Centre dedocumentation
scientifique

Forest structure and fine root biomass influence soil CO2 efflux in temperate forests under drought / Antonios Apostolakis in Forests, vol 14 n° 2 (February 2023)  

Public [article]  inForests > vol 14 n° 2 (February 2023) . - n° 411 Titre : Forest structure and fine root biomass influence soil CO2 efflux in temperate forests under drought Type de document : Article/Communication Auteurs : Antonios Apostolakis, Auteur ; Ingo Schöning, Auteur ; Beate Michalzik, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 411 Langues : Anglais (eng) Descripteur : [Termes IGN] Allemagne [Termes IGN] biomasse forestière [Termes IGN] forêt tempérée [Termes IGN] puits de carbone [Termes IGN] qualité du sol [Termes IGN] sécheresse [Termes IGN] structure d'un peuplement forestier [Termes IGN] température au sol [Termes IGN] teneur en carbone [Termes IGN] teneur en eau de la végétation [Vedettes matières IGN] Végétation et changement climatique Numéro de notice : A2023-165 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f14020411 Date de publication en ligne : 17/12/2023 En ligne : https://doi.org/10.3390/f14020411 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102871 [article]

Testing the application of process-based forest growth model PREBAS to uneven-aged forests in Finland / Man Hu in Forest ecology and management, vol 529 (February-1 2023)  

Public [article]  inForest ecology and management > vol 529 (February-1 2023) . - n° 120702 Titre : Testing the application of process-based forest growth model PREBAS to uneven-aged forests in Finland Type de document : Article/Communication Auteurs : Man Hu, Auteur ; Francesco Minunno, Auteur ; Mikko Peltoniemi, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120702 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière [Termes IGN] croissance des arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] forêt inéquienne [Termes IGN] hauteur des arbres [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] modélisation de la forêt [Termes IGN] mortalité [Termes IGN] peuplement mélangé [Termes IGN] photosynthèse [Termes IGN] Picea abies [Termes IGN] structure d'un peuplement forestier [Vedettes matières IGN] Foresterie Résumé : (auteur) The challenges of applying process-based models to uneven-aged forests are the difficulties in simulating the interactions between trees and resource allocation between size classes. In this study, we focused on a process-based forest growth model PREBAS which is a mean tree model with Reineke self-thinning mortality and was originally developed for even-aged forests. The primary aim was to test the application of PREBAS model to uneven-aged forests by introducing different diameter at breast height (DBH) size classes to better represent the forest structure. Additionally, we introduced a new mortality model to PREBAS which is developed for uneven-aged stands and compared with the current PREBAS version in which a modification Reineke rule is used. The tests were conducted in 26 old Norway spruce dominated stands in southern and central Finland with three consecutive measurements (on average a 25-year study period). To evaluate the model performance, we compared the estimations of stand averaged diameter at breast height (D), stand averaged tree height (H), stand averaged crown base height (), stand basal area (B) and density (N) with measurements. Moreover, biomass estimations of each tree component (foliage, branch and stem) were compared to estimations from empirical models. Results showed that introducing size distributions can represent better stand structure and improve the model predictions compared with data. Moreover, the new mortality model showed promise with qualitatively more realistic results especially among the largest tree size classes. However, model bias still existed in the simulation although the predictions were improved. It revealed that further calibration of the PREBAS model with size classes should be done to better extend the model applicability to uneven-aged forests. Numéro de notice : A2023-022 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120702 Date de publication en ligne : 05/12/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120702 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102228 [article]

Decision 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 38 n° inconnu ([01/01/2023])  

