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Horvitz-Thompson–like estimation with distance-based detection probabilities for circular plot sampling of forests / Kasper Kansanen in Biometrics, vol 77 n° 2 (June 2021)  

Public [article]  inBiometrics > vol 77 n° 2 (June 2021) . - pp 715 - 728 Titre : Horvitz-Thompson–like estimation with distance-based detection probabilities for circular plot sampling of forests Type de document : Article/Communication Auteurs : Kasper Kansanen, Auteur ; Petteri Packalen, Auteur ; Matti Maltamo, Auteur ; Lauri Mehtätalo, Auteur Année de publication : 2021 Article en page(s) : pp 715 - 728 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] distribution de Poisson [Termes IGN] erreur systématique [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] placette d'échantillonnage [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) In circular plot sampling, trees within a given distance from the sample plot location constitute a sample, which is used to infer characteristics of interest for the forest area. If the sample is collected using a technical device located at the sampling point, eg, a terrestrial laser scanner, all trees of the sample plot cannot be observed because they hide behind each other. We propose a Horvitz-Thompson–like estimator with distance-based detection probabilities derived from stochastic geometry for estimation of population totals such as stem density and basal area in such situation. We show that our estimator is unbiased for Poisson forests and give estimates of variance and approximate confidence intervals for the estimator, unlike any previous methods. We compare the estimator to two previously published benchmark methods. The comparison is done through a simulation study where several plots are simulated either from field measured data or different marked point processes. The simulations show that the estimator produces lower or comparable error values than the other methods. In the sample plots based on the field measured data, the bias is relatively small—relative mean of errors for stem density, for example, varying from 0.3% to 2.2%, depending on the detection condition. The empirical coverage probabilities of the approximate confidence intervals are either similar to the nominal levels or conservative in these sample plots. Numéro de notice : A2021-987 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1111/biom.13312 Date de publication en ligne : 07/06/2020 En ligne : https://doi.org/10.1111/biom.13312 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103237 [article]

Estimating forest stand density and structure using Bayesian individual tree detection, stochastic geometry, and distribution matching / Kasper Kansanen in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 152 (June 2019) . - pp 66 - 78 Titre : Estimating forest stand density and structure using Bayesian individual tree detection, stochastic geometry, and distribution matching Type de document : Article/Communication Auteurs : Kasper Kansanen, Auteur ; Jari Vauhkonen, Auteur ; Timo Lähivaara, Auteur ; Aku Seppänen, Auteur ; Matti Maltamo, Auteur ; Lauri Mehtätalo, Auteur Année de publication : 2019 Article en page(s) : pp 66 - 78 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] appariement d'histogramme [Termes IGN] chaîne de traitement [Termes IGN] détection d'arbres [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier local [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] placette d'échantillonnage [Termes IGN] surface terrière [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Errors in individual tree detection and delineation affect diameter distribution predictions based on crown attributes extracted from the detected trees. We develop a methodology for circumventing these problems. The method is based on matching cumulative distribution functions of field measured tree diameter distributions and crown radii distributions extracted from airborne laser scanning data through individual tree detection presented by Vauhkonen and Mehtätalo (2015). In this study, empirical distribution functions and a monotonic, nonlinear model curve are introduced. Tree crown radius distribution produced by individual tree detection is corrected by a method taking into account that all trees cannot be detected. The evaluation is based on the ability of the developed model sequence to predict quadratic mean diameter and total basal area. The studied data consists of 36 field plots in a typical boreal managed forest area in eastern Finland. The suggested enhancements to the model sequence produce improved results in most of the test cases. Most notably, in leave-one-out cross-validation experiments the modified models improve RMSE of basal area 13% in the full data and RMSE of quadratic mean diameter and basal area 69% and 11%, respectively, in pure pine plots. Better modeling of the crown radius distribution and improved matching between crown radii and stem diameters add the operational premises of the full distribution matching. Numéro de notice : A2019-455 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.04.007 Date de publication en ligne : 15/04/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92868 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019061	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2019063	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2019062	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Airborne laser scanning for tree diameter distribution modelling: a comparison of different modelling alternatives in a tropical single-species plantation / Matti Maltamo in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)  

Public [article]  inForestry, an international journal of forest research > vol 91 n° 1 (January 2018) . - pp 121 - 131 Titre : Airborne laser scanning for tree diameter distribution modelling: a comparison of different modelling alternatives in a tropical single-species plantation Type de document : Article/Communication Auteurs : Matti Maltamo, Auteur ; Lauri Mehtätalo, Auteur ; R. Abdelfattah, Auteur ; Jari Vauhkonen, Auteur ; Petteri Packalen, Auteur Année de publication : 2018 Article en page(s) : pp 121 - 131 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Brésil [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] diamètre des arbres [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Eucalyptus grandis [Termes IGN] modèle numérique [Termes IGN] plantation forestière [Termes IGN] positionnement par GNSS Mots-clés libres : Weibull distribution Résumé : (Auteur) This study examines the potential of airborne laser scanning (ALS) to predict diameter distributions in an even-aged plantation of Eucalyptus urograndis in Brazil. The single-species plantation conditions allow different modelling alternatives to be compared without the presence of minor tree species or an understory layer affecting the results. Three modelling alternatives based on the two-parametric Weibull function form; parameter prediction, parameter recovery and distribution matching were tested with a k-nearest neighbour prediction (k-nn) method. We also evaluated a parameter prediction alternative, in which the Weibull distribution was predicted using field attributes. The results showed that ALS information can predict diameter distributions with an error margin of slightly more than 10 per cent of the RMSE of the mean of the third power of diameter, and with error index values between 50 and 60. The degree of accuracy was only slightly improved when the Weibull distribution was predicted using field attributes. According to the accuracy metrics, the differences between modelling alternatives were minor but parameter recovery and k-nn seem to be the most favourable ALS-based prediction methods. To conclude, the results showed a strong relationship between ALS information and diameter distributions in a tropical single-species plantation and we discuss how these results could be applied in other types of forests. Numéro de notice : A2018-633 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx041 En ligne : https://doi.org/10.1093/forestry/cpx041 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93233 [article]