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Tree diversity and identity modulate the growth response of thermophilous deciduous forests to climate warming / Giovanni Jacopetti in Oikos, vol 2023 n° inconnu (2023)  

Public [article]  inOikos > vol 2023 n° inconnu (2023) . - n ° e08875 Titre : Tree diversity and identity modulate the growth response of thermophilous deciduous forests to climate warming Type de document : Article/Communication Auteurs : Giovanni Jacopetti, Auteur ; Federico Selvi, Auteur ; Filippo Bussotti, Auteur ; Martina Pollastrini, Auteur ; Tommaso Jucker, Auteur ; Olivier Bouriaud , Auteur Année de publication : 2023 Projets : FunDivEUROPE / Article en page(s) : n ° e08875 Note générale : bibliographie The research leading to these results received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant 265171. Langues : Anglais (eng) Descripteur : [Termes IGN] cerne [Termes IGN] croissance des arbres [Termes IGN] forêt de feuillus [Termes IGN] forêt thermophile [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Italie [Termes IGN] richesse floristique [Termes IGN] sécheresse [Termes IGN] température au sol [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Tree diversity and species identity are known to play an important role in modulating forest productivity and its capacity to buffer the effects of climatic events. The FunDivEurope exploratory platform allowed us to analyse this modulating effect in a medium-term time span, after an abrupt rise to a new stable level of the average summer temperature of ca 2°C, in Mediterranean forests in central Italy. This paper aims to answer the following questions: 1) did increasing temperature and drought events affect the growth of thermophilous deciduous forests? 2) Was this effect buffered in mixed stands compared to monocultures? 3) Did co-occurring tree species with different ecological characteristics, from more mesophilous to more xerophilous, have different responses? In 2012 and 2017, wood cores were collected from 659 trees in 36 plots representative of thermophilous deciduous forests. The selected tree species were Castanea sativa, Ostrya carpinifolia, Quercus cerris, Quercus ilex and Quercus petraea. In the sampling plots, they were present in pure stands and mixtures from two to four species. After measuring annual rings on cores, chronologies of basal area increment were built, and inventory data were used to estimate tree growth. Results showed a strong reduction of growth, lasting at least 18 years, after the temperature rise. Tree diversity significantly reduced the growth drop after the sudden and stable rise in summer average temperature. Tree mixture effect on growth stability appeared to be dependent on the tree species present in the mixture. Temperature rise and associated drought events, even without changes in rainfall, are one of the main challenges that European forests will face in the current scenarios of climate change. Tree diversity can buffer the effects of climate change over periods of at least 15 years and should be considered in forest management plans. Numéro de notice : A2023-070 Affiliation des auteurs : LIF+Ext (2020- ) Autre URL associée : archives Univ Florence Thématique : BIODIVERSITE/FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/oik.08875 Date de publication en ligne : 22/12/2022 En ligne : https://doi.org/10.1111/oik.08875 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102324 [article]

Quantifying the influence of plot-level uncertainty in above ground biomass up scaling using remote sensing data in central Indian dry deciduous forest / Thangavelu Mayamanikandan in Geocarto international, vol 37 n° 12 ([01/07/2022])  

Public [article]  inGeocarto international > vol 37 n° 12 [01/07/2022] . - pp 3489 - 3503 Titre : Quantifying the influence of plot-level uncertainty in above ground biomass up scaling using remote sensing data in central Indian dry deciduous forest Type de document : Article/Communication Auteurs : Thangavelu Mayamanikandan, Auteur ; Suraj Reddy, Auteur ; Rakesh Fararoda, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 3489 - 3503 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse aérienne [Termes IGN] forêt de feuillus [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] incertitude des données [Termes IGN] Inde [Termes IGN] placette d'échantillonnage [Termes IGN] superposition d'images Résumé : (auteur) Accurate and reliable estimation of Above Ground Biomass (AGB) in tropical forests is much needed for net carbon assessments. The aim of the study is to determine the uncertainty in biomass estimation in terms of field plot size, shape and location error using field plot and remote sensing data in tropical dry deciduous forests of India. Detailed tree measurements and location mapping are performed in 13 (1 ha) plots and 1 a very large permanent plot of 32 ha and AGB is estimated using local volume equations. Remote sensing-based AGB estimated using a multiple linear regression model between the reflectance (Sentinel-2) and backscatter (Sentinel-1) with field AGB. The result shows relative root mean square error of the model decreased by approximately 50% with a plot size increase from 0.01 ha (64%) to 0.64 ha (14%). Furthermore, we also observed that the effect of global positioning system location errors in AGB modelling would be negated by increasing plot size. Numéro de notice : A2022-587 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1864029 Date de publication en ligne : 29/12/2020 En ligne : https://doi.org/10.1080/10106049.2020.1864029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101361 [article]

