Centre dedocumentation
scientifique

Automated fusion of forest airborne and terrestrial point clouds through canopy density analysis / Wenxia Dai in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 94 - 107 Titre : Automated fusion of forest airborne and terrestrial point clouds through canopy density analysis Type de document : Article/Communication Auteurs : Wenxia Dai, Auteur ; Bisheng Yang, Auteur ; Xinlian Liang, Auteur ; Zhen Dong, Auteur ; Ronggang Huang, Auteur ; Yunsheng Wang, Auteur ; Wuyan Li, Auteur Année de publication : 2019 Article en page(s) : pp 94 - 107 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] algorithme ICP [Termes descripteurs IGN] canopée [Termes descripteurs IGN] données TLS (télémétrie) [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] fusion de données multisource [Termes descripteurs IGN] image ADAR [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] surveillance forestière Résumé : (Auteur) Airborne laser scanning (ALS) and terrestrial laser scanning (TLS) systems are effective ways to capture the 3D information of forests from complementary perspectives. Registration of the two sources of point clouds is necessary for various forestry applications. Since the forest point clouds show irregular and natural point distributions, standard registration methods working on geometric keypoints (e.g., points, lines, and planes) are likely to fail. Hence, we propose a novel method to register the ALS and TLS forest point clouds through density analysis of the crowns. The proposed method extracts mode-based keypoints by the mean shift method and aligns them by maximum likelihood estimation. Firstly, the differences in the point densities of the ALS and TLS crowns are minimized to produce analogous modes, which represent the local maxima of the underlying probability density function (PDF). The mode-based keypoints are then aligned through the coherent point drift (CPD) algorithm, which is independent of the descriptor similarities and considers the alignment as a maximum likelihood estimation problem. The sets of keypoints derived from the two data sources need not be equal. Finally, the recovered transformation is applied to the original point clouds and refined through the standard iterative closest point (ICP) algorithm. In contrast to some of the existing methods, the proposed method avoids the geometric description of the forest point clouds. Furthermore, additional information such as tree diameter or height is not required to evaluate the similarities. The experiments in this study were conducted in a Scandinavian boreal forest, located in Evo, Finland. The proposed method was tested on four datasets (ALS data: a circle with a diameter of 60 m, multi-scan TLS data: 32 × 32 m) with heterogeneous tree species and structures. The results showed that the proposed probabilistic-based method obtains a good performance with a 3D distance residual of 0.069 m, and improved the accuracy of the registration when compared with the existing methods. Numéro de notice : A2019-318 Thématique : FORET/IMAGERIE Nature : Article DOI : doi.org/10.1016/j.isprsjprs.2019.08.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.008 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93356 [article]

Using LiDAR-modified topographic wetness index, terrain attributes with leaf area index to improve a single-tree growth model in south-eastern Finland / Cheikh Mohamedou in Forestry, an international journal of forest research, vol 92 n° 3 (July 2019)  

Public [article]  inForestry, an international journal of forest research > vol 92 n° 3 (July 2019) . - pp 253 - 263 Titre : Using LiDAR-modified topographic wetness index, terrain attributes with leaf area index to improve a single-tree growth model in south-eastern Finland Type de document : Article/Communication Auteurs : Cheikh Mohamedou, Auteur ; Lauri Korhonen, Auteur ; Kalle Eerikäinen, Auteur ; Timo Tokola, Auteur Année de publication : 2019 Article en page(s) : pp 253 - 263 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] diamètre des arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] indice d'humidité [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] Perceptron multicouche Résumé : (Auteur) Tree growth information is crucial in forest management and planning. Terrain-derived attributes such as the topographic wetness index (TWI), in addition to leaf area index (LAI) are closely related to tree growth, but are not commonly used in empirical growth models. In this study, we examined if modified TWI and LAI estimated from airborne light detection and ranging (LiDAR) data could be used to improve the predictions of a national single-tree diameter growth model. Altogether 1118 sample trees were selected within 197 subjectively placed plots in randomly selected forest stands in south-eastern Finland. Linear mixed effect (LME) and multilayer perceptron models were used to model the bias of 5-year growth predictions of the model and thus ultimately improve its predictions. The root mean square error (RMSE) of the national model was 0.604 cm. LME modelling reduced this value to 0.404 cm and MLP to 0.568 cm. The predictors included in the best-performing LME model were modified TWI, LAI estimated from LiDAR intensities, and elevation. Without an LAI estimate, the best RMSE was 0.436 cm. When applied as such, original and modified TWIs produced similar accuracy. We conclude that both TWI and LAI obtained from LiDAR data improve the diameter growth predictions of the national model. Numéro de notice : A2019-293 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpz010 date de publication en ligne : 28/02/2019 En ligne : https://doi.org/10.1093/forestry/cpz010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93184 [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 descripteurs IGN] appariement d'histogramme [Termes descripteurs IGN] chaîne de traitement [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] inventaire forestier local [Termes descripteurs IGN] Picea abies [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] placette d'échantillonnage [Termes descripteurs 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 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]

