Détail de l'autorité
|
LUE / Université de Lorraine
Nom :
LUE
titre complet :
Lorraine Université d'Excellence
Auteurs :
Université de Lorraine
|
Documents disponibles (6)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesMultisource 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)
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 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 forestierRésumé : (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
in ISPRS Journal of photogrammetry and remote sensing > vol 192 (October 2022) . - pp 175 - 188[article]
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 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 climatiqueRésumé : (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
in BioScience > vol 72 n° 3 (March 2022) . - pp 233 - 246[article]
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 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 climatiqueRésumé : (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
in Ecosystems > vol 25 n° 2 (March 2022) . - pp 404 - 421[article]
Titre : Inflation of wood resources in European forests: The footprints of a big-bang Type de document : Article/Communication Auteurs : Jean-Daniel Bontemps Année de publication : 2021 Projets : ARBRE / AgroParisTech, LUE / Université de Lorraine Article en page(s) : n° e0259795 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] anthropisation
[Termes IGN] capital sur pied
[Termes IGN] changement climatique
[Termes IGN] dynamique de la végétation
[Termes IGN] exploitation forestière
[Termes IGN] exportation
[Termes IGN] gestion forestière
[Termes IGN] impact sur l'environnement
[Termes IGN] politique forestière
[Termes IGN] politique publique
[Termes IGN] puits de carbone
[Termes IGN] ressources forestières
[Termes IGN] Union Européenne
[Termes IGN] volume en bois
[Vedettes matières IGN] ForesterieRésumé : (auteur) The current increase in European forest resources forms a singularity across the globe. Whether this trend will persist, and how biological and economic trends feature it form crucial issues to green economy challenges and C sequestration. The present screening of Forest Europe 2015 statistics explored the features, inertia and limits of this expansion, and its relationships with countries’ development, forest management and trade, intense in this area of the world. Persisting footprint of past demographic pressure on forests was identified, with opposed traces on their area and growing stock density. Steady growing stock (GS) increases, proportional to GS, not density-limited, and sustained by forest area increases, supported the view of an inflationary forest dynamic. Economic development and liberalism fostered both forest exploitation and production, yielding no significant impact on GS changes. Wood exports exerted a tension on forest exploitation and GS changes, thus lowering GS inflation but providing a resource security margin in the face of expected climate threats. Conflicting a common view, GS inflation and moderate felling-to-increment ratios make increased use of wood resources and C sequestration reconcilable, and GS expansion timely for ongoing EU forest policy processes. Anticipated adverse impacts of ongoing climate change were not clearly identified in these statistics. Numéro de notice : A2021-871 Affiliation des auteurs : LIF (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1371/journal.pone.0259795 Date de publication en ligne : 24/11/2021 En ligne : https://doi.org/10.1371/journal.pone.0259795 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99130
in Plos one > vol 16 n° 11 (November 2021) . - n° e0259795[article]
Titre : A new small area estimation algorithm to balance between statistical precision and scale Type de document : Article/Communication Auteurs : Cédric Vega Année de publication : 2021 Projets : LUE / Université de Lorraine, DIABOLO / Packalen, Tuula, ARBRE/CHM-era / Jolly, Anne Article en page(s) : n° 102303 Note générale : bibliographie
This research was funded by The French Environmental Management Agency (ADEME), grant number 16-60-C0007. The methods and algorithms for processing photogrammetric data were supported by DIABOLO project from the European Union’s Horizon 2020 research and innovation program under grant agreement No 633464, as well as CHM-ERA project from the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE). Ankit Sagar received the financial support of the French PIA project “Lorraine Université d’Excellence”, reference ANR-15-IDEX-04-LUE, through the project Impact DeepSurf.Langues : Anglais (eng) Descripteur : [Termes IGN] arbre BSP
[Termes IGN] capital sur pied
[Termes IGN] données auxiliaires
[Termes IGN] données de terrain
[Termes IGN] estimation bayesienne
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] réduction d'échelle
[Termes IGN] seuillage
[Termes IGN] surface terrière
[Vedettes matières IGN] SylvicultureRésumé : (auteur) Combining national forest inventory (NFI) data with auxiliary information allows downscaling and improving the precision of NFI estimates for small domains, where normally too few field plots are available to produce reliable estimates. In most situations, small domains represent administrative units that could greatly vary in size and forested area. In small and poorly sampled domains, the precision of estimates often drop below expected standards.
To tackle this issue, we introduce a downscaling algorithm generating the smallest possible groups of domains satisfying prescribed sampling density and estimation error. The binary space partitioning algorithm recursively divides the population of domains in two groups while the prescribed precision conditions are fulfilled.
The algorithm was tested on two major forest attributes (i.e. growing stock and basal area) in an area of 7,500 km2 dominated by hardwood forests in the centre of France. The estimation domains consisted in 157 municipalities. The field data included 819 NFI plots surveyed during a 5 years period. The auxiliary data consisted in 48 metrics derived from a forest map, photogrammetric models and Landsat images. A model-assisted framework was used for estimation. For each forest attribute, the best model was selected using a best-subset approach using a Bayesian Information Criteria. The retained models explained 58% and 41% of the observed variance for the growing stocks and basal areas respectively. The performance of the algorithm was evaluated using a minimum of 3 NFI points per domain and estimation errors varying from 10 to 50%.
For a target estimation error set to 10%, the algorithm led to a limited number of estimation domains ( The algorithm provides a flexible estimation framework for small area estimation. The key advantages of the approach are relying on its capacity to produce estimations based on a preselected precision threshold and to produce results over the whole area of interest, avoiding areas without any estimates. The algorithm could also be used on any kind of polygon layers (not only administrative ones), provided that the field sampling design enable estimation. This makes the proposed algorithm a convenient tool notably for decision makers and forest managers.Numéro de notice : A2021-067 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2021.102303 Date de publication en ligne : 25/01/2021 En ligne : https://doi.org/10.1016/j.jag.2021.102303 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96992
in International journal of applied Earth observation and geoinformation > vol 97 (May 2021) . - n° 102303[article]Permalink
