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Aboveground biomass of salt-marsh vegetation in coastal wetlands: Sample expansion of in situ hyperspectral and Sentinel-2 data using a generative adversarial network / Chen Chen in Remote sensing of environment, vol 270 (March 2022)
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Titre : Aboveground biomass of salt-marsh vegetation in coastal wetlands: Sample expansion of in situ hyperspectral and Sentinel-2 data using a generative adversarial network Type de document : Article/Communication Auteurs : Chen Chen, Auteur ; Yi Ma, Auteur ; Guangbo Ren, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112885 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biomasse aérienne
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte thématique
[Termes IGN] image hyperspectrale
[Termes IGN] image Sentinel-MSI
[Termes IGN] littoral
[Termes IGN] marais salant
[Termes IGN] réseau antagoniste génératifRésumé : (auteur) Coastal wetlands are main components of the “blue carbon” ecosystems in coastal zones. Salt-marsh biomass is especially important regarding climate-change mitigation. Generating high precision biomass maps for evaluating the ecological functions of coastal wetlands is essential; however, conducting accurate biomass inversions with limited in situ observations from coastal wetlands is challenging. We propose a generative adversarial network with a constrained factor model (GAN-CF) for expanding limited in situ salt-marsh biomass observations. We used Sentinel-2 images and a deep belief network based on the conjugate gradient method (CG-DBN) for obtaining land-cover maps and the salt-marsh distribution (species: Phragmites australis, Suaeda glauca, Spartina alterniflora, and mixed species dominated by Tamarix chinensis) in the study area. This study bridges in situ hyperspectral and Sentinel-2 multispectral data by a satellite-band equivalent conversion model. The biomass and multispectral data derived from Sentinel-2 were used as input for the proposed GAN-CF model, which produced and constrained the generated samples based on the features (i.e., spectra, vegetation index, and biomass) of the in situ observations. Aboveground biomass (AGB) maps at 10-m spatial resolution were produced by constructing multiple linear regression models (MLRMs) based on the generated samples of each salt-marsh type using Sentinel-2 images. The quantity and richness of the generated samples improved the AGB estimations in the study area. The inversion accuracy of S. alterniflora was significantly improved (RMSE = 3.71 Mg/ha); the estimated AGB was strongly related to the in situ observations (R = 0.923). The estimated AGB was validated using in situ observations. The total amount of salt-marsh AGB in the study area in 2019 was estimated at 2.36 × 105 Mg, with 7.95 Mg/ha average. The salt-marsh biomass in decreasing order was as follows: P. australis (12.7 Mg/ha) > S. alterniflora (11.5 Mg/ha) > mixed species (8.97 Mg/ha) > S. glauca (2.18 Mg/ha). The salt-marsh area in decreasing order was as follows: S. glauca (10,410 ha) > P. australis (7320 ha) > mixed species (6740 ha) > S. alterniflora (5240 ha). By a feasibility analysis we estimated the biomass based on the Sentinel-2 data covering the Yellow River delta wetland in May, July, and September 2019 and the Jiaozhou Bay wetland in September 2019 by using the generated samples. The generated samples based on the 2013–2019 in situ observations constitute a salt-marsh biomass database, which can be useful for quantifying the regional carbon storage and ecological restoration monitoring. Numéro de notice : A2022-128 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112885 Date de publication en ligne : 07/01/2022 En ligne : https://doi.org/10.1016/j.rse.2021.112885 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99710
in Remote sensing of environment > vol 270 (March 2022) . - n° 112885[article]Are northern German Scots pine plantations climate smart? The impact of large-scale conifer planting on climate, soil and the water cycle / Christoph Leuschner in Forest ecology and management, vol 507 (1 March 2022)
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Titre : Are northern German Scots pine plantations climate smart? The impact of large-scale conifer planting on climate, soil and the water cycle Type de document : Article/Communication Auteurs : Christoph Leuschner, Auteur ; Agnes Förster, Auteur ; Marco Diers, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120013 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] acidification des sols
[Termes IGN] albedo
[Termes IGN] Allemagne
[Termes IGN] biomasse aérienne
[Termes IGN] canopée
[Termes IGN] changement climatique
[Termes IGN] évapotranspiration
[Termes IGN] Fagus sylvatica
[Termes IGN] foresterie
[Termes IGN] Pinus sylvestris
[Termes IGN] puits de carbone
