Descripteur
Documents disponibles dans cette catégorie (1246)
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
Etendre la recherche sur niveau(x) vers le bas
A spatial dataset of forest mensuration collected in black pine plantations in central Italy / Paolo Cantiani in Annals of Forest Science, vol 74 n° 3 (September 2017)
![]()
[article]
Titre : A spatial dataset of forest mensuration collected in black pine plantations in central Italy Type de document : Article/Communication Auteurs : Paolo Cantiani, Auteur ; Maurizio Marchi, Auteur Année de publication : 2017 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre (flore)
[Termes IGN] base de données localisées
[Termes IGN] bois mort
[Termes IGN] données de terrain
[Termes IGN] données dendrométriques
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] géoréférencement
[Termes IGN] houppier
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] peuplement forestier
[Termes IGN] Pinus nigra
[Termes IGN] placette d'échantillonnage
[Termes IGN] sol
[Termes IGN] Toscane (Italie)
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Key message : The dataset provides an exhaustive tree inventory with forest mensuration and spatial location carried out in 54 plots sampled in 45- to 55-year-old black pine plantations, located in two areas of Tuscany (central Italy). Forest mensuration includes horizontal and vertical structure measurements and a total of 4171 trees were geo-referenced. The most abundant species was the black pine, Pinus nigra spp. laricio, for which a total of 3631 trees were observed. The dataset was collected as part of the SelPiBio LIFE project (LIFE13 BIO/IT/000282). Dataset access athttp://doi.org/10.5281/zenodo.438681. Associated metadata available athttps://metadata-afs.nancy.inra.fr/geonetwork/apps/georchestra/?uuid=73591027-0f1e-40a3-95d0-b614517c1290&hl=eng.
Context : The main aim of the SelPiBio LIFE project (www.selpibio.eu) is to demonstrate the effects of two thinning regimes, selective and from below, on soil biodiversity in young black pine stands. The spatial structure of forests and the relationships between trees are a good proxy of overall biodiversity level. Spatial datasets with geo referenced trees and related mensurational data represent the highest level of information for forest inventories and research activities.
Aims : This dataset has been developed during the A2 Action (Assessment of structural and mensurational parameters of the forest stands and the dead wood) of the project, to record the main mensurational parameters of the studied black pine stands. A tree-level database was compiled to describe the vertical and horizontal structure of 54 monitoring plots before the application of the silvicultural treatment.
Methods : In addition to classical in-field measurements (e.g. diameters at breast height, total height of the tree, crown depth etc.), all trees were georeferenced by means of polar coordinates collected from the centre of each monitoring plot, including crown projection on the ground, described with eight points. Then, a polynomial spline function was fitted across the recorded data to obtain a convex polygon and to calculate crown area and crown perimeter of each measured tree in GIS environment.
Results : A polygonal ESRI shapefile in ETRS89/UTM32N reference system (EPSG: 25832) with 4171 records representing the crown projections on the ground of each measured tree with all the mensurational parameters included into the attribute table. The database is freely available under the Creative Commons Attribution-NonCommercial 4. 182 0 License.
