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scientifique

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)  

Public [article]  inEuropean Journal of Forest Research > vol 140 n° 3 (June 2021) . - pppages 675 - 689 Titre : Improving tree biomass models through crown ratio patterns and incomplete data sources Type de document : Article/Communication Auteurs : Maria Menéndez-Miguélez, Auteur ; Ricardo Ruiz-Peinado, Auteur ; Miren del Rio, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pppages 675 - 689 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse aérienne [Termes IGN] Espagne [Termes IGN] houppier [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modélisation de la forêt [Termes IGN] puits de carbone [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Aboveground biomass quantification is essential for determining carbon stocks in forests. Multiple tree biomass models are available, but estimations can be biased outside the fitting range. This is due to the lack of data for larger trees, mainly because of the cost and time required. This study proposed a methodology based on tree crown biomass ratio (crown biomass: total aboveground biomass) modelling. The original data used in the existing biomass models in Spain have been notably extended by the inclusion of stem data from First Spanish National Forest Inventory and other databases, covering better tree size variability. The analysis of the crown biomass ratio against tree size (d2h), allowed us to distinguish three different patterns: an increasing pattern, a constant one, and a decreasing pattern. A new system of biomass models was fitted simultaneously by species, including a model for crown biomass ratio according to the identified pattern, a stem biomass model, and a total aboveground biomass model. Using this methodology, models were fitted for the 29 most important species in Spain. The fitted models result in more accurate and unbiased predictions for stem biomass, and realistic estimations for the crown biomass. This methodology means more robust and flexible biomass estimations with the possibility of using different data sources. The absence of crown information is not an obstacle because this component is a percentage of total aboveground biomass. Moreover, determining the crown biomass ratio pattern allows improving the accuracy of tree biomass estimation beyond the range of tree sizes (2–70 cm) for which these models were fitted. Numéro de notice : A2021-430 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-021-01354-3 date de publication en ligne : 10/02/2021 En ligne : https://doi.org/10.1007/s10342-021-01354-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97791 [article]

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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 6 (June 2021) . - pp 1155 - 1178 Titre : Walking through the forests of the future: using data-driven virtual reality to visualize forests under climate change Type de document : Article/Communication Auteurs : Jiawei Huang, Auteur ; Melissa S. Lucash, Auteur ; Robert M. Scheller, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1155 - 1178 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière [Termes IGN] carte de la végétation [Termes IGN] changement climatique [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de simulation [Termes IGN] modélisation de la forêt [Termes IGN] monde virtuel [Termes IGN] paysage forestier [Termes IGN] réalité virtuelle [Termes IGN] visualisation 3D [Termes IGN] Wisconsin (Etats-Unis) [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Communicating and understanding climate induced environmental changes can be challenging, especially using traditional representations such as graphs, maps or photos. Immersive visualizations and experiences offer an intuitive, visceral approach to otherwise rather abstract concepts, but creating them scientifically is challenging. In this paper, we linked ecological modeling, procedural modeling, and virtual reality to provide an immersive experience of a future forest. We mapped current tree species composition in northern Wisconsin using the Forest Inventory and Analysis (FIA) data and then forecast forest change 50 years into the future under two climate scenarios using LANDIS-II, a spatially-explicit, mechanistic simulation model. We converted the model output (e.g., tree biomass) into parameters required for 3D visualizations with analytical modeling. Procedural rules allowed us to efficiently and reproducibly translate the parameters into a simulated forest. Data visualization, environment exploration, and information retrieval were realized using the Unreal Engine. A system evaluation with experts in ecology provided positive feedback and future topics for a comprehensive ecosystem visualization and analysis approach. Our approach to create visceral experiences of forests under climate change can facilitate communication among experts, policy-makers, and the general public. Numéro de notice : A2021-384 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1830997 date de publication en ligne : 10/11/2020 En ligne : https://doi.org/10.1080/13658816.2020.1830997 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97641 [article]

