Centre de documentation
scientifique

FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach / Martin Schwartz in Earth System Science Data, vol 15 n° inconnu (2023)  

Public [article]  inEarth System Science Data > vol 15 n° inconnu (2023) Titre : FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach Type de document : Article/Communication Auteurs : Martin Schwartz, Auteur ; Philippe Ciais, Auteur ; Aurélien de Truchis, Auteur ; Jérôme Chave, Auteur ; Catherine Ottle, Auteur ; Cédric Vega , Auteur ; Jean-Pierre Wigneron, Auteur ; et al., Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond [Termes IGN] biomasse aérienne [Termes IGN] données allométriques [Termes IGN] Global Ecosystem Dynamics Investigation lidar [Termes IGN] hauteur des arbres [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] inventaire forestier national (données France) [Termes IGN] modèle numérique de surface de la canopée [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) The contribution of forests to carbon storage and biodiversity conservation highlights the need for accurate forest height and biomass mapping and monitoring. In France, forests are managed mainly by private owners and divided into small stands, requiring 10 to 50 m spatial resolution data to be correctly separated. Further, 35 % of the French forest territory is covered by mountains and Mediterranean forests which are managed very extensively. In this work, we used a deep-learning model based on multi-stream remote sensing measurements (NASA’s GEDI LiDAR mission and ESA’s Copernicus Sentinel 1 & 2 satellites) to create a 10 m resolution canopy height map of France for 2020 (FORMS-H). In a second step, with allometric equations fitted to the French National Forest Inventory (NFI) plot data, we created a 30 m resolution above-ground biomass density (AGBD) map (Mg ha-1) of France (FORMS-B). Extensive validation was conducted. First, independent datasets from Airborne Laser Scanning (ALS) and NFI data from thousands of plots reveal a mean absolute error (MAE) of 2.94 m for FORMS-H, which outperforms existing canopy height models. Second, FORMS-B was validated using two independent forest inventory datasets from the Renecofor permanent forest plot network and from the GLORIE forest inventory with MAE of 59.6 Mg ha-1 and 19.6 Mg.ha-1 respectively, providing greater performance than other AGBD products sampled over France. These results highlight the importance of coupling remote sensing technologies with recent advances in computer science to bring material insights to climate-efficient forest management policies. Additionally, our approach is based on open-access data having global coverage and a high spatial and temporal resolution, making the maps reproducible and easily scalable. FORMS products can be accessed from https://doi.org/10.5281/zenodo.7840108 (Schwartz et al., 2023). Numéro de notice : A2023-179 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/essd-2023-196 En ligne : https://doi.org/10.5194/essd-2023-196 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103341 [article]

Ensure forest-data integrity for climate change studies / Risto Päivinen in Nature climat change, vol 13 n° inconnu ([01/05/2023])  

Public [article]  inNature climat change > vol 13 n° inconnu [01/05/2023] . - pp 495 - 496 Titre : Ensure forest-data integrity for climate change studies Type de document : Article/Communication Auteurs : Risto Päivinen, Auteur ; Rasmus Astrup, Auteur ; Richard A. Birdsey, Auteur ; Johannes Breidenbach, Auteur ; Jonas Fridman, Auteur ; Annika S. Kangas, Auteur ; Pekka E. Kauppi, Auteur ; Mickael Kohl, Auteur ; Kari T. Korhonen, Auteur ; Vivian Kvist Johannsen, Auteur ; François Morneau , Auteur ; Thomas Riedel, Auteur ; Klemens Schadauer, Auteur ; Iddo K. Wernick, Auteur Année de publication : 2023 Article en page(s) : pp 495 - 496 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique [Termes IGN] intégrité des données [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Forest inventory observations are critical for monitoring the contribution of terrestrial ecosystems to the global carbon cycle and a changing climate1. Like all scientific data, ensuring open access to forest data generally serves to secure the integrity of the data and facilitate climt mitigation efforts. ... Numéro de notice : A2023-175 Affiliation des auteurs : IGN+Ext (2020- ) Thématique : BIODIVERSITE/FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1038/s41558-023-01683-8 Date de publication en ligne : 22/05/2023 En ligne : https://doi.org/10.1038/s41558-023-01683-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103294 [article]

Evaluation of growth models for mixed forests used in Swedish and Finnish decision support systems / Jorge Aldea in Forest ecology and management, vol 529 (February-1 2023)  