Coniferous and broad-leaved forest distinguishing using L-band polarimetric SAR data / Fang Shang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 9 (September 2021) . - pp 7487 - 7499 Titre : Coniferous and broad-leaved forest distinguishing using L-band polarimetric SAR data Type de document : Article/Communication Auteurs : Fang Shang, Auteur ; Taiga Saito, Auteur ; Saya Ohi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 7487 - 7499 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande L [Termes IGN] détection de changement [Termes IGN] détection de cible [Termes IGN] distribution spatiale [Termes IGN] forêt de feuillus [Termes IGN] image ALOS-PALSAR [Termes IGN] image radar moirée [Termes IGN] Japon [Termes IGN] Pinophyta [Termes IGN] polarimétrie radar Résumé : (auteur) This article proposes a coniferous and broad-leaved forest distinguishing method using L-band polarimetric SAR data based on the structure-orientation parameter. The structure-orientation parameter is one of the averaged Stokes vector-based discriminators which is sensitive to the composition of equivalent horizontal and vertical structures. In the proposed method, the structure-orientation parameters is compensated by employing the scattered power information to remove the influence of the topography. The final distinguishing result is generated based on the statistical feature of the compensated parameters. The experiments using several sets of ALOS2-PALSAR2 level 1.1 data prove that the proposed method has high performance for forest-type distinguishing. Numéro de notice : A2021-648 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3032468 Date de publication en ligne : 03/11/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3032468 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98355 [article]

A density-based algorithm for the detection of individual trees from LiDAR data / Melissa Latella in Remote sensing, Vol 13 n° 2 (January-2 2021)  

Public [article]  inRemote sensing > Vol 13 n° 2 (January-2 2021) . - n° 322 Titre : A density-based algorithm for the detection of individual trees from LiDAR data Type de document : Article/Communication Auteurs : Melissa Latella, Auteur ; Fabio Sola, Auteur ; Carlo Camporeal, Auteur Année de publication : 2021 Article en page(s) : n° 322 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] comptage [Termes IGN] densité de la végétation [Termes IGN] détection d'arbres [Termes IGN] distribution spatiale [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt de feuillus [Termes IGN] hauteur des arbres [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] semis de points [Termes IGN] sous-étage Résumé : (auteur) Nowadays, LiDAR is widely used for individual tree detection, usually providing higher accuracy in coniferous stands than in deciduous ones, where the rounded-crown, the presence of understory vegetation, and the random spatial tree distribution may affect the identification algorithms. In this work, we propose a novel algorithm that aims to overcome these difficulties and yield the coordinates and the height of the individual trees on the basis of the point density features of the input point cloud. The algorithm was tested on twelve deciduous areas, assessing its performance on both regular-patterned plantations and stands with randomly distributed trees. For all cases, the algorithm provides high accuracy tree count (F-score > 0.7) and satisfying stem locations (position error around 1.0 m). In comparison to other common tools, the algorithm is weakly sensitive to the parameter setup and can be applied with little knowledge of the study site, thus reducing the effort and cost of field campaigns. Furthermore, it demonstrates to require just 2 points·m−2 as minimum point density, allowing for the analysis of low-density point clouds. Despite its simplicity, it may set the basis for more complex tools, such as those for crown segmentation or biomass computation, with potential applications in forest modeling and management. Numéro de notice : A2021-196 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13020322 Date de publication en ligne : 19/01/2021 En ligne : https://doi.org/10.3390/rs13020322 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97146 [article]