Public [article]  inGeocarto international > vol 38 n° inconnu [01/01/2023] Titre : Decision tree-based machine learning models for above-ground biomass estimation using multi-source remote sensing data and object-based image analysis Type de document : Article/Communication Auteurs : Haifa Tamiminia, Auteur ; Bahram Salehi, Auteur ; Masoud Mahdianpari, Auteur ; et al., Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] analyse d'image orientée objet [Termes IGN] biomasse aérienne [Termes IGN] boosting adapté [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification pixellaire [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Extreme Gradient Machine [Termes IGN] image ALOS-PALSAR [Termes IGN] image Landsat [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] New York (Etats-Unis ; état) [Termes IGN] réserve naturelle Résumé : (auteur) Forest above-ground biomass (AGB) estimation provides valuable information about the carbon cycle. Thus, the overall goal of this paper is to present an approach to enhance the accuracy of the AGB estimation. The main objectives are to: 1) investigate the performance of remote sensing data sources, including airborne light detection and ranging (LiDAR), optical, SAR, and their combination to improve the AGB predictions, 2) examine the capability of tree-based machine learning models, and 3) compare the performance of pixel-based and object-based image analysis (OBIA). To investigate the performance of machine learning models, multiple tree-based algorithms were fitted to predictors derived from airborne LiDAR data, Landsat, Sentinel-2, Sentinel-1, and PALSAR-2/PALSAR SAR data collected within New York’s Adirondack Park. Combining remote sensing data from multiple sources improved the model accuracy (RMSE: 52.14 Mg ha−1 and R2: 0.49). There was no significant difference among gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGBoost) models. In addition, pixel-based and object-based models were compared using the airborne LiDAR-derived AGB raster as a training/testing sample. The OBIA provided the best results with the RMSE of 33.77 Mg ha−1 and R2 of 0.81 for the combination of optical and SAR data in the GBM model. Numéro de notice : A2022-331 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1080/10106049.2022.2071475 Date de publication en ligne : 27/04/2022 En ligne : https://doi.org/10.1080/10106049.2022.2071475 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100607 [article]

Estimating mangrove above-ground biomass at Maowei Sea, Beibu Gulf of China using machine learning algorithm with Sentinel-1 and Sentinel-2 data / Zhuomei Huang in Geocarto international, vol 38 n° inconnu ([01/01/2023])  

Public [article]  inGeocarto international > vol 38 n° inconnu [01/01/2023] Titre : Estimating mangrove above-ground biomass at Maowei Sea, Beibu Gulf of China using machine learning algorithm with Sentinel-1 and Sentinel-2 data Type de document : Article/Communication Auteurs : Zhuomei Huang, Auteur ; Yichao Tian, Auteur ; et al., Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse aérienne [Termes IGN] Chine [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] mangrove [Termes IGN] optimisation par essaim de particules Résumé : (auteur) Blue carbon ecosystems such as mangroves are natural barriers to resisting and alleviating the impact of storm surges and extreme catastrophic weather. Accurate and efficient determination of the aboveground biomass of mangroves is of great importance for the protection and restoration of blue carbon ecosystems and their response to climate change. This study proposes a light gradient boosting model (LGBM) based on particle swarm optimization (PSO) algorithm for feature selection. We constructed and verified the proposed model using 227 quadrat datasets from a field survey and Sentinel-1 and Sentinel-2 data. The determination coefficient (R2) and root-mean-square error (RMSE) were used to evaluate the performance of the model. Compared with random forest(RF), K-nearest neighbourhood regression(KNNR), extreme gradient boosting(XGBR), LGBM, and other machine learning algorithms, the LGBM-PSO model achieves better results (R2 = 0.7807, RMSE = 24.6864 Mg·ha−1), The predicted range of mangrove biomass is 4.623–206.975 Mg·ha−1. Therefore, the use of multisource remote sensing data combined with the LGBM-PSO model can provide better prediction results of aboveground biomass of mangroves, thereby providing a new method for estimating the aboveground biomass of large-scale mangroves. Numéro de notice : A2022-621 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2022.2102226 Date de publication en ligne : 22/07/2022 En ligne : https://doi.org/10.1080/10106049.2022.2102226 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101356 [article]

Improving methods to predict aboveground biomass of Pinus sylvestris in urban forest using UFB model, LiDAR and digital hemispherical photography / Ihor Kozak in Urban Forestry & Urban Greening, vol 79 (January 2023)  