[Termes IGN] résilience écologique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Increasing temperatures and rising atmospheric vapor pressure deficits are exposing forests around the globe to increasing drought and heat stress, demanding a shift to climate-smart forestry for increasing the stress resistance and resilience of production forests and to enhance their climate change mitigation potential. Based on measurements in paired pine and beech forests and the review of literature data, we analyse the biophysical consequences and the carbon cycle impact of large-scale Scots pine (Pinus sylvestris L.) plantations in northern Germany in the face of a warming and aridifying climate. We quantified canopy surface albedo and surface temperature, evapotranspiration and deep seepage, carbon (C) storage in biomass and soil and annual C sequestration, and soil acidification of pine plantations in comparison to beech forests (Fagus sylvatica L.), the natural forest vegetation. We find that near-infrared (NIR, 700–3000 mn) canopy surface albedo is higher by 5.2 percentage points during summer over beech as compared to pine forest, resulting in a 9 % higher net radiation and a 0.6 K higher surface temperature of the pine canopy. Deep seepage is on average by 68 mm yr−1 smaller under pine than beech forest (66 mm yr−1 vs. 134 mm yr−1) due to the higher evapotranspiration of pine. C storage in biomass and soil is by ∼ 48 Mg C ha−1 higher in beech than pine forests, reflecting the higher productivity of beech, demonstrating an unfavorably low C sequestration potential of Scots pine plantations. We conclude that the large-scale Scots pine plantations in northern Germany (>1.7 million ha) are neither environmental-friendly nor climate smart, given their enhancement of climate-warming, low climate change mitigation potential, and negative effect on groundwater recharge. Replacing pine plantations by beech (or other hardwood) forests in northern Germany and adjacent regions is urgently needed for achieving the goals of climate-smart forestry. Numéro de notice : A2022-136 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120013 Date de publication en ligne : 24/01/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99742
in Forest ecology and management > vol 507 (1 March 2022) . - n° 120013[article]Assessing the dependencies of scots pine (Pinus sylvestris L.) structural characteristics and internal wood property variation / Ville Kankare in Forests, vol 13 n° 3 (March 2022)
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Titre : Assessing the dependencies of scots pine (Pinus sylvestris L.) structural characteristics and internal wood property variation Type de document : Article/Communication Auteurs : Ville Kankare, Auteur ; Ninni Saarinen, Auteur ; Jiri Pyorala, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 397 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse forestière
[Termes IGN] croissance des arbres
[Termes IGN] dendrochronologie
[Termes IGN] densité du bois
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] Finlande
[Termes IGN] forêt équienne
[Termes IGN] modèle linéaire
[Termes IGN] Pinus sylvestris
[Termes IGN] puits de carbone
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] variation de densitéRésumé : (auteur) Wood density is well known to vary between tree species as well as within and between trees of a certain species depending on the growing environment causing uncertainties in forest biomass and carbon storage estimation. This has created a need to develop novel methodologies to obtain wood density information over multiple tree communities, landscapes, and ecoregions. Therefore, the aim of this study was to evaluate the dependencies between structural characteristics of Scots pine (Pinus sylvestris L.) tree communities and internal wood property (i.e., mean wood density and ring width) variations at breast height. Terrestrial laser scanning was used to derive the structural characteristics of even-aged Scots pine dominated forests with varying silvicultural treatments. Pearson’s correlations and linear mixed effect models were used to evaluate the interactions. The results show that varying silvicultural treatments did not have a statistically significant effect on the mean wood density. A notably stronger effect was observed between the structural characteristics and the mean ring width within varying treatments. It can be concluded that single time terrestrial laser scanning is capable of capturing the variability of structural characteristics and their interactions with mean ring width within different silvicultural treatments but not the variation of mean wood density. Numéro de notice : A2027-208 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f13030397 Date de publication en ligne : 28/02/2022 En ligne : https://doi.org/10.3390/f13030397 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100025
in Forests > vol 13 n° 3 (March 2022) . - n° 397[article]Changes of tree stem biomass in European forests since 1950 / Aleksandr Lebedev in Journal of forest science, vol 68 n° 3 (March 2022)
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Titre : Changes of tree stem biomass in European forests since 1950 Type de document : Article/Communication Auteurs : Aleksandr Lebedev, Auteur ; Valery Kuzmichev, Auteur Année de publication : 2022 Article en page(s) : pp 107 - 115 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] Betula pendula
[Termes IGN] biomasse forestière
[Termes IGN] densité du bois
[Termes IGN] écosystème forestier
[Termes IGN] Europe (géographie politique)
[Termes IGN] forêt tempérée
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] puits de carbone
[Termes IGN] tronc
