab to provide scalable applications and processing solutions for the geosciences. Numéro de notice : A2022-706 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2022.105192 Date de publication en ligne : 09/07/2022 En ligne : https://doi.org/10.1016/j.cageo.2022.105192 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101575
in Computers & geosciences > vol 167 (October 2022) . - n° 105192[article]Increasing and widespread vulnerability of intact tropical rainforests to repeated droughts / Shengli Tao in Proceedings of the National Academy of Sciences of the United States of America PNAS, vol 119 n° 37 (2022)
[article]
Titre : Increasing and widespread vulnerability of intact tropical rainforests to repeated droughts Type de document : Article/Communication Auteurs : Shengli Tao, Auteur ; Jérôme Chave, Auteur ; Pierre-Louis Frison , Auteur ; et al., Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : n° e2116626119 Note générale : bibliographie
This study was supported by an Investissement d’Avenir grant managed by the Agence Nationale de la Recherche (CEBA, ref. ANR-10-LABX-25-01; TULIP, ref. ANR-10-LABX-0041; ANAEE-France: ANR-11-INBS-0001), and by the National Natural Science Foundation of China (grant no. 31988102). This research was also supported by a Centre National d' Etudes Spatiales (CNES) postdoctoral fellowship to S.T., the CNES-BIOMASS pluriannual project, and the European Space Agency (ESA) Climate Change Initiative (CCI) Biomass project (contract no. 4000123662/18/I-NB).Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] forêt tropicale
[Termes IGN] image radar
[Termes IGN] sécheresse
[Termes IGN] série temporelle
[Termes IGN] vulnérabilitéRésumé : (auteur) Intact tropical rainforests have been exposed to severe droughts in recent decades, which may threaten their integrity, their ability to sequester carbon, and their capacity to provide shelter for biodiversity. However, their response to droughts remains uncertain due to limited high-quality, long-term observations covering extensive areas. Here, we examined how the upper canopy of intact tropical rainforests has responded to drought events globally and during the past 3 decades. By developing a long pantropical time series (1992 to 2018) of monthly radar satellite observations, we show that repeated droughts caused a sustained decline in radar signal in 93%, 84%, and 88% of intact tropical rainforests in the Americas, Africa, and Asia, respectively. Sudden decreases in radar signal were detected around the 1997–1998, 2005, 2010, and 2015 droughts in tropical Americas; 1999–2000, 2004–2005, 2010–2011, and 2015 droughts in tropical Africa; and 1997–1998, 2006, and 2015 droughts in tropical Asia. Rainforests showed similar low resistance (the ability to maintain predrought condition when drought occurs) to severe droughts across continents, but American rainforests consistently showed the lowest resilience (the ability to return to predrought condition after the drought event). Moreover, while the resistance of intact tropical rainforests to drought is decreasing, albeit weakly in tropical Africa and Asia, forest resilience has not increased significantly. Our results therefore suggest the capacity of intact rainforests to withstand future droughts is limited. This has negative implications for climate change mitigation through forest-based climate solutions and the associated pledges made by countries under the Paris Agreement. Numéro de notice : A2022-681 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : vers HAL Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1073/pnas.2116626119 En ligne : https://doi.org/10.1073/pnas.2116626119 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101538
in Proceedings of the National Academy of Sciences of the United States of America PNAS > vol 119 n° 37 (2022) . - n° e2116626119[article]Tree regeneration in models of forest dynamics – Suitability to assess climate change impacts on European forests / Louis A. König in Forest ecology and management, vol 520 (September-15 2022)
[article]
Titre : Tree regeneration in models of forest dynamics – Suitability to assess climate change impacts on European forests Type de document : Article/Communication Auteurs : Louis A. König, Auteur ; Frits Mohren, Auteur ; Mart-Jan Schelhaas, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120390 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] dépérissement
[Termes IGN] dynamique de la végétation
[Termes IGN] écosystème forestier
[Termes IGN] Europe (géographie politique)
[Termes IGN] germination
[Termes IGN] gestion forestière durable
[Termes IGN] graine
[Termes IGN] jeune arbre
[Termes IGN] modélisation de la forêt
[Termes IGN] pollen
[Termes IGN] régénération (sylviculture)
