Détail de l'auteur
Auteur Annika S. Kangas |
Documents disponibles écrits par cet auteur (9)
Ajouter le résultat dans votre panier Affiner la recherche Interroger des sources externesEnsure forest-data integrity for climate change studies / Risto Päivinen in Nature climat change, vol 13 n° inconnu ([01/05/2023])
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 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 forestierRésumé : (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
in Nature climat change > vol 13 n° inconnu [01/05/2023] . - pp 495 - 496[article]
Titre : Potential of Bayesian formalism for the fusion and assimilation of sequential forestry data in time and space Type de document : Article/Communication Auteurs : Cheikh Mohamedou, Auteur ; Annika S. Kangas, Auteur ; Alireza Hamedianfar, Auteur ; Jari Vauhkonen, Auteur Année de publication : 2022 Article en page(s) : pp 439 - 449 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données spatiotemporelles
[Termes IGN] dynamique de la végétation
[Termes IGN] estimation bayesienne
[Termes IGN] fusion de données
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] série temporelle
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Forest resource assessments based on multi-source and multi-temporal data have become more common. Therefore, enhancing the prediction capabilities of forestry dynamics by efficiently pooling and analyzing time-series and spatial sequential data is now more pivotal. Bayesian filtering and smoothing provide a well-defined formalism for the fusion or assimilation of various data. We ascertained how often the generic, standardized Bayesian framework is used in the scientific literature and whether such an approach is beneficial for forestry applications. A review of the literature showed that the use of Bayesian methods appears to be less common in forestry than in other disciplines, particularly remote sensing. Specifically, time-series analyses were found to favor ad hoc methods. Our review did not reveal strong numeric evidence for better performance by the various Bayesian approaches, but this result may be partly due to the challenge in comparing a variety of methods for different prediction tasks. We identified methodological challenges related to assimilating predictions of forest development; in particular, combining modelled growth with disturbances due to both forest operations and natural phenomena. Nevertheless, the Bayesian frameworks provide possibilities to efficiently combine and update prior and posterior predictive distributions and derive related uncertainty measures that appear under-utilized in forestry. Numéro de notice : A2022-315 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.1139/cjfr-2021-0145 Date de publication en ligne : 17/01/2022 En ligne : https://doi.org/10.1139/cjfr-2021-0145 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100415
in Canadian Journal of Forest Research > Vol 52 n° 4 (April 2022) . - pp 439 - 449[article]
Titre : Assessing local trends in indicators of ecosystem services with a time series of forest resource maps Type de document : Article/Communication Auteurs : Matti Katila, Auteur ; Tuomas Rajala, Auteur ; Annika S. Kangas, Auteur Année de publication : 2020 Article en page(s) : n° 10347 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte forestière
[Termes IGN] classification barycentrique
[Termes IGN] données de terrain
[Termes IGN] Finlande
[Termes IGN] image satellite
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] ressources forestières
[Termes IGN] série temporelle
[Termes IGN] service écosystémique
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Since the 1990’s, forest resource maps and small area estimates have been produced by combining national forest inventory (NFI) field plot data, optical satellite images and numerical map data using a non-parametric k-nearest neighbour method. In Finland, thematic maps of forest variables have been produced by the means of multi-source NFI (MS-NFI) for eight to ten times depending on the geographical area, but the resulting time series have not been systematically utilized. The objective of this study was to explore the possibilities of the time series for monitoring the key ecosystem condition indicators for forests. To this end, a contextual Mann-Kendall (CMK) test was applied to detect trends in time-series of two decades of thematic maps. The usefulness of the observed trends may depend both on the scale of the phenomena themselves and the uncertainties involved in the maps. Thus, several spatial scales were tested: the MS-NFI maps at 16 × 16 m2 pixel size and units of 240 × 240 m2, 1200 × 1200 m2 and 12 000 × 12 000 m2 aggregated from the MS-NFI map data. The CMK test detected areas of significant increasing trends of mean volume on both study sites and at various unit sizes except for the original thematic map pixel size. For other variables such as the mean volume of tree species groups, the proportion of broadleaved tree species and the stand age, significant trends were mostly found only for the largest unit size, 12 000 × 12 000 m2. The multiple testing corrections decreased the amount of significant p-values from the CMK test strongly. The study showed that significant trends can be detected enabling indicators of ecosystem services to be monitored from a time-series of satellite image-based thematic forest maps. Numéro de notice : A2020-791 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14214/sf.10347 Date de publication en ligne : 14/09/2020 En ligne : https://doi.org/10.14214/sf.10347 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96562
