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DIABOLO / Packalen, Tuula
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DIABOLO
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Distributed, integrated and harmonised forest information for bioeconomy outlooks
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Packalen, Tuula
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Affiner la recherche Interroger des sources externesA new small area estimation algorithm to balance between statistical precision and scale / Cédric Vega in International journal of applied Earth observation and geoinformation, vol 97 (May 2021)
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]
Titre : Harmonised projections of future forest resources in Europe Type de document : Article/Communication Auteurs : Jari Vauhkonen, Auteur ; Ambros Berger, Auteur ; Thomas Gschwantner, Auteur ; Klemens Schadauer, Auteur ; Philippe Lejeune, Auteur ; Jérôme Perin, Auteur ; Radim Adolt, Auteur ; Miroslav Zeman, Auteur ; Vivian Kvist Johannsen, Auteur ; Sebastian Kepfer-Rojas, Auteur ; Allan Sims, Auteur ; Claire Bastick Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Article en page(s) : n° 79 Note générale : bibliographie
Correction de cet article https://link.springer.com/article/10.1007%2Fs13595-019-0872-5Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse
[Termes IGN] bois sur pied
[Termes IGN] Europe (géographie politique)
[Termes IGN] foresterie
[Termes IGN] gestion forestière durable
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] politique forestière
[Termes IGN] prévision
[Termes IGN] puits de carbone
[Termes IGN] ressources forestières
[Vedettes matières IGN] Economie forestièreRésumé : (auteur) A dataset of forest resource projections in 23 European countries to 2040 has been prepared for forest-related policy analysis and decision-making. Due to applying harmonised definitions, while maintaining country-specific forestry practices, the projections should be usable from national to international levels. The dataset can be accessed at https://doi.org/10.5061/dryad.4t880qh . The associated metadata are available at https://metadata-afs.nancy.inra.fr/geonetwork/srv/eng/catalog.search#/metadata/8f93e0d6-b524-43bd-bdb8-621ad5ae6fa9 Numéro de notice : A2019-322 Affiliation des auteurs : IGN+Ext (2012-2019) Autre URL associée : correction de l'article Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0863-6 Date de publication en ligne : 29/07/2019 En ligne : https://doi.org/10.1007/s13595-019-0863-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93299
in Annals of Forest Science > Vol 76 n° 3 (September 2019) . - n° 79[article]
Titre : Increasing precision for French forest inventory estimates using the k-NN technique with optical and photogrammetric data and model-assisted estimators Type de document : Article/Communication Auteurs : Dinesh Babu Irulappa-Pillai-Vijayakumar Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Article en page(s) : n° 991 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre caducifolié
[Termes IGN] classification barycentrique
[Termes IGN] feuillu
[Termes IGN] image Landsat-8
[Termes IGN] inférence statistique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Orléans, forêt domaniale d' (Loiret)
[Termes IGN] photogrammétrie numérique
[Termes IGN] Pinus pinaster
[Termes IGN] Pinus sylvestris
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus sessiliflora
[Termes IGN] Sologne (France)
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Multisource forest inventory methods were developed to improve the precision of national forest inventory estimates. These methods rely on the combination of inventory data and auxiliary information correlated with forest attributes of interest. As these methods have been predominantly tested over coniferous forests, the present study used this approach for heterogeneous and complex deciduous forests in the center of France. The auxiliary data considered included a forest type map, Landsat 8 spectral bands and derived vegetation indexes, and 3D variables derived from photogrammetric canopy height models. On a subset area, changes in canopy height estimated from two successive photogrammetric models were also used. A model-assisted inference framework, using a k nearest-neighbors approach, was used to predict 11 field inventory variables simultaneously. The results showed that among the auxiliary variables tested, 3D metrics improved the precision of dendrometric estimates more than other auxiliary variables. Relative efficiencies (RE) varying from 2.15 for volume to 1.04 for stand density were obtained using all auxiliary variables. Canopy height changes also increased RE from 3% to 26%. Our results confirmed the importance of 3D metrics as auxiliary variables and demonstrated the value of canopy change variables for increasing the precision of estimates of forest structural attributes such as density and quadratic mean diameter. Numéro de notice : A2019-382 Affiliation des auteurs : LIF+Ext (2012-2019) Autre URL associée : vers HAL Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11080991 Date de publication en ligne : 25/04/2019 En ligne : https://doi.org/10.3390/rs11080991 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93456
in Remote sensing > vol 11 n° 8 (August 2019) . - n° 991[article]
Titre : RegisTree: a registration algorithm to enhance forest inventory plot georeferencing Type de document : Article/Communication Auteurs : Maryem Fadili Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Article en page(s) : n° 30 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] placette d'échantillonnage
[Termes IGN] superposition de donnéesRésumé : (auteur) Key message : The accuracy of remote sensing-based models of forest attributes could be improved by controlling the spatial registration of field and remote sensing data. We have demonstrated the potential of an algorithm matching plot-level field tree positions with lidar canopy height models and derived local maxima to achieve a precise registration automatically.
Context : The accuracy of remote sensing-based estimates of forest parameters depends on the quality of the spatial registration of the training data.
Aims : This study introduces an algorithm called RegisTree to correct field plot positions by matching a spatialized field tree height map with lidar canopy height models (CHMs).
Methods : RegisTree is based on a point (field positions) to surface (CHM) adjustment approach modified to ensure that at least one field tree position corresponds to CHM local maxima.
Results : RegisTree has been validated with respect to positioning errors and the performance of lidar-derived estimation of plot volume. Overall, RegisTree enabled to register field plots surveyed in a range of forest conditions with a precision of 1.5 m (± 1.23 m), but a higher performance for conifer plots, and a limited efficiency in homogeneous stands, having similar heights. Improved plot positions were found to have a limited impact on volume predictions under the range of tested conditions, with a gain up to 1.3%.
Conclusion : RegisTree could be used to improve the forest plot position from field surveys collected with low-grade GPS and to contribute to the development of processing chains of 3D remote sensing-based models of forest parameters.Numéro de notice : A2019-339 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0814-2 Date de publication en ligne : 02/04/2019 En ligne : http://dx.doi.org/10.1007/s13595-019-0814-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93373
in Annals of Forest Science > vol 76 n° 2 (June 2019) . - n° 30[article]
Titre : The conservation status assessment of Natura 2000 forest habitats in Europe: capabilities, potentials and challenges of national forest inventories data Type de document : Article/Communication Auteurs : Iciar A. Alberdi, Auteur ; Leonia Nunes, Auteur ; Marko Kovac, Auteur ; Ingrid Bonhême Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Article en page(s) : n° 34 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] habitat (nature)
[Termes IGN] habitat d'intérêt communautaire
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] inventaire forestier national (données France)
[Termes IGN] politique de conservation (biodiversité)
[Termes IGN] site Natura 2000
[Termes IGN] Union Européenne
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Context : There are differences among Member States as regards applying conservation status assessment and priorities according to the Directive on the conservation of natural habitats (Habitats Directive).
Aims : This paper aims to analyse the consistency as regards forest habitat types reporting and the use and suitability of National Forest Inventories (NFIs) to assess their conservation status, as well as to provide recommendations for harmonised assessments through NFIs.
Methods : A survey was carried out concerning the use of NFI data to report within the commitments of the Habitat Directive. The survey covered 13 European countries, accounting for 62% of forest habitat area. Additionally, case studies were carried out in four countries.
Results : The identification of forest habitat types and the set of quantitative and/or qualitative indicators differ between countries. The use of NFI data is being considered in seven countries and it is expected to increase for the 2013–2018 reporting period. The main challenges reported of use of NFI data are related to the habitat identification and their mapping, and the monitoring frequency, design and costs (i.e. rare or small area habitats).
Conclusion : It is necessary to improve the comparability of the conservation status assessments between countries.Numéro de notice : A2019-642 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0820-4 Date de publication en ligne : 03/04/2019 En ligne : https://doi.org/10.1007/s13595-019-0820-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95998
in Annals of Forest Science > vol 76 n° 2 (June 2019) . - n° 34[article]DIABOLO policy brief. Responding to European, national and regional challenges with harmonised forest information / Tuula Packalen (2019)
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