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Climate change impacts on Europe’s forests are becoming visible much sooner than previously anticipated. The increase in natural disturbances leads to tree mortality and raises concerns about the forest’s adaptive potential to sustain vital ecosystem services. In this context, the regeneration phase is crucial and comprises the largest potential to adapt to new environmental conditions with long lasting implications. Yet, forest regeneration is particularly susceptible to climatic changes due to the many directly climate-dependent processes, such as seed production and germination but also seedling and sapling development. Models of forest dynamics (MFDs) are essential to describe, understand and predict the effects of changing environmental and management factors on forest dynamics and subsequently on associated ecosystem services. We review a large variety of MFDs with regard to their representation and climate sensitivity of regeneration processes. Starting with a description of the underlying biological processes, we evaluate the various approaches taking into account specific model purposes, and provide recommendations for future developments. We distinguish between models based on ecological principles and models based on empirical relationships. We found an ample mix of regeneration modelling approaches tailored to different model purposes. We conclude that current approaches should be refined to adequately capture altered regeneration trends. Specifically, refinement is needed for MFDs that rely on ecological principals, as they suffer from knowledge gaps and underrepresented processes, thereby limiting their ability to accurately simulate forest regeneration under climate change. Global vegetation models are strongly constrained by their weak representation of vegetation structure and composition, and need to include more detail regarding structural complexity and functional diversity. Models focused on timber yield often rely on strong assumptions regarding the abundance and composition of the next tree generation, which may no longer hold true with changes in climate and forest management. With the increased utilization of natural regeneration as a source of forest renewal, more dynamic representations of tree regeneration are needed. Our review highlights the necessity to increase the data basis to close knowledge gaps and to enable the adequate incorporation and parameterization of the involved processes. This would allow to capture altered regeneration patterns and subsequent effects on forest structure, composition and, ultimately, forest functioning under climate change. Numéro de notice : A2022-556 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120390 Date de publication en ligne : 05/07/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120390 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101170
in Forest ecology and management > vol 520 (September-15 2022) . - n° 120390[article]Assessing the impact of forest structure disturbances on the arboreal movement and energetics of orangutans : An agent-based modeling approach / Kirana Widyastuti in Frontiers in Ecology and Evolution, vol 2022 ([01/09/2022])
[article]
Titre : Assessing the impact of forest structure disturbances on the arboreal movement and energetics of orangutans : An agent-based modeling approach Type de document : Article/Communication Auteurs : Kirana Widyastuti, Auteur ; Romain Reuillon, Auteur ; Paul Chapron , Auteur ; Wildan Abdussalam, Auteur ; Darmae Nasir, Auteur ; Mark E. Harrison, Auteur ; Helen Morrogh-Bernard, Auteur ; Muhammad Ali Imron, Auteur ; Uta Berger, Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : n° 983337 Note générale : bibliographie
This research is part of a project funded by UK Research and Innovation (UKRI) through the Global Challenges Research Fund (GCRF), grant number NE/T010401/1.Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de sensibilité
[Termes IGN] analyse multicritère
[Termes IGN] forêt tropicale
[Termes IGN] habitat animal
[Termes IGN] impact sur l'environnement
[Termes IGN] modèle orienté agent
[Termes IGN] SimiiformesRésumé : (auteur) Agent-based models have been developed and widely employed to assess the impact of disturbances or conservation management on animal habitat use, population development, and viability. However, the direct impacts of canopy disturbance on the arboreal movement of individual primates have been less studied. Such impacts could shed light on the cascading effects of disturbances on animal health and fitness. Orangutans are an arboreal primate that commonly encounters habitat quality deterioration due to land-use changes and related disturbances such as forest fires. Forest disturbance may, therefore, create a complex stress scenario threatening orangutan populations. Due to forest disturbances, orangutans may adapt to employ more terrestrial, as opposed to