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Termes IGN > foresterie > sylviculture > déboisement
déboisement
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déforestage, déforestation. défrichement, sylviculture. >> reboisement, coupe à blanc. Equiv. LCSH : Deforestation. Domaine(s) : 580, 630. Synonyme(s)déforestationVoir aussi |
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Resilience of Pyrenean forests after recurrent historical deforestations / Valenti Rull in Forests, vol 14 n° 3 (March 2023)
[article]
Titre : Resilience of Pyrenean forests after recurrent historical deforestations Type de document : Article/Communication Auteurs : Valenti Rull, Auteur ; Teresa Vegas-Vilarrúbia, Auteur Année de publication : 2023 Article en page(s) : n° 567 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] déboisement
[Termes IGN] forêt méditerranéenne
[Termes IGN] histoire
[Termes IGN] historique des données
[Termes IGN] régénération (sylviculture)
[Termes IGN] résilience écologique
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) The long-term resilience of Pyrenean forests in the face of historical anthropogenic clearing remains largely unknown. In this paper, a high-resolution (decadal to subdecadal) paleoecological study of mid-elevation Pyrenean forests is presented that encompasses the last two millennia. This long-term record was obtained after sediment coring, dating (varve counting) and pollen analysis of annually laminated (varved) sediments from Lake Montcortès, situated at 1027 m elevation, in the transition between the Mediterranean and montane forest belts. This allowed the definition of three major deforestation/recovery cycles during the Roman, Medieval and Modern times. Each DR cycle is characterized considering three different levels: overall forest trends, forest type and individual taxa. Overall, the studied forests exhibited high resilience, as they recovered almost completely after each deforestation event (bulk resilience). The critical point of no return (tipping point) beyond which forests would have irreversibly disappeared from the region was never reached, even after deforestation magnitudes above 60%. The different forest types identified (conifer, sclerophyll and deciduous) persisted over time, showing similar heterogeneous patterns with minor spatial reorganizations (mosaic resilience). Individually, the main forest taxa underwent minor variations in their relative abundances, always within the same attraction domains (community resilience). The high levels of resilience documented in these Pyrenean forests are attributed to the action of metapopulation and metacommunity processes and mechanisms in a highly dynamic patchy environment. Conservation actions should be focused on the maintenance of these spatial patterns and the associated ecological dynamics. Numéro de notice : A2023-166 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f14030567 Date de publication en ligne : 13/03/2023 En ligne : https://doi.org/10.3390/f14030567 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102903
in Forests > vol 14 n° 3 (March 2023) . - n° 567[article]Prescribed fire after thinning increased resistance of sub-Mediterranean pine forests to drought events and wildfires / Lena Vilà-Vilardell in Forest ecology and management, vol 527 (January-1 2023)
[article]
Titre : Prescribed fire after thinning increased resistance of sub-Mediterranean pine forests to drought events and wildfires Type de document : Article/Communication Auteurs : Lena Vilà-Vilardell, Auteur ; Miquel De Cáceres, Auteur ; Míriam Piqué, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120602 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] brûlis
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] incendie de forêt
[Termes IGN] Pinus nigra
[Termes IGN] sécheresse
[Termes IGN] sous-étage
[Termes IGN] stress hydrique
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] vulnérabilité
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Vegetation structure affects the vulnerability of a forest to drought events and wildfires. Management decisions, such as thinning intensity and type of understory treatment, influence competition for water resources and amount of fuel available. While heavy thinning effectively reduces tree water stress and intensity of a crown fire, the duration of these benefits may be limited by a fast growth response of the understory. Our aim was to study the effect of forest structure on pine forests vulnerability to extreme drought events and on the potential wildfire behaviour after management, with a special focus on the role of the understory. In three sub-Mediterranean sites of NE Spain dominated by Pinus nigra, two intensities of thinning (light: aiming at 70–75% canopy cover; and heavy: aiming at 50–60% canopy cover) followed by two understory treatments (mechanical only and mechanical plus prescribed burning) were applied, resulting in four differently managed stands plus an untreated control per site. Four to five years after management, we measured forest structure (overstory in one 314 m2 circular plot and understory in 20 quadrats of 1 m2 per treatment unit) and fuel load (in two 10 m transects per treatment unit) and simulated water balance and fire behaviour under extreme weather conditions. Understory contribution was assessed comparing the real structure with a virtual forest stand where understory vegetation equalled the one of the untreated control. Our results suggest that the resulting mid-term structure following treatments effectively reduced water stress and fire behaviour compared with untreated control, and that the most effective treatments were the ones where prescribed burning was applied after light or heavy thinning. While understory clearing contributes to increase the resistance to both disturbances, an additive effect of burning the debris reduced the vulnerability to drought and wildfires after treatments. Our study highlights the importance of managing the understory to further increase forest resistance to both disturbances. Numéro de notice : A2023-030 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120602 Date de publication en ligne : 08/11/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120602 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102109