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Based on the measurements of the biomass of the stems of 3 699 trees of Scots pine, Norway spruce, and silver birch in Europe since 1950, it has been shown that these tree species show a reduction in biomass and wood density. These results contradict the fact that the volume of wood is directly converted to biomass using the historical values of the conversion rates. From 1950 to 2020 the biomass of 1 m3 of the stem with bark decreased on average by 80 kg (–17%) for Scots pine, by 105 kg (–22%) for Norway spruce and by 92 kg (–15%) for silver birch. The results obtained should be taken into account when assessing the technical properties of wood and estimating carbon sequestration by forest biomass. Since decreasing trends in stem biomass have been identified for several tree species, the phenomenon may have a large degree of generality. Such studies should be continued both at the regional and national level and at the global level. Numéro de notice : A2022-366 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.17221/135/2021-JFS Date de publication en ligne : 01/03/2022 En ligne : https://doi.org/10.17221/135/2021-JFS Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100587
in Journal of forest science > vol 68 n° 3 (March 2022) . - pp 107 - 115[article]Estimating aboveground biomass of urban forest trees with dual-source UAV acquired point clouds / Jiayuan Lin in Urban Forestry & Urban Greening, vol 69 (March 2022)
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Titre : Estimating aboveground biomass of urban forest trees with dual-source UAV acquired point clouds Type de document : Article/Communication Auteurs : Jiayuan Lin, Auteur ; Decao Chen, Auteur ; Wenjian Wu, Auteur ; Xiaohan Liao, Auteur Année de publication : 2022 Article en page(s) : n° 127521 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] allométrie
[Termes IGN] biomasse aérienne
[Termes IGN] Chine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt urbaine
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] structure-from-motionRésumé : (auteur) Urban forest is a crucial part of urban ecological environment. The accurate estimation of its tree aboveground biomass (AGB) is of significant value to evaluate urban ecological functions and estimate urban forest carbon storage. It has a high accuracy to estimate the forest AGB with field measured canopy structure parameters, but unsuitable for large-scale operations. Limited by low spatial resolution or spectral saturation, the estimated forest AGBs based on various satellite remotely sensed data have relatively low accuracies. In contrast, Unmanned Aerial Vehicle (UAV) remote sensing provides a promising way to accurately estimate the tree AGB of fragmented urban forest. In this study, taking an artificial urban forest in Ma'anxi Wetland Park in Chongqing City, China as an example, we used UAVs equipped with a digital camera and a LiDAR to acquire two point cloud data. One was produced from overlapping images using Structure from Motion (SfM) photogrammetry, and the other was resolved from laser scanned raw data. The dual point clouds were combined to extract individual tree height (H) and canopy radius (Rc), which were then input to the newly established allometric equation with tree H and Rc as predictor variables to obtain the AGBs of all dawn redwood trees in study area. In accuracy assessment, the coefficient of determination (R2) and Root Mean Square Error (RMSE) of extracted H were 0.9341 and 0.59 m; the R2 and RMSE of extracted Rc were 0.9006 and 0.28 m; the R2 and RMSE of estimated AGB were 0.9452 and 17.59 kg. These results proved the feasibility and effectiveness of applying dual-source UAV point cloud data and the new allometric equation on H and Rc to accurate AGB estimation of urban forest trees. Numéro de notice : A2022-319 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ufug.2022.127521 Date de publication en ligne : 24/02/2022 En ligne : https://doi.org/10.1016/j.ufug.2022.127521 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100425
in Urban Forestry & Urban Greening > vol 69 (March 2022) . - n° 127521[article]Five decades of ground flora changes in a temperate forest: The good, the bad and the ambiguous in biodiversity terms / K.J. Kirby in Forest ecology and management, vol 505 (1 February 2022)
PermalinkSurvival time and mortality rate of regeneration in the deep shade of a primeval beech forest / R. Petrovska in European Journal of Forest Research, vol 141 n° 1 (February 2022)
PermalinkDecision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis / Haifa Tamiminia in Geocarto international, vol 37 n° inconnu ([25/01/2022])
PermalinkCombined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation / Narissara Nuthammachot in Geocarto international, vol 37 n° 2 ([15/01/2022])
PermalinkDetection 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)
PermalinkEstimating aboveground biomass in dense Hyrcanian forests by the use of Sentinel-2 data / Fardin Moradi in Forests, vol 13 n° 1 (January 2022)
PermalinkFungal perspective of pine and oak colonization in Mediterranean degraded ecosystems / Irene Adamo in Forests, vol 13 n° 1 (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)
PermalinkMonitoring forest-savanna dynamics in the Guineo-Congolian transition area of the centre region of Cameroon / Le Bienfaiteur Sagang Takougoum (2022)
PermalinkClimate warming-induced replacement of mesic beech by thermophilic oak forests will reduce the carbon storage potential in aboveground biomass and soil / Jan Kasper in Annals of Forest Science [en ligne], vol 78 n° 4 (December 2021)
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