arboreal, movements potentially prolonging the search for fruiting and nesting trees. In turn, this may lead to changes in daily activity patterns (i.e., time spent traveling, feeding, and resting) and available energy budget, potentially decreasing the orangutan's fitness. We developed the agent-based simulation model BORNEO (arBOReal aNimal movEment mOdel), which explicitly describes both orangutans' arboreal and terrestrial movement in a forest habitat, depending on distances between trees and canopy structures. Orangutans in the model perform activities with a motivation to balance energy intake and expenditure through locomotion. We tested the model using forest inventory data obtained in Sebangau National Park, Central Kalimantan, Indonesia. This allowed us to construct virtual forests with real characteristics including tree connectivity, thus creating the potential to expand the environmental settings for simulation experiments. In order to parameterize the energy related processes of the orangutans described in the model, we applied a computationally intensive evolutionary algorithm and evaluated the simulation results against observed behavioral patterns of orangutans. Both the simulated variability and proportion of activity budgets including feeding, resting, and traveling time for female and male orangutans confirmed the suitability of the model for its purpose. We used the calibrated model to compare the activity patterns and energy budgets of orangutans in both natural and disturbed forests . The results confirm field observations that orangutans in the disturbed forest are more likely to experience deficit energy balance due to traveling to the detriment of feeding time. Such imbalance is more pronounced in males than in females. The finding of a threshold of forest disturbances that affects a significant change in activity and energy budgets suggests potential threats to the orangutan population. Our study introduces the first agent-based model describing the arboreal movement of primates that can serve as a tool to investigate the direct impact of forest changes and disturbances on the behavior of species such as orangutans. Moreover, it demonstrates the suitability of high-performance computing to optimize the calibration of complex agent-based models describing animal behavior at a fine spatio-temporal scale (1-m and 1-s granularity). Numéro de notice : A2022-689 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : BIODIVERSITE/FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3389/fevo.2022.983337 Date de publication en ligne : 23/09/2022 En ligne : https://doi.org/10.3389/fevo.2022.983337 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101678
in Frontiers in Ecology and Evolution > vol 2022 [01/09/2022] . - n° 983337[article]Effect of riparian soil moisture on bacterial, fungal and plant communities and microbial decomposition rates in boreal stream-side forests / M.J. Annala in Forest ecology and management, vol 519 (September-1 2022)PermalinkUsing multi-temporal tree inventory data in eucalypt forestry to benchmark global high-resolution canopy height models. A showcase in Mato Grosso, Brazil / Adrián Pascual in Ecological Informatics, vol 70 (September 2022)PermalinkExploring tree growth allometry using two-date terrestrial laser scanning / Tuomas Yrttimaa in Forest ecology and management, vol 518 (August-15 2022)PermalinkEstimating feature extraction changes of Berkelah Forest, Malaysia from multisensor remote sensing data using and object-based technique / Syaza Rozali in Geocarto international, vol 37 n° 11 ([15/06/2022])PermalinkHow large-scale bark beetle infestations influence the protective effects of forest stands against avalanches: A case study in the Swiss Alps / Marion E. Caduff in Forest ecology and management, vol 514 (June-15 2022)PermalinkDirect and automatic measurements of stem curve and volume using a high-resolution airborne laser scanning system / Eric Hyyppä in Science of remote sensing, vol 5 (June 2022)PermalinkFunding for planting missing species financially supports the conversion from pure even-aged to uneven-aged mixed forests and climate change mitigation / Joerg Roessinger in European Journal of Forest Research, vol 141 n° 3 (June 2022)PermalinkGreen infrastructure planning through EO and GIS analysis: the canopy plan of Liège, Belgium, to mitigate its urban heat island / Benjamin Beaumont in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2022 (2022 edition)PermalinkIndividual tree detection and estimation of stem attributes with mobile laser scanning along boreal forest roads / Raul de Paula Pires in ISPRS Journal of photogrammetry and remote sensing, vol 187 (May 2022)PermalinkSmartphone digital photography for fractional vegetation cover estimation / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 5 (May 2022)Permalink