in Silva fennica > vol 54 n° 4 (September 2020) . - n° 10347[article]
Titre : Economic losses caused by tree species proportions and site type errors in forest management planning Type de document : Article/Communication Auteurs : Arto Haara, Auteur ; Annika S. Kangas, Auteur ; Sakari Tuominen, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] coupe (sylviculture)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] erreur
[Termes IGN] Finlande
[Termes IGN] identification de plantes
[Termes IGN] image 3D
[Termes IGN] image aérienne
[Termes IGN] image spatiale
[Termes IGN] incertitude des données
[Termes IGN] inventaire forestier étranger (données)
[Vedettes matières IGN] Economie forestièreRésumé : (auteur) The aim of this study was to estimate economic losses, which are caused by forest inventory errors of tree species proportions and site types. Our study data consisted of ground truth data and four sets of erroneous tree species proportions. They reflect the accuracy of tree species proportions in four remote sensing data sets, namely 1) airborne laser scanning (ALS) with 2D aerial image, 2) 2D aerial image, 3) 3D and 2D aerial image data together and 4) satellite data. Furthermore, our study data consisted of one simulated site type data set. We used the erroneous tree species proportions to optimise the timing of forest harvests and compared that to the true optimum obtained with ground truth data. According to the results, the mean losses of Net Present Value (NPV) because of erroneous tree species proportions at an interest rate of 3% varied from 124.4 € ha–1 to 167.7 € ha–1. The smallest losses were observed using tree species proportions predicted using ALS data and largest using satellite data. In those stands, respectively, in which tree species proportion errors actually caused economic losses, they were 468 € ha–1 on average with tree species proportions based on ALS data. In turn, site type errors caused only small losses. Based on this study, accurate tree species identification seems to be very important with respect to operational forest inventory. Numéro de notice : A2019-378 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.10089 Date de publication en ligne : 17/06/2019 En ligne : https://doi.org/10.14214/sf.10089 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93444
in Silva fennica > vol 53 n° 2 (2019)[article]
Titre : Efficiency of post-stratification for a large-scale forest inventory : case Finnish NFI Type de document : Article/Communication Auteurs : Helena Haakana, Auteur ; Juha Heikkinen, Auteur ; Matti Katila, Auteur ; Annika S. Kangas, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de la végétation
[Termes IGN] densité de la végétation
[Termes IGN] Finlande
[Termes IGN] image Landsat
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] ressources forestières
[Termes IGN] stratification
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Key message : Post-stratification based on remotely sensed data is an efficient method in estimating regional-level results in the operational National Forest Inventory. It also enables calculating the results accurately for smaller areas than with the default method of using the field plots only.
Context : The utilization of auxiliary information in survey sampling through model-assisted estimation or post-stratification has gained popularity in forest inventory recently. However, post-stratification at a large scale involves practical concerns such as the availability of auxiliary data independent of the sample at hand, and a large number of variables for which the results are needed.
Aims : We assessed the efficiency of two different types of post-stratification, either post-stratifying for each variable of interest separately or using one post-stratification for all variables, compared to the estimation based on the field sample plots only. In addition, we examined the precision of area and volume estimates, and the efficiency of post-stratification at different spatial scales.
Methods : For post-stratification, we used the volume maps based on Landsat satellite imagery, digital map data, and the sample plot data of the previous inventory. The efficiencies of post-stratifications based on the mean volume and the mean volumes by tree species were compared.
Results : In estimating the total volume, the relative efficiency of post-stratification compared to field plot based estimation was 1.54–3.54 over the provinces in South Finland. In estimating the volumes by tree species groups, the relative efficiency was 0.93–2.39. The gain with a separate stratification compared to the stratification based on total mean volume for all variables was at largest 0.69. In the small test areas, the relative standard errors of the total volume estimates decreased on average by 33% by using post-stratification instead of sample plots only. The mean relative efficiency was 2.36.
Conclusion : The utilization of an old forest resources map and post-stratification based on the mean volume is an operational approach for the National Forest Inventory. Post-stratification also enables calculating the results accurately for markedly smaller areas than with the field plots only. Post-stratification reduced the probability of very high sampling variances, making the results more robust.Numéro de notice : A2019-042 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-018-0795-6 Date de publication en ligne : 30/01/2019 En ligne : https://doi.org/10.1007/s13595-018-0795-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92040
in Annals of Forest Science > vol 76 n° 1 (March 2019)[article]