in Forest ecology and management > vol 527 (January-1 2023) . - n° 120602[article]Forêt amazonienne : de nouveau sous contrôle ? / Laurent Polidori in Géomètre, n° 2208 (décembre 2022)
[article]
Titre : Forêt amazonienne : de nouveau sous contrôle ? Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2022 Article en page(s) : pp 24 - 24 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Amazonie
[Termes IGN] déboisement
[Termes IGN] forêt
[Termes IGN] incendie de forêt
[Termes IGN] télédétection spatialeRésumé : (Auteur) La forêt amazonienne s’est encore trouvée au centre de toutes les attentions lors de la COP27 qui vient de se tenir en Egypte, compte tenu de son rôle essentiel dans l’évolution du climat mondial. Mais 2022 était une année atypique. Numéro de notice : A2022-806 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/12/2022 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102191
in Géomètre > n° 2208 (décembre 2022) . - pp 24 - 24[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]Scorch height and volume modeling in prescribed fires: Effects of canopy gaps in Pinus pinaster stands in Southern Europe / J.R. Molina in Forest ecology and management, vol 506 (February-15 2022)
[article]
Titre : Scorch height and volume modeling in prescribed fires: Effects of canopy gaps in Pinus pinaster stands in Southern Europe Type de document : Article/Communication Auteurs : J.R. Molina, Auteur ; M. Ortega, Auteur ; F. Rodríguez y Silva, Auteur Année de publication : 2022 Article en page(s) : n° 119979 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] brûlis
[Termes IGN] canopée
[Termes IGN] échantillonnage de données
[Termes IGN] Espagne
[Termes IGN] gestion des risques
[Termes IGN] gestion forestière
[Termes IGN] incendie de forêt
[Termes IGN] Pinus pinaster
[Vedettes matières IGN] ForesterieRésumé : (auteur) The use of prescribed fire has been on the rise in recent years owing to its effectiveness in surface fuel reduction, its implementation cost, and the possibility of firefighter training. However, greater knowledge regarding the effects of fire on woodlands is required by forest managers. Scorch height and scorch volume are the most widely used variables for evaluating the effects of burning on trees. This study proposes a scorch height model for the prescribed fires of pine stands in Southern Europe. Although the two main variables of the existing models (fire-line intensity and air temperature) were considered, our model achieved a coefficient of determination of 89% with the incorporation of the canopy base height. A decision tree for scorch volume was also developed using the three independent variables. The presence of canopy gaps in the lower, mid-, and upper slopes resulted in significant differences in the scorch height. The scorch height increased between 0.33 m and 2.08 m because of the canopy gaps in the upper slope. These findings can play an important role in the implementation and improvement of prescribed burn windows. Numéro de notice : A2022-058 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2021.119979 Date de publication en ligne : 24/12/2021 En ligne : https://doi.org/10.1016/j.foreco.2021.119979 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99469
in Forest ecology and management > vol 506 (February-15 2022) . - n° 119979[article]Monthly mapping of forest harvesting using dense time series Sentinel-1 SAR imagery and deep learning / Feng Zhao in Remote sensing of environment, vol 269 (February 2022)PermalinkAn assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 / Darius Phiri in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkPermalinkPrescribed burning as a cost-effective way to address climate change and forest management in Mediterranean countries / Renata Martins Pacheco in Annals of Forest Science, vol 78 n° 4 (December 2021)PermalinkProgress on incorporating biodiversity monitoring in REDD+ through national forest inventories / Loïc Gillerot in Global ecology and conservation, vol 32 (December 2021)PermalinkSemantic unsupervised change detection of natural land cover with multitemporal object-based analysis on SAR images / Donato Amitrano in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 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)PermalinkApport des données Sentinel-1 pour le suivi continu de la forêt tropicale : Cas de la Guyane / Marie Ballère (2021)PermalinkImpact of forest disturbance on InSAR surface displacement time series / Paula M. Bürgi in IEEE Transactions on geoscience and remote sensing, vol 59 n° 1 (January 2021)PermalinkIntegrating multilayer perceptron neural nets with hybrid ensemble classifiers for deforestation probability assessment in Eastern India / Sunil Saha in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)Permalink