Réservation

Réserver ce document

Exemplaires (3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019061	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2019063	DEP-RECP	Revue	MATIS	Dépôt en unité	Exclu du prêt
081-2019062	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Detecting and characterizing downed dead wood using terrestrial laser scanning / Tuomas Yrttimaa in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 151 (May 2019) . - pp 76 - 90 Titre : Detecting and characterizing downed dead wood using terrestrial laser scanning Type de document : Article/Communication Auteurs : Tuomas Yrttimaa, Auteur ; Ninni Saarinen, Auteur ; Ville Luoma, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 76 - 90 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] bois mort [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] placette d'échantillonnage [Termes descripteurs IGN] qualité des données [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] rastérisation [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] tronc [Termes descripteurs IGN] volume en bois Résumé : (Auteur) Dead wood is a key forest structural component for maintaining biodiversity and storing carbon. Despite its important role in a forest ecosystem, quantifying dead wood alongside standing trees has often neglected when investigating the feasibility of terrestrial laser scanning (TLS) in forest inventories. The objective of this study was therefore to develop an automatic method for detecting and characterizing downed dead wood with a diameter exceeding 5 cm using multi-scan TLS data. The developed four-stage algorithm included (1) RANSAC-cylinder filtering, (2) point cloud rasterization, (3) raster image segmentation, and (4) dead wood trunk positioning. For each detected trunk, geometry-related quality attributes such as dimensions and volume were automatically determined from the point cloud. For method development and validation, reference data were collected from 20 sample plots representing diverse southern boreal forest conditions. Using the developed method, the downed dead wood trunks were detected with an overall completeness of 33% and correctness of 76%. Up to 92% of the downed dead wood volume were detected at plot level with mean value of 68%. We were able to improve the detection accuracy of individual trunks with visual interpretation of the point cloud, in which case the overall completeness was increased to 72% with mean proportion of detected dead wood volume of 83%. Downed dead wood volume was automatically estimated with an RMSE of 15.0 m3/ha (59.3%), which was reduced to 6.4 m3/ha (25.3%) as visual interpretation was utilized to aid the trunk detection. The reliability of TLS-based dead wood mapping was found to increase as the dimensions of dead wood trunks increased. Dense vegetation caused occlusion and reduced the trunk detection accuracy. Therefore, when collecting the data, attention must be paid to the point cloud quality. Nevertheless, the results of this study strengthen the feasibility of TLS-based approaches in mapping biodiversity indicators by demonstrating an improved performance in quantifying ecologically most valuable downed dead wood in diverse forest conditions. Numéro de notice : A2019-205 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.03.007 date de publication en ligne : 16/03/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.03.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92668 [article]

Réservation

Réserver ce document

Exemplaires (3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019051	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2019053	DEP-RECP	Revue	MATIS	Dépôt en unité	Exclu du prêt
081-2019052	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Economic losses caused by tree species proportions and site type errors in forest management planning / Arto Haara in Silva fennica, vol 53 n° 2 (2019)  

Public [article]  inSilva fennica > vol 53 n° 2 (2019) 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 descripteurs IGN] coupe (sylviculture) [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] éclaircie (sylviculture) [Termes descripteurs IGN] erreur [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] identification de plantes [Termes descripteurs IGN] image 3D [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] image spatiale [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] inventaire forestier étranger (données) [Vedettes matières IGN] Economie forestière Résumé : (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 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 [article]

Efficiency of post-stratification for a large-scale forest inventory : case Finnish NFI / Helena Haakana in Annals of Forest Science [en ligne], vol 76 n° 1 (March 2019)  

Permalink

Predicting tree diameter using allometry described by non-parametric locally-estimated copulas from tree dimensions derived from airborne laser scanning / Qing Xu in Forest ecology and management, vol 434 (28 February 2019)  

Permalink

A modeling-based approach for soil frost detection in the northern boreal forest region with C-Band SAR / Juval Cohen in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)  

Permalink

TanDEM-X digital surface models in boreal forest above-ground biomass change detection / Kirsi Karila in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

Permalink

Automatic determination of stream networks from DEMs by using road network data to locate culverts / Ville Mäkinen in International journal of geographical information science IJGIS, Vol 33 n° 1-2 (January - February 2019)  

Permalink

Is field-measured tree height as reliable as believed – A comparison study of tree height estimates from field measurement, airborne laser scanning and terrestrial laser scanning in a boreal forest / Yunsheng Wang in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)  

Permalink

Validating and comparing GNSS antenna calibrations / Ulla Kallio in Journal of geodesy, vol 93 n° 1 (January 2019)  

Permalink

Models for diameter and height growth of Scots pine, Norway spruce and pubescent birch in drained peatland sites in Finland / Jaakko Repola in Silva fennica, vol 52 n° 5 (November 2018)  

Permalink

Estimating storm damage with the help of low-altitude photographs and different sampling designs and estimators / Pekka Hyvönen in Silva fennica, vol 52 n° 3 ([01/08/2018])  

Permalink

Effect of first thinning type and age on growth, stem quality and financial performance of a Scots pine stand in Finland / Pentti Niemistö in Silva fennica, vol 52 n° 2 ([01/05/2018])  

Permalink