Conclusion : With this database, a wide range of forestry-related indices could be easily calculated, including geostatistical analysis and autocorrelation functions, to compare Italian artificial black pine stands with other studied forests.Numéro de notice : A2017-355 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1007/s13595-017-0648-8 Date de publication en ligne : 26/06/2017 En ligne : https://doi.org/10.1007/s13595-017-0648-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85722
in Annals of Forest Science > vol 74 n° 3 (September 2017)[article]Automatic mapping of forest stands based on three-dimensional point clouds derived from terrestrial laser-scanning / Tim Ritter in Forests, vol 8 n° 8 (August 2017)
![]()
[article]
Titre : Automatic mapping of forest stands based on three-dimensional point clouds derived from terrestrial laser-scanning Type de document : Article/Communication Auteurs : Tim Ritter, Auteur ; Marcel Schwarz, Auteur ; Andreas Tockner, Auteur ; Friedrich Leisch, Auteur ; Arne Nothdurft, Auteur Année de publication : 2017 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba
[Termes IGN] analyse de groupement
[Termes IGN] Autriche
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Fagus sylvatica
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Larix decidua
[Termes IGN] peuplement forestier
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] Préalpes (Europe)
[Termes IGN] semis de points
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Mapping of exact tree positions can be regarded as a crucial task of field work associated with forest monitoring, especially on intensive research plots. We propose a two-stage density clustering approach for the automatic mapping of tree positions, and an algorithm for automatic tree diameter estimates based on terrestrial laser-scanning (TLS) point cloud data sampled under limited sighting conditions. We show that our novel approach is able to detect tree positions in a mixed and vertically structured stand with an overall accuracy of 91.6%, and with omission- and commission error of only 5.7% and 2.7% respectively. Moreover, we were able to reproduce the stand’s diameter in breast height (DBH) distribution, and to estimate single trees DBH with a mean average deviation of ±2.90 cm compared with tape measurements as reference. Numéro de notice : A2017-876 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f8080265 Date de publication en ligne : 25/07/2017 En ligne : https://doi.org/10.3390/f8080265 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91195
in Forests > vol 8 n° 8 (August 2017)[article]Hybrid three-phase estimators for large-area forest inventory using ground plots, airborne lidar, and space lidar / Sören Holm in Remote sensing of environment, vol 197 (August 2017)
![]()
[article]
Titre : Hybrid three-phase estimators for large-area forest inventory using ground plots, airborne lidar, and space lidar Type de document : Article/Communication Auteurs : Sören Holm, Auteur ; Ross Nelson, Auteur ; Göran Stahl, Auteur Année de publication : 2017 Article en page(s) : pp 85 - 97 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse
[Termes IGN] données ICEsat
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation statistique
[Termes IGN] Etats-Unis
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] placette d'échantillonnage
[Termes IGN] variance
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Previous studies have utilized ground plots, airborne lidar scanning or profiling data, and space lidar profiling data to estimate biomass across large regions, but these studies have failed to take into account the variance components associated with multiple models because the proper variance equations were not available. Previous large-domain studies estimated the variances of their biomass density estimates as the sum of the GLAS sampling variability plus the model variability associated with the models that predict airborne lidar estimates of biomass density (Y) as a function of satellite lidar measurements (X). This approach ignores the additional variability associated with the predictive models used to estimate ground biomass density as a function of airborne lidar measurements. This paper addresses that shortcoming. Analytic variance expressions are provided that include sampling variability and model variability in situations where multiple models are employed to generate estimates of biomass. As an example, the forest biomass of the continental US is estimated, by forest stratum within state, using a space lidar system (ICESat/GLAS). An airborne laser system (ALS) is used as an intermediary to tie the GLAS measurements of forest height to a small subset of US Forest Service (USFS) ground plots by flying the ALS over the ground plots and, independently, over individual GLAS footprints. Two sets of models are employed to relate satellite measurements to the ground plots. The first set of equations relates USFS ground plot estimates of total aboveground dry biomass density (Y1) to spatially coincident ALS forest canopy measurements (X1). The second set of models predicts those ALS canopy height measurements (X1) used in the first set of models to GLAS waveform measurements (X2). The following important conclusions are noted. (1) The variability associated with estimation of the plot-ALS model coefficients is significant and should be included in the overall estimate of biomass density variance. In the continental US, the total variance of mean forest biomass density (98.06 t/ha) increases by a factor of 3.6 ×, i.e., from 1.91 to 6.94 t2/ha2, when plot-ALS model variance is included in the calculation of total variance. (2) State-level results are more variable, but on average, the percent model variance at the state level, i.e., (model variance / total variance) ∗ 100, increases from 16% to 59% when plot-ALS model variance is included. (3) The overall model variance is driven in large part by the number of plots overflown by the ALS and the number of GLAS pulses overflown by the ALS. Given a choice of improving precision by either increasing the number of plot-ALS observations or increasing ALS-GLAS observations, there is no obvious benefit to selecting one over the other. However, typically the number of ground plots overflown is the limiting factor. (4) If heteroskedasticity is evident in either the ground-air or air-satellite models, it can modeled using weighted regression techniques and incorporated into these model variance formulas in straightforward fashