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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, 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 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 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- ) 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 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)  

Public [article]  inBioScience > vol 72 n° 3 (March 2022) . - pp 233 - 246 Titre : Adding tree rings to North America's national forest inventories: An essential tool to guide drawdown of atmospheric CO2 Type de document : Article/Communication Auteurs : Margaret E.K. Evans, Auteur ; R. Justin DeRose, Auteur ; Stefan Klesse, Auteur ; Martin P. Girardin, Auteur ; Kelly A. Heilman, Auteur ; M. Ross Alexander, Auteur ; André Arsenault, Auteur ; Flurin Babst, Auteur ; Mathieu Bouchard, Auteur ; Sean M. P. Cahoon, Auteur ; Elisabeth M. Campbell, Auteur ; Michael Dietze, Auteur ; Louis Duchesne, Auteur ; David Frank, Auteur ; Courtney L. Giebink, Auteur ; Armando Gómez-Guerrero, Auteur ; Genaro Gutiérrez García, Auteur ; Edward H. Hogg, Auteur ; Juha Metsaranta, Auteur ; Clémentine Ols , Auteur ; et al., Auteur Année de publication : 2022 Projets : ARBRE / AgroParisTech, LUE / Université de Lorraine Article en page(s) : pp 233 - 246 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Amérique du nord [Termes IGN] cerne [Termes IGN] dendrochronologie [Termes IGN] dioxyde de carbone [Termes IGN] gaz à effet de serre [Termes IGN] inventaire forestier étranger (données) [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Tree-ring time series provide long-term, annually resolved information on the growth of trees. When sampled in a systematic context, tree-ring data can be scaled to estimate the forest carbon capture and storage of landscapes, biomes, and—ultimately—the globe. A systematic effort to sample tree rings in national forest inventories would yield unprecedented temporal and spatial resolution of forest carbon dynamics and help resolve key scientific uncertainties, which we highlight in terms of evidence for forest greening (enhanced growth) versus browning (reduced growth, increased mortality). We describe jump-starting a tree-ring collection across the continent of North America, given the commitments of Canada, the United States, and Mexico to visit forest inventory plots, along with existing legacy collections. Failing to do so would be a missed opportunity to help chart an evidence-based path toward meeting national commitments to reduce net greenhouse gas emissions, urgently needed for climate stabilization and repair. Numéro de notice : A2022-031 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/biosci/biab119 Date de publication en ligne : 08/12/2021 En ligne : https://doi.org/10.1093/biosci/biab119 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99282 [article]

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)  

Public [article]  inEcosystems > vol 25 n° 2 (March 2022) . - pp 404 - 421 Titre : Unexpected negative effect of available water capacity detected on recent conifer forest growth trends across wide environmental gradients Type de document : Article/Communication Auteurs : Clémentine Ols , Auteur ; Thomas Gschwantner, Auteur ; Klemens Schadauer, Auteur ; Jean-Daniel Bontemps , Auteur Année de publication : 2022 Projets : ARBRE / AgroParisTech, LUE / Université de Lorraine Article en page(s) : pp 404 - 421 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] analyse diachronique [Termes IGN] Autriche [Termes IGN] cerne [Termes IGN] changement climatique [Termes IGN] croissance des arbres [Termes IGN] gradient d'altitude [Termes IGN] hétérogénéité environnementale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] inventaire forestier national (données France) [Termes IGN] Larix decidua [Termes IGN] modèle de croissance végétale [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] ressources en eau [Termes IGN] structure d'un peuplement forestier [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) National Forest Inventories (NFIs) perform systematic forest surveys across space and time. They are hence powerful tools to understand climate controls on forest growth at wide geographical scales and account for the effects of local abiotic and biotic interactions. To investigate the effects of climate change upon growth dynamics of four major European conifer species along elevation and continentality gradients, we herein provide an original harmonization of the French and Austrian NFI datasets. The growth of Norway spruce, Scots pine, silver fir and European larch over the 1996–2016 period was studied in pure and even-aged plots across different ecological regions. We derived climate-driven growth trends from > 65, 000 radial increment series filtered out from major biotic and abiotic influences using statistical modeling. We further identified primary environmental drivers of conifer growth by regressing growth trends against regionally aggregated biotic and abiotic forest attributes. Negative growth trends were observed in continental regions undergoing the most rapid warming and thermal amplitude contraction over the study period. Negative trends were also associated with lower forest structural heterogeneity and, surprisingly, with greater available water capacity. Remarkably, we observed these associations both at the inter- and intra-species levels, suggesting the universality of these primary growth determinants. Our study shows that harmonized NFI data at the transnational level provide reliable information on climate–growth interactions. Here, greater forest structural complexity and greater water resource limitation were highlighted as drivers of greater forest resilience to climate change at large-scale. This result forms crucial bases to implementing climate-smart forest management. Numéro de notice : A2022-023 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10021-021-00663-3 En ligne : https://doi.org/10.1007/s10021-021-00663-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98116 [article]

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

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Ancient forest statistics provide centennial perspective over the status and dynamics of forest area in France / Timothée Audinot in Annals of Forest Science, vol 77 n° 3 (September 2020)  

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