Public [article]  inUrban Forestry & Urban Greening > vol 79 (January 2023) . - n° 127793 Titre : Improving methods to predict aboveground biomass of Pinus sylvestris in urban forest using UFB model, LiDAR and digital hemispherical photography Type de document : Article/Communication Auteurs : Ihor Kozak, Auteur ; Mikhail Popov, Auteur ; Igor Semko, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 127793 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] biomasse aérienne [Termes IGN] détection d'arbres [Termes IGN] données lidar [Termes IGN] forêt urbaine [Termes IGN] houppier [Termes IGN] image hémisphérique [Termes IGN] Leaf Area Index [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle de régression [Termes IGN] modèle numérique de terrain [Termes IGN] photographie numérique [Termes IGN] Pinus sylvestris [Termes IGN] Pologne [Termes IGN] semis de points [Termes IGN] surface terrière Résumé : (auteur) The article proposes methods for combining Airborne Laser Scanning (ALS) with Digital Hemispherical Photography (DHP) data required by the Urban Forest Biomass (UFB) model to predict the aboveground biomass (AGB) of Scotch pine (Pinus sylvestris L.) in urban forests of Lublin (Poland). The article also demonstrates the potential of ALS and DHP data in urban AGB estimation. ALS and Leaf Area Index (LAI) data were calculated using a voxels-vector approach based on the measurements taken at eight permanent sample plots (PSPs). The research was conducted in 2014 and the prediction was made until 2030. It was found that the determination coefficients (R2) for the Basal Area (BA) of the trees are 0.97, and the BA modeling parameters have a high correlation with those observed in the field (model efficiency (ME) 0.94). 83 % growth trajectory based on the measured BA was appropriately modeled using the UFB model (P > 0.9). The results for AGB show that the degree of fitting and accuracy are greatest for the Monte Carlo (MC) simulation technique based on ALS and DHP data (UBF with ALS and DHP) where R2 = 0.98, RMSE = 2.97 t/ha, MAE = 2.35 t/ha, rRMSE = 1.28 %, which performed better than MC simulation technique without ALS and DHP (UBF without ALS and DHP) where R2 = 0.94, RMSE = 4.58 t/ha, MAE = 3.64 t/ha, rRMSE = 3.29 %. The results indicate that the proposed method based on combining the UFB model, LiDAR and DHP allows us to improve the accuracy of the AGB prediction. Numéro de notice : A2023-023 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ufug.2022.127793 Date de publication en ligne : 23/11/2022 En ligne : https://doi.org/10.1016/j.ufug.2022.127793 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102246 [article]

Management of birch spruce mixed stands with consideration of carbon stock in biomass and harvested wood products / Jānis Vuguls in Forests, vol 14 n° 1 (January 2023)  

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A new strategy for improving the accuracy of forest aboveground biomass estimates in an alpine region based on multi-source remote sensing / Yali Zhang in GIScience and remote sensing, vol 60 n° 1 (2023)  

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Above ground biomass estimation from UAV high resolution RGB images and LiDAR data in a pine forest in Southern Italy / Mauro Maesano in iForest, biogeosciences and forestry, vol 15 n° 6 (December 2022)  

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Wall-to-wall mapping of forest biomass and wood volume increment in Italy / Francesca Giannetti in Forests, vol 13 n° 12 (December 2022)  

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Development and long-term dynamics of old-growth beech-fir forests in the Pyrenees: Evidence from dendroecology and dynamic vegetation modelling / Dario Martín-Benito in Forest ecology and management, vol 524 (November-15 2022)  

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Estimating carbon stocks and biomass expansion factors of urban greening trees using terrestrial laser scanning / Linlin Wu in Forests, vol 13 n° 9 (september 2022)  

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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])  

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Management or climate and which one has the greatest impact on forest soil’s protective value? A case study in Romanian mountains / Cosmin Cosofret in Forests, vol 13 n° 6 (June 2022)  

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Uncertainty of biomass stocks in Spanish forests: a comprehensive comparison of allometric equations / Aitor Ameztegui in European Journal of Forest Research, vol 141 n° 3 (June 2022)  

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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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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 (March-1 2022)  

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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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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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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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Aboveground biomass estimation of an agro-pastoral ecology in semi-arid Bundelkhand region of India from Landsat data: a comparison of support vector machine and traditional regression models / Dibyendu Deb in Geocarto international, vol 37 n° 4 ([15/02/2022])  

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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 (February-1 2022)  

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Survival 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)  

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Combined 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])  

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3D stem modelling in tropical forest: towards improved biomass and biomass change estimates / Sébastien Bauwens (2022)  