Public [article]  inForest ecology and management > vol 529 (February-1 2023) . - n° 120721 Titre : Evaluation of growth models for mixed forests used in Swedish and Finnish decision support systems Type de document : Article/Communication Auteurs : Jorge Aldea, Auteur ; Simone Bianchi, Auteur ; Urban Nilsson, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120721 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Betula (genre) [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] peuplement mélangé [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] Suède [Termes IGN] système d'aide à la décision [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Interest in mixed forests is increasing since they could provide higher benefits and positive externalities compared to monocultures, although their management is more complex and silvicultural prescriptions for them are still scarce. Growth simulations are a powerful tool for developing useful guidelines for mixed stands. Heureka and Motti are two decision support systems commonly used for forest management in Sweden and Finland respectively. They were developed mostly with data from pure stands, so how they would perform in mixed stands is currently uncertain. We compiled a large and updated common database of well-replicated experimental research sites and monitoring networks composed by 218 and 1,160 plot-level observations of mixed stands from Sweden and Finland, respectively. We aimed to evaluated the accuracy of Heureka and Motti basal area growth models in those mixed-species stands and to detect any bias in their short-term predictions. Basal area growth simulations (excluding mortality models) were compared to observed stand-level values in a period-wise process with update of the start values in each period. The residual plots were visually examined for different stand mixtures: Norway spruce (Picea abies Karst.)-birch (Betula spp), Scots pine (Pinus sylvestris L.)-birch and Scots pine-Norway spruce. We observed that the basal area growth models in both decision support systems performed quite well for all mixtures regardless of the proportion of species. Motti simulations overestimated growth in Scots pine-Norway spruce mixtures by 0.063 m2·ha−1·year−1 which may be acceptable for practical use. Therefore, we corroborated that both decision support systems can be currently utilized for short-term forest growth simulation of mixed boreal forests. Numéro de notice : A2023-107 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120721 Date de publication en ligne : 28/12/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120721 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102441 [article]

Improving quantitative structure models with an Huxley protocol based filter / Jan Hackenberg in Applied geomatics, vol 15 n° inconnu (2023)

Public [article]  inApplied geomatics > vol 15 n° inconnu (2023) Titre : Improving quantitative structure models with an Huxley protocol based filter Type de document : Article/Communication Auteurs : Jan Hackenberg , Auteur ; Jean-Daniel Bontemps , Auteur Année de publication : 2023 Note générale : bibliographie preprint https://doi.org/10.21203/rs.3.rs-2818844/v1 Langues : Anglais (eng) Descripteur : [Termes IGN] données localisées 3D [Termes IGN] modélisation de la forêt [Termes IGN] semis de points [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Quantitative structure models (QSMs) are topological ordered cylinder models of trees which describe the branching structure up to the tips. Methods : We present unpublished tree describing parameters which can be derived [rein a single Quantitative Structure Model QSM. The parameters are used to build two Radius correction filters. Results : For validation we use QSMs produced from an open point cloud data set of tree clouds with the SimpleForest software. We coin-pare the QSM volume against the harvested reference data for 65 felled trees. We also found QSM data of Tree QSM, a competitive and broadly accepted QSM modeling tool. Our RMSE was less than 40 % of the TreeQSM RMSE. For other error measures, the r2adi and the CCC, the relative improvement looked even better with reaching only 27 % and 21 % of the TreeQSM errors respectively. Conclusions: In forest ecology we should use the here presented pipeline to build accurate CPIs for reasons of: Quality - With the invention of the QSM Radius filter techniques we improve tree volume prediction capabilities utilizing QSMs. Quantity - More data can be collected with QSMs than with traditional methods. Here we use models build on more than ten thousand measurements. Numéro de notice : A2023-178 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET/INFORMATIQUE/MATHEMATIQUE Nature : Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103320 [article]

Forest Inventory and Analysis Fiscal Year 2021 : Business Report / Mila Alvarez (2023)  

Public Titre : Forest Inventory and Analysis Fiscal Year 2021 : Business Report Type de document : Rapport Auteurs : Mila Alvarez, Auteur ; United States forest service, Auteur Editeur : Radnor [Etats-Unis] : United States Department of Agriculture, Forest Service Année de publication : 2023 Conférence : FIAS 2006, 8th Annual Forest Inventory and Analysis Symposium 16/10/2006 19/10/2006 Monterey Californie - Etats-Unis OA Proceedings Importance : 92 p. Note générale : FS-1212 Langues : Anglais (eng) Descripteur : [Termes IGN] Etats-Unis [Termes IGN] inventaire forestier étranger (données) [Vedettes matières IGN] Inventaire forestier Numéro de notice : 17754 Affiliation des auteurs : non IGN Thématique : FORET Nature : Rapport DOI : sans En ligne : https://www.fs.usda.gov/sites/default/files/fs_media/fs_document/FIA-2021-Busine [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103176

La forêt progresse mais la mortalité des arbres s’accroît / Anonyme in Géomètre, n° 2209 (janvier 2023)

Permalink

Taller and slenderer trees in Swedish forests according to data from the National Forest Inventory / Alex Appiah Mensah in Forest ecology and management, vol 527 (January-1 2023)  

Permalink

Comparison of methods for the automatic classification of forest habitat types in the Southern Alps : Application to ecological data from the French national forest inventory / Charlotte Labit in Biodiversity & Conservation, vol 31 n° 13-14 (December 2022)  

Permalink

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)  

Permalink

An estimation method to reduce complete and partial nonresponse bias in forest inventory / James A. Westfall in European Journal of Forest Research, vol 141 n° 5 (October 2022)  

Permalink

Caractériser l’environnement compétitif des arbres : dépassons la surface terrière ! / Thomas Cordonnier in Revue forestière française, vol 73 n° 6 (2021)  

Permalink

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)  

Permalink

Using multi-temporal tree inventory data in eucalypt forestry to benchmark global high-resolution canopy height models. A showcase in Mato Grosso, Brazil / Adrián Pascual in Ecological Informatics, vol 70 (September 2022)  

Permalink

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)  

Permalink

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)  

Permalink