Analysis of plot-level volume increment models developed from machine learning methods applied to an uneven-aged mixed forest / Seyedeh Kosar Hamidi in Annals of Forest Science [en ligne], vol 78 n° 1 (March 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 1 (March 2021) . - n° 4 Titre : Analysis of plot-level volume increment models developed from machine learning methods applied to an uneven-aged mixed forest Type de document : Article/Communication Auteurs : Seyedeh Kosar Hamidi, Auteur ; Eric K. Zenner, Auteur ; Mahmoud Bayat, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Acer velutinum [Termes IGN] alnus cordata [Termes IGN] analyse comparative [Termes IGN] apprentissage automatique [Termes IGN] carpinus betulus [Termes IGN] classification barycentrique [Termes IGN] classification par forêts aléatoires [Termes IGN] classification par réseau neuronal [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] dynamique de la végétation [Termes IGN] écosystème forestier [Termes IGN] Fagus orientalis [Termes IGN] forêt inéquienne [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Iran [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] peuplement mélangé [Termes IGN] régression linéaire [Termes IGN] volume en bois [Vedettes matières IGN] Sylviculture Résumé : (auteur) Key message: We modeled 10-year net stand volume growth with four machine learning (ML) methods, i.e., artificial neural networks (ANN), support vector machines (SVM), random forests (RF), and nearest neighbor analysis (NN), and with linear regression analysis. Incorporating interactions of multiple variables, the ML methods ANN and SVM predicted nonlinear system behavior and unraveled complex relations with greater accuracy than regression analysis. Context: Investigating the quantitative and qualitative characteristics of short-term forest dynamics is essential for testing whether the desired goals in forest-ecosystem conservation and restoration are achieved. Inventory data from the Jojadeh section of the Farim Forest located in the uneven-aged, mixed Hyrcanian Forest were used to model and predict 10-year net annual stand volume increment with new machine learning technologies. Aims: The main objective of this study was to predict net annual stand volume increment as the preeminent factor of forest growth and yield models. Methods: In the current study, volume increment was modeled from two consecutive inventories in 2003 and 2013 using four machine learning techniques that used physiographic data of the forest as input for model development: (i) artificial neural networks (ANN), (ii) support vector machines (SVM), (iii) random forests (RF), and (iv) nearest neighbor analysis (NN). Results from the various machine learning technologies were compared against results produced with regression analysis. Results: ANNs and SVMs with a linear kernel function that incorporated field-measurements of terrain slope and aspect as input variables were able to predict plot-level volume increment with a greater accuracy (94%) than regression analysis (87%). Conclusion: These results provide compelling evidence for the added utility of machine learning technologies for modeling plot-level volume increment in the context of forest dynamics and management. Numéro de notice : A2021-071 Affiliation des auteurs : non IGN Thématique : FORET/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01011-6 date de publication en ligne : 12/01/2021 En ligne : https://doi.org/10.1007/s13595-020-01011-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96794 [article]

Modelling potential density of natural regeneration of European oak species (Quercus robur L., Quercus petraea (Matt.) Liebl.) depending on the distance to the potential seed source: Methodological approach for modelling dispersal from inventory data at forest enterprise level / Maximilian Axer in Forest ecology and management, vol 482 ([15/02/2021])  

Public [article]  inForest ecology and management > vol 482 [15/02/2021] . - n° 118802 Titre : Modelling potential density of natural regeneration of European oak species (Quercus robur L., Quercus petraea (Matt.) Liebl.) depending on the distance to the potential seed source: Methodological approach for modelling dispersal from inventory data at forest enterprise level Type de document : Article/Communication Auteurs : Maximilian Axer, Auteur ; Robert Schlicht, Auteur ; Sven Wagner, Auteur Année de publication : 2021 Article en page(s) : n° 118802 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] conversion forestière [Termes IGN] dispersion [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Pinophyta [Termes IGN] planification [Termes IGN] Quercus pedunculata [Termes IGN] Quercus sessiliflora [Termes IGN] régénération (sylviculture) [Termes IGN] régression quantile [Termes IGN] Saxe (Allemagne) [Termes IGN] semis (sylviculture) [Vedettes matières IGN] Sylviculture Résumé : (auteur) The use of natural oak regeneration from admixed oaks and neighbouring oak stands provides an interesting alternative to cost-intensive artificial oak regeneration when aiming for forest conversion of pure coniferous stands. In this study analysis of forest inventory data is done on how far and in what density natural regeneration of both Pedunculate and Sessile oak occurs in coniferous stands. In order to investigate as exclusively as possible the effect of distance to the seed source on the regeneration density of both oaks, the regeneration potential was determined by using quantile regression. By applying a .995th quantile, reducing factors on seedling density, e.g. desiccation, browsing, pathogens or limited resource availability, were excluded as much as possible. Thus, the effect of zoochorus vectors on effective dispersal could be quantified. The regeneration potential was determined based on data from the forest inventory of the Saxony state forest enterprise, Germany, including 2357 sample plots. Remote sensing data, including the location of oaks in the overstorey, were used to determine the distance to the nearest potential seed source. The results of the present study demonstrate that the highest regeneration densities are not found in the immediate vicinity of the nearest seed source, but at distances between 60 and 140 m to it,i.e. the maximum of seedling density per area unit is in some distance to the trees trunk. In the present study, dispersal distances of established regeneration up to 1565 m were detected. From a distance of 1570–2300 m on, there was no oak regeneration. The results prove that acorns are taken from the seed source and that, in addition to barochorus dispersal, the zoochorus dispersal is of great importance for the succession of coniferous stands. The position of potential seed sources is therefore an important information for silvicultural planning, in order to estimate potential oak regeneration densities. Numéro de notice : A2021-228 Affiliation des auteurs : non IGN Nature : Article DOI : 10.1016/j.foreco.2020.118802 date de publication en ligne : 13/12/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118802 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97208 [article]

Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data / Juan Guerra-Hernández in Forest ecology and management, vol 481 (February 2021)  

Public [article]  inForest ecology and management > vol 481 (February 2021) . - n° 118690 Titre : Developing a site index model for P. Pinaster stands in NW Spain by combining bi-temporal ALS data and environmental data Type de document : Article/Communication Auteurs : Juan Guerra-Hernández, Auteur ; Stefano Arellano-Pérez, Auteur ; Eduardo González-Ferreiro, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 118690 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] anomalie de croissance des arbres [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] échantillonnage [Termes IGN] Galice (Espagne) [Termes IGN] gestion forestière [Termes IGN] hauteur des arbres [Termes IGN] indice de végétation [Termes IGN] inventaire forestier étranger (données) [Termes IGN] lasergrammétrie [Termes IGN] Pinus pinaster [Termes IGN] régression multivariée par spline adaptative [Termes IGN] série temporelle Résumé : (auteur) Site index (SI) is a common measure of forest site productivity, serving as a valuable baseline for forest management. The main objective of this study was to develop a SI model for Pinus pinaster Ait. in north-west Spain by combining bi–temporal, low–density airborne laser scanning (ALS) data (acquired in the periods 2009–2011 and 2015–2017) with climatic, edaphic and physiographical data. Site productivity, assessed by site quality curves, was modelled using an age-independent difference equation method based on ALS metrics and environmental variables. For the model development process, we used data from 156 sample plots in pure and even-aged P. pinaster stands distributed throughout Galicia (NW Spain) and measured in the Spanish National Forest Inventory (SNFI). The generalized algebraic difference approach (GADA) formulation was tested by using two different base equations for modelling the dominant height growth (ΔH) from ALS variables. The GADA formulation derived from the Bertalanffy’s base model produced the best estimates of dominant height (H) for P. pinaster stands in Galicia. Use of the proposed model to estimate ΔH for a new pine stand requires two ALS data sets for estimating site-specific (local) parameters. To enable use of the model when such information is not available, the relationship between the values of the site-specific parameter and environmental variables was described using Multivariate Adaptive Regression Splines (MARS). Use of the MARS equation enabled us to develop spatially-explicit predictive maps of the site-specific parameter values, which can be used together with the GADA model to derive ΔH curves and SI estimates for P. pinaster stands in the whole study region. Numéro de notice : A2021-225 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2020.118690 date de publication en ligne : 01/11/2021 En ligne : https://doi.org/10.1016/j.foreco.2020.118690 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97200 [article]

Long-term tree species population dynamics in Swiss forest reserves influenced by forest structure and climate / A.S. Mathys in Forest ecology and management, vol 481 (February 2021)  

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Stand-scale climate change impacts on forests over large areas: transient responses and projection uncertainties / NIca Huber in Ecological Applications, vol 31 ([01/02/2021])  

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Analyzing the joint effect of forest management and wildfires on living biomass and carbon stocks in Spanish forests / Patricia Adame in Forests, vol 11 n°11 (November 2020)  

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Uncertainty of forested wetland maps derived from aerial photography / Stephen P. Prisley in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 10 (October 2020)  

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Assessing local trends in indicators of ecosystem services with a time series of forest resource maps / Matti Katila in Silva fennica, vol 54 n° 4 (September 2020)  

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Evaluating the accuracy of ALS-based removal estimates against actual logging data / Ville Vähä-Konka in Annals of Forest Science [en ligne], 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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Analysing the quality of Swiss National Forest Inventory measurements of woody species richness / Berthold Traub in Forest ecosystems, vol 7 (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 forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data / Johannes Schumacher in Forest ecosystems, vol 7 (2020)  

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