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Above-ground biomass estimation in a Mediterranean sparse coppice oak forest using Sentinel-2 data / Fardin Moradi in Annals of forest research, vol 65 n° 1 (January - June 2022)  

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Contributions of multi-temporal airborne LiDAR data to mapping carbon stocks and fluxes in tropical forests / Claudia Milena Huertas Garcia (2022)  

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Estimating aboveground biomass in dense Hyrcanian forests by the use of Sentinel-2 data / Fardin Moradi in Forests, vol 13 n° 1 (January 2022)  

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Global canopy height regression and uncertainty estimation from GEDI LIDAR waveforms with deep ensembles / Nico Lang in Remote sensing of environment, vol 268 (January 2022)  

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Impacts of drought on biomass and carbon fluxes in the Amazon rainforest / Yitong Yao (2022)  

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Investigating the role of wind disturbance in tropical forests through a forest dynamics model and satellite observations / E-Ping Rau (2022)  

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Monitoring forest-savanna dynamics in the Guineo-Congolian transition area of the centre region of Cameroon / Le Bienfaiteur Sagang Takougoum (2022)  

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Climate 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, vol 78 n° 4 (December 2021)  

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Estimation of individual tree stem biomass in an uneven-aged structured coniferous forest using multispectral LiDAR data / Nikos Georgopoulos in Remote sensing, vol 13 n° 23 (December-1 2021)  

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A generic information framework for decision-making in a forest-based bio-economy / Jean-Baptiste Pichancourt in Annals of Forest Science, vol 78 n° 4 (December 2021)  

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Modelling bark volume for six commercially important tree species in France: assessment of models and application at regional scale / Rodolphe Bauer in Annals of Forest Science, vol 78 n° 4 (December 2021)  

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Above-ground biomass change estimation using national forest inventory data with Sentinel-2 and Landsat / Stefano Puliti in Remote sensing of environment, vol 265 (November 2021)  

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Multi-sensor aboveground biomass estimation in the broadleaved hyrcanian forest of Iran / Ghasem Ronoud in Canadian journal of remote sensing, vol 47 n° 6 ([01/11/2021])  

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The effects of combining the variables in allometric biomass models on biomass estimates over large forest areas: A european beech case study / Erick O. Osewe in Forests, vol 12 n° 10 (October 2021)  

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Variation in downed deadwood density, biomass, and moisture during decomposition in a natural temperate forest / Tomas Přívětivý in Forests, vol 12 n° 10 (October 2021)  

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Mapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches / He Zhang in Remote sensing, vol 13 n° 18 (September-2 2021)  

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Target-based automated matching of multiple terrestrial laser scans for complex forest scenes / Xuming Ge in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)  

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The real potential of current passive satellite data to map aboveground biomass in tropical forests / Nidhi Jha in Remote sensing in ecology and conservation, vol 7 n° 3 (September 2021)  

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Calibration of the process-based model 3-PG for major central European tree species / David I. Forrester in European Journal of Forest Research, vol 140 n° 4 (August 2021)  

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Surface modelling of forest aboveground biomass based on remote sensing and forest inventory data / Xiaofang Sun in Geocarto international, vol 36 n° 14 ([01/08/2021])  

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Estimation of biomass increase and CUE at a young temperate scots pine stand concerning drought occurrence by combining eddy covariance and biometric methods / Paulina Dukat in Forests, vol 12 n° 7 (July 2021)  

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Estimation of tree height and aboveground biomass of coniferous forests in North China using stereo ZY-3, multispectral Sentinel-2, and DEM data / Yueting Wang in Ecological indicators, vol 126 (July 2021)  

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Semantic 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)  

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Spatio-temporal-spectral observation model for urban remote sensing / Zhenfeng Shao in Geo-spatial Information Science, vol 24 n° 3 (July 2021)  

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Altimétrie laser et surveillance / Laurent Polidori in Géomètre, n° 2192 (juin 2021)

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Identifying the effects of chronic saltwater intrusion in coastal floodplain swamps using remote sensing / Elliott White Jr in Remote sensing of environment, vol 258 (June 2021)  