Unprecedented pluri-decennial increase in the growing stock of French forests is persistent and dominated by private broadleaved forests / Jean-Daniel Bontemps in Annals of Forest Science, vol 77 n° 4 (December 2020)  

Public [article]  inAnnals of Forest Science > vol 77 n° 4 (December 2020) . - n° 98 Titre : Unprecedented pluri-decennial increase in the growing stock of French forests is persistent and dominated by private broadleaved forests Type de document : Article/Communication Auteurs : Jean-Daniel Bontemps , Auteur ; Anaïs Denardou-Tisserand , Auteur ; Jean-Christophe Hervé (1961-2017) , Auteur ; Jean Bir , Auteur ; Jean-Luc Dupouey, Auteur Année de publication : 2020 Projets : ARBRE / AgroParisTech (2007 -) Article en page(s) : n° 98 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] bois sur pied [Termes IGN] changement d'utilisation du sol [Termes IGN] forêt de feuillus [Termes IGN] forêt privée [Termes IGN] inventaire forestier national (données France) [Termes IGN] modèle de régression [Termes IGN] politique forestière [Termes IGN] puits de carbone [Termes IGN] série temporelle [Termes IGN] surface forestière [Vedettes matières IGN] Economie forestière Résumé : (auteur) Key message: French forests exhibit the fastest relative changes across Europe. Growing stock increases faster than area, and is greatest in low-stocked private broadleaved forests. Past areal increases and current GS levels show positive effects on GS expansion, with GS increases hence expected to persist. Context: Strong increases in growing stocks (GS) of European forests for decades remain poorly understood and of unknown duration. French forests showing the greatest relative changes across Europe form the investigated case study. Aims: The magnitudes of net area, GS, and GS density (GSD) changes were evaluated across forest categories reflecting forest policy and land-use drivers. The roles of forest areal changes, GS and GSD levels on GS changes were investigated. Methods: National Forest Inventory data were used to produce time series of area, GS and GSD across forest categories over 1976–2014, and exploratory causal models of GS changes. Results: GS (+ 57%) increased three times faster than area, highlighting an advanced stage in the forest transition. Low-stocked private forests exhibited strong changes in GS/GSD, greatest in private broadleaved forests, stressing the contribution of returning forests on abandoned lands. Regression models demonstrated positive effects of both past areal increases and current GS, on GS expansion. Conclusion: Aerial C-sink in French forests is expected to persist in future decades. Numéro de notice : A2020-647 Affiliation des auteurs : LIF+Ext (2020- ) Autre URL associée : vers HAL Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01003-6 Date de publication en ligne : 12/10/2020 En ligne : https://doi.org/10.1007/s13595-020-01003-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96075 [article]

Is field-measured tree height as reliable as believed – Part II, A comparison study of tree height estimates from conventional field measurement and low-cost close-range remote sensing in a deciduous forest / Luka Jurjević in ISPRS Journal of photogrammetry and remote sensing, vol 169 (November 2020)  

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CO2 fertilization, transpiration deficit and vegetation period drive the response of mixed broadleaved forests to a changing climate in Wallonia / Louis de Wergifosse in Annals of Forest Science, vol 77 n° 3 (September 2020)  

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Improved supervised learning-based approach for leaf and wood classification from LiDAR point clouds of forests / Sruthi M. Krishna Moorthy in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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Potential of UAV photogrammetry for characterization of forest canopy structure in uneven-aged mixed conifer–broadleaf forests / Sadeepa Jayathunga in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)  

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Expansion tendancielle du stock de bois dans les forêts françaises (1976–2015) [diaporama] / Jean-Daniel Bontemps (2018)  

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The potential of the greenness and radiation (GR) model to interpret 8-day gross primary production of vegetation / Chaoyang Wu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)  

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