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Identification and spatial extent of understory plant species requiring vegetation control to ensure tree regeneration in French forests / Noé Dumas in Annals of Forest Science, vol 79 n° 1 (2022)  

Public [article]  inAnnals of Forest Science > vol 79 n° 1 (2022) . - n° 41 Titre : Identification and spatial extent of understory plant species requiring vegetation control to ensure tree regeneration in French forests Type de document : Article/Communication Auteurs : Noé Dumas, Auteur ; Jean-Luc Dupouey, Auteur ; Jean-Claude Gégout, Auteur ; Vincent Boulanger, Auteur ; Jean-Daniel Bontemps , Auteur ; François Morneau , Auteur ; Marine Dalmasso , Auteur ; Catherine Collet, Auteur Année de publication : 2022 Projets : ARBRE / AgroParisTech (2007 -) Article en page(s) : n° 41 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] contrôle de la végétation [Termes IGN] coopérative forestière [Termes IGN] distribution spatiale [Termes IGN] enquête [Termes IGN] France (végétation) [Termes IGN] gestion forestière durable [Termes IGN] inventaire forestier national (données France) [Termes IGN] Molinia caerulea [Termes IGN] propriétaire forestier [Termes IGN] Pteridium aquilinum [Termes IGN] régénération (sylviculture) [Termes IGN] Rubus fruticosus [Termes IGN] sous-bois [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Key message: Fifteen species are most susceptible to require vegetation control during tree regeneration in the range of our study. Among these 15 species, Rubus fruticosus, Pteridium aquilinum, and Molinia caerulea cover each more than 300,000 ha of open-canopy forests. Context: Vegetation control, i.e., the reduction of competitive species cover, is often required to promote tree seedling establishment during the forest regeneration stage. The necessity to control understory vegetation largely depends on the species to be controlled. In order to plan forest renewal operations, it is critical to identify which species require vegetation control during the regeneration stage and to quantify the forest area affected by these species. Aims: We aimed at identifying the main species requiring vegetation control and at estimating the forest area they cover at the national level. Methods: Using National Forest Inventory data, we created four indicators based on two levels of plant cover, cross-referenced with two levels of canopy opening, and compared them to the outcome of a survey of forest manager practices. Results: The best indicator was the one that represented the proportion of forests with open canopy where the species was present with a large cover in the understory. In non-Mediterranean France, according to the indicator, a total of 15 species were found to frequently require vegetation control during the tree regeneration stage. Pteridium aquilinum, Molinia caerulea, and Rubus fruticosus were the main species, and each covered more than 300,000 ha of forest with open canopies, representing about 13% of the total forest area with open canopies outside of the Mediterranean area. Conclusions: Forests covered by species requiring vegetation control according to forest managers represent a large share of the forest area undergoing regeneration. This study provides the first list of species that require vegetation control based on a methodological protocol that makes it possible to calculate the area associated with each species. Numéro de notice : A2022-730 Affiliation des auteurs : LIF+Ext (2020- ) Autre URL associée : vers HAL Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s13595-022-01160-w Date de publication en ligne : 22/09/2022 En ligne : https://doi.org/10.1186/s13595-022-01160-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101681 [article]

Modelling forest volume with small area estimation of forest inventory using GEDI footprints as auxiliary information / Shaohui Zhang in International journal of applied Earth observation and geoinformation, vol 114 (November 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 114 (November 2022) . - n° 103072 Titre : Modelling forest volume with small area estimation of forest inventory using GEDI footprints as auxiliary information Type de document : Article/Communication Auteurs : Shaohui Zhang, Auteur ; Cédric Vega , Auteur ; Christine Deleuze, Auteur ; Sylvie Durrieu, Auteur ; Pierre Barbillon, Auteur ; Olivier Bouriaud , Auteur ; Jean-Pierre Renaud , Auteur Année de publication : 2022 Projets : ARBRE / AgroParisTech (2007 -) Article en page(s) : n° 103072 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] empreinte [Termes IGN] gestion forestière [Termes IGN] Global Ecosystem Dynamics Investigation lidar [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier local [Termes IGN] inventaire forestier national (données France) [Termes IGN] modèle numérique de terrain [Termes IGN] modélisation de la forêt [Termes IGN] placette d'échantillonnage [Termes IGN] Sologne (France) [Termes IGN] variogramme [Termes IGN] volume en bois Résumé : (auteur) The French National Forest Inventory provides detailed forest information up to large national and regional scales. Forest inventory for small areas of interest within a large population is equally important for decision making, such as for local forest planning and management purposes. However, sampling these small areas with sufficient ground plots is often not cost efficient. In response, small area estimation has gained increasing popularity in forest inventory. It consists of a set of techniques that enables predictions of forest attributes of subpopulation with the help of auxiliary information that compensates for the small field samples. Common sources of auxiliary information usually come from remote sensing technology, such as airborne laser scanning and satellite imagery. The newly launched NASA’s Global Ecosystem Dynamics Investigation (GEDI), a full waveform Lidar instrument, provides an unprecedented opportunity of collecting large-scale and dense forest sample plots given its sampling frequency and spatial coverage. However, the geolocation uncertainty associated with GEDI footprints create important challenges for their use for small area estimations. In this study, we designed a process that provides NFI measurements at plot level with GEDI auxiliary information from nearby footprints. We demonstrated that GEDI RH98 is equivalent to NFI dominant height at plot level. We stressed the importance of pairing NFI plots with nearby GEDI footprints, based on not only the distance in between but also their similarities, i.e., forest heights and forest types. Subsequently, these NFI-GEDI pairs were used for small area estimations following a two-phase sampling scheme. We showcased that, with an adequate sample size, small area estimation with GEDI auxiliary data can improve the accuracy of forest volume estimates. Numéro de notice : A2022-786 Affiliation des auteurs : LIF+Ext (2020- ) Autre URL associée : vers HAL Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2022.103072 Date de publication en ligne : 22/10/2022 En ligne : https://doi.org/10.1016/j.jag.2022.103072 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101890 [article]

Multisource forest inventories: A model-based approach using k-NN to reconcile forest attributes statistics and map products / Ankit Sagar in ISPRS Journal of photogrammetry and remote sensing, vol 192 (October 2022)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 192 (October 2022) . - pp 175 - 188 Titre : Multisource forest inventories: A model-based approach using k-NN to reconcile forest attributes statistics and map products Type de document : Article/Communication Auteurs : Ankit Sagar , Auteur ; Cédric Vega , Auteur ; Olivier Bouriaud , Auteur ; Christian Piedallu, Auteur ; Jean-Pierre Renaud , Auteur Année de publication : 2022 Projets : LUE / Université de Lorraine, ARBRE / AgroParisTech (2007 -), DEEPSURF / Pironon, Jacques Article en page(s) : pp 175 - 188 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification barycentrique [Termes IGN] données allométriques [Termes IGN] données lidar [Termes IGN] image Landsat-8 [Termes IGN] inventaire forestier national (données France) [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Forest map products are widely used and have taken benefit from progresses in the multisource forest inventory approaches, which are meant to improve the precision of forest inventory estimates at high spatial resolution. However, estimating errors of pixel-wise predictions remains difficult, and reconciling statistical outcomes with map products is still an open and important question. We address this problem using an original approach relying on a model-based inference framework and k-nearest neighbours (k-NN) models to produce pixel-wise estimations and related quality assessment. Our approach takes advantage of the resampling properties of a model-based estimator and combines it with geometrical convex-hull models to measure respectively the precision and accuracy of pixel predictions. A measure of pixel reliability was obtained by combining precision and accuracy. The study was carried out over a 7,694 km2 area dominated by structurally complex broadleaved forests in centre of France. The targeted forest attributes were growing stock volume, basal area and growing stock volume increment. A total of 819 national forest inventory plots were combined with auxiliary data extracted from a forest map, Landsat 8 images, and 3D point clouds from both airborne laser scanning and digital aerial photogrammetry. k-NN models were built independently for both 3D data sources. Both selected models included 5 auxiliary variables, and were generated using 5 neighbours, and most similar neighbours distance measure. The models showed relative root mean square error ranging from 35.7% (basal area, digital aerial photogrammetry) in calibration to 63.4% (growing stock volume increment, airborne laser scanning) in the validation set. At pixel level, we found that a minimum of 86.4% of the predictions were of high precision as their bootstrapped coefficient of variation fall below calibration’s relative root mean square error. The amount of extrapolation varied from 4.3% (digital aerial photogrammetry) to 6.3% (airborne laser scanning). A relationship was found between extrapolation and k-NN distance, opening new opportunities to correct extrapolation errors. At the population level, airborne laser scanning and digital aerial photogrammetry performed similarly, offering the possibility to use digital aerial photogrammetry for monitoring purposes. The proposed method provided consistent estimates of forest attributes and maps, and also provided spatially explicit information about pixel predictions in terms of precision, accuracy and reliability. The method therefore produced high resolution outputs, significant for either decision making or forest management purposes. Numéro de notice : A2022-629 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.08.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.08.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101495 [article]

Characterizing the calibration domain of remote sensing models using convex hulls / Jean-Pierre Renaud in International journal of applied Earth observation and geoinformation, vol 112 (August 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 112 (August 2022) . - n° 102939 Titre : Characterizing the calibration domain of remote sensing models using convex hulls Type de document : Article/Communication Auteurs : Jean-Pierre Renaud , Auteur ; Ankit Sagar , Auteur ; Pierre Barbillon, Auteur ; Olivier Bouriaud , Auteur ; Christine Deleuze, Auteur ; Cédric Vega , Auteur Année de publication : 2022 Projets : DEEPSURF / Pironon, Jacques, ARBRE / AgroParisTech (2007 -) Article en page(s) : n° 102939 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques [Termes IGN] données allométriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] échantillonnage [Termes IGN] erreur systématique [Termes IGN] étalonnage de modèle [Termes IGN] étalonnage des données [Termes IGN] extrapolation [Termes IGN] placette d'échantillonnage Résumé : (auteur) The ever-increasing availability of remote sensing data allows production of forest attributes maps, which are usually made using model-based approaches. These map products are sensitive to various bias sources, including model extrapolation. To identify, over a case study forest, the proportion of extrapolated predictions, we used a convex hull method applied to the auxiliary data space of an airborne laser scanning (ALS) flight. The impact of different sampling efforts was also evaluated. This was done by iteratively thinning a set of 487 systematic plots using nested sub-grids allowing to divide the sample by two at each level. The analysis were conducted for all alternative samples and evaluated against 56 independent validation plots. Residuals of the extrapolated validation plots were computed and examined as a function of their distance to the model calibration domain. Extrapolation was also characterized for the pixels of the area of interest (AOI) to upscale at population level. Results showed that the proportion of extrapolated pixels greatly reduced with an increasing sampling effort. It reached a plateau (ca. 20% extrapolation) with a sampling intensity of ca. 250-calibration plots. This contrasts with results on model’s root mean squared error (RMSE), which reached a plateau at a much lower sampling intensity. This result emphasizes the fact that with a low sampling effort, extrapolation risk remains high, even at a relatively low RMSE. For all attributes examined (i.e., stand density, basal area, and quadratic mean diameter) estimations were generally found to be biased for validation plots that were extrapolated. The method allows an easy identification of map pixels that are out of the calibration domain, making it an interesting tool to evaluate model transferability over an area of interest (AOI). It could also serve to compare “competing” models at a variable selection phase. From a model calibration perspective, it could serve a posteriori, to evaluate areas (in the auxiliary space) that merit further sampling efforts to improve model reliability. Numéro de notice : A2022-581 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2022.102939 Date de publication en ligne : 28/07/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102939 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101341 [article]