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Improving tree biomass models through crown ratio patterns and incomplete data sources / Maria Menéndez-Miguélez in European Journal of Forest Research, vol 140 n° 3 (June 2021)  

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Model-based estimation of forest canopy height and biomass in the Canadian boreal forest using radar, LiDAR, and optical remote sensing / Michael L. Benson in IEEE Transactions on geoscience and remote sensing, vol 59 n° 6 (June 2021)  

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Walking through the forests of the future: using data-driven virtual reality to visualize forests under climate change / Jiawei Huang in International journal of geographical information science IJGIS, vol 35 n° 6 (June 2021)  

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Aboveground biomass estimates of tropical mangrove forest using Sentinel-1 SAR coherence data : The superiority of deep learning over a semi-empirical model / S.M. Ghosh in Computers & geosciences, vol 150 (May 2021)  

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Estimation of some stand parameters from textural features from WorldView-2 satellite image using the artificial neural network and multiple regression methods: a case study from Turkey / Alkan Günlü in Geocarto international, vol 36 n° 8 ([01/05/2021])  

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Evaluating P-Band TomoSAR for biomass retrieval in boreal forest / Erik Blomberg in IEEE Transactions on geoscience and remote sensing, vol 59 n° 5 (May 2021)  

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European beech leads to more bioactive humus forms but stronger mineral soil acidification as Norway spruce and Scots pine – Results of a repeated site assessment after 63 and 82 years of forest conversion in Central Germany / Florian Achilles in Forest ecology and management, vol 483 ([01/03/2021])  

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Variations in temperate forest biomass ratio along three environmental gradients are dominated by interspecific differences in wood density / Baptiste Kerfriden in Plant ecology, vol 222 n° 3 (March 2021)  

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What factors shape spatial distribution of biomass in riparian forests? Insights from a LiDAR survey over a large area / Leo Huylenbroeck in Forests, vol 12 n° 3 (March 2021)  

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Agroforestry / Gopal Shukla (2021)  

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Applications of remote sensing data in mapping of forest growing stock and biomass / Jose Aranha (2021)  

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Déterminants de la composition floristique et estimations des stocks de carbone des peuplements forestiers matures de Uma (Tshopo, RDC) / John Katembo Mukirania (2021)  

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Evaluation du stock de carbone aérien dans la végétation à partir de multiples observations satellites micro-ondes / Martin Cubaud (2021) 

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Forest biomass / Ana Cristina Goncalves (2021)  

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Qualification des données LiDAR GEDI pour le suivi de l’impact climatique sur la forêt de Südharz / Iris Jeuffrard (2021) 

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Variabilité environnementale et botanique de la densité du bois des espèces forestières et variabilité temporelle de la biomasse aérienne des forêts françaises : une analyse sur un échantillon systématique de l’inventaire forestier national / Baptiste Kerfriden (2021)  

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Exploring the inclusion of Sentinel-2 MSI texture metrics in above-ground biomass estimation in the community forest of Nepal / Santa Pandit in Geocarto international, vol 35 n° 16 ([01/12/2020])  

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Improving aboveground biomass estimates by taking into account density variations between tree components / Antoine Billard in Annals of Forest Science, vol 77 n° 4 (December 2020)  

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Ground-based remote sensing of forests exploiting GNSS signals / Leila Guerriero in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

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L-band SAR for estimating aboveground biomass of rubber plantation in Java Island, Indonesia / Bambang H Trisasongko in Geocarto international, vol 35 n° 12 ([01/09/2020])  

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Carbon stocks, partitioning, and wood composition in short-rotation forestry system under reduced planting spacing / Felipe Schwerz in Annals of Forest Science, vol 77 n° 3 (September 2020)  

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Predicting biomass dynamics at the national extent from digital aerial photogrammetry / Bronwyn Price in International journal of applied Earth observation and geoinformation, vol 90 (August 2020)  

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Influence of forest management activities on soil organic carbon stocks: A knowledge synthesis / Mathias Mayer in Forest ecology and management, Vol 466 (15 June 2020)  

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Improving precision of field inventory estimation of aboveground biomass through an alternative view on plot biomass / Christoph Kleinn in Forest ecosystems, vol 7 (2020)  

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Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors / Svetlana Saarela in Forest ecosystems, vol 7 (2020)  

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Potential of texture from SAR tomographic images for forest aboveground biomass estimation / Zhanmang Liao in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)  

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Mangrove forest classification and aboveground biomass estimation using an atom search algorithm and adaptive neuro-fuzzy inference system / Minh Hai Pham in Plos one, vol 15 n° 5 (May 2020)  

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Above-ground biomass estimation and yield prediction in potato by using UAV-based RGB and hyperspectral imaging / Bo Li in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)  

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Assessing forest availability for wood supply in Europe / Iciar A. Alberdi in Forest policy and economics, vol 111 (February 2020)  

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Can Carbon Sequestration in Tasmanian “Wet” Eucalypt Forests Be Used to Mitigate Climate Change? Forest Succession, the Buffering Effects of Soils, and Landscape Processes Must Be Taken into Account / Peter D. McIntosh in International journal of forestry research, vol 2020 ([01/02/2020])  

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Artificial neural network models by ALOS PALSAR data for aboveground stand carbon predictions of pure beech stands: a case study from northern of Turkey / Alkan Günlü in Geocarto international, Vol 35 n° 1 ([02/01/2020])  

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Estimation et suivi de la ressource en bois en France métropolitaine par valorisation des séries multi-temporelles à haute résolution spatiale d'images optiques (Sentinel-2) et radar (Sentinel-1, ALOS-PALSAR) / David Morin (2020)  

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European Forest Accounts - Années 2016-2017 : Rapport d’étude / Alexandra Niedzwiedz (2020)  

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Inversion de données PolSAR en bande P pour l'estimation de la biomasse forestière / Colette Gelas (2020)  

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Remote sensing technology applications in forestry and REDD+ / Kim Calders (2020)  

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Réponses de la productivité des forêts aux fluctuations météorologiques : biais et surestimations des estimations de terrain / Olivier Bouriaud (2020)  

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Phosphorus availability in relation to soil properties and forest productivity in Pinus sylvestris L. plantations / Teresa Bueis in Annals of Forest Science, Vol 76 n° 4 (December 2019)  

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A two-scale approach for estimating forest aboveground biomass with optical remote sensing images in a subtropical forest of Nepal / Upama A. Koju in Journal of Forestry Research, vol 30 n° 6 (December 2019)  

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Mapping of forest tree distribution and estimation of forest biodiversity using Sentinel-2 imagery in the University Research Forest Taxiarchis in Chalkidiki, Greece / Maria Kampouri in Geocarto international, vol 34 n° 12 ([15/09/2019])  

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Free and open-source GIS technologies for the management of woody biomass / Michele Mangiameli in Applied geomatics, vol 11 n° 3 (September 2019)  

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Pressures and threats to nature related to human activities in European urban and suburban forests / Ewa Referowska-Chodak in Forests, vol 10 n° 9 (September 2019)  

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Quantifying intra-annual dynamics of carbon sequestration in the forming wood: a novel histologic approach / Anjy Andrianantenaina in Annals of Forest Science, Vol 76 n° 3 (September 2019)  

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Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images / Jie Wang in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

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Innovations in ground and airborne technologies as reference and for training and validation: Terrestrial Laser Scanning (TLS) / Mathias I. Disney in Surveys in Geophysics, vol 40 n° 4 (July 2019)  

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Occlusion probability in operational forest inventory field sampling with ForeStereo / Fernando Montes in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

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Object-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment / Eduarda M.O. Silveira in International journal of applied Earth observation and geoinformation, vol 78 (June 2019)  

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Tree and stand level estimations of Abies alba Mill. aboveground biomass / Andrzej M. Jagodzinski in Annals of Forest Science, vol 76 n° 2 (June 2019)  

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Estimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery / Yanan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

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Wood quality of black spruce and balsam fir trees defoliated by spruce budworm: A case study in the boreal forest of Quebec, Canada / Carlos Paixao in Forest ecology and management, vol 437 (1 April 2019)  

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Estimation of aboveground biomass and carbon in a tropical rain forest in Gabon using remote sensing and GPS data / Kalifa Goïta in Geocarto international, vol 34 n° 3 ([01/03/2019])  

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