Modeling and propagating inventory-based sampling uncertainty in the large-scale forest demographic model “MARGOT” / Timothée Audinot in Natural Resource Modelling, vol 35 n° 3 (August 2022)  

Public [article]  inNatural Resource Modelling > vol 35 n° 3 (August 2022) . - n° e12352 Titre : Modeling and propagating inventory-based sampling uncertainty in the large-scale forest demographic model “MARGOT” Type de document : Article/Communication Auteurs : Timothée Audinot , Auteur ; Holger Wernsdörfer, Auteur ; Gilles Le Moguédec, Auteur ; Jean-Daniel Bontemps , Auteur Année de publication : 2022 Projets : ModForTrans / Bontemps, Jean-Daniel, ARBRE / AgroParisTech (2007 -) Article en page(s) : n° e12352 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] incertitude des données [Termes IGN] inventaire forestier national (données France) [Termes IGN] modélisation de la forêt [Termes IGN] propagation d'incertitude [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Models based on national forest inventory (NFI) data intend to project forests under management and policy scenarios. This study aimed at quantifying the influence of NFI sampling uncertainty on parameters and simulations of the demographic model MARGOT. Parameter variance–covariance structure was estimated from bootstrap sampling of NFI field plots. Parameter variances and distributions were further modeled to serve as a plug-in option to any inventory-based initial condition. Forty-year time series of observed forest growing stock were compared with model simulations to balance model uncertainty and bias. Variance models showed high accuracies. The Gamma distribution best fitted the distributions of transition, mortality and felling rates, while the Gaussian distribution best fitted tree recruitment fluxes. Simulation uncertainty amounted to 12% of the model bias at the country scale. Parameter covariance structure increased simulation uncertainty by 5.5% in this 12%. This uncertainty appraisal allows targeting model bias as a modeling priority. Numéro de notice : A2022-576 Affiliation des auteurs : LIF+Ext (2020- ) Autre URL associée : vers HAL Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/nrm.12352 Date de publication en ligne : 08/08/2022 En ligne : https://doi.org/10.1111/nrm.12352 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101333 [article]

Adding tree rings to North America's national forest inventories: An essential tool to guide drawdown of atmospheric CO2 / Margaret E.K. Evans in BioScience, vol 72 n° 3 (March 2022)  

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Unexpected negative effect of available water capacity detected on recent conifer forest growth trends across wide environmental gradients / Clémentine Ols in Ecosystems, vol 25 n° 2 (March 2022)  

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A limited number of species is sufficient to assign a vegetation plot to a forest vegetation unit / Lise Maciejewski in Applied Vegetation Science, vol 25 n° 1 (January/March 2022)  

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A square-grid sampling support to reconcile systematicity and adaptivity in the periodic spatial survey of natural resources / Olivier Bouriaud (2022)  

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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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Inflation of wood resources in European forests: The footprints of a big-bang / Jean-Daniel Bontemps in Plos one, vol 16 n° 11 (November 2021)  

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Effects of thinning practice, high pruning and slash management on crop tree and stand growth in young even-aged stands of planted silver birch (Betula pendula Roth) / Jens Peter Skovsgaard in Forests, vol 12 n° 2 (February 2021)  

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Convex hull: another perspective about model predictions and map derivatives from remote sensing data / Jean-Pierre Renaud (2021)  

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High resolution mapping of forest resources and prediction reliability using multisource inventory approach / Ankit Sagar (2021)    

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Reply to Elmendorf and Ettinger: Photoperiod plays a dominant and irreplaceable role in triggering secondary growth resumption / Jian-Guo Huang in Proceedings of the National Academy of Sciences of the United States of America PNAS, vol 117 n° 52 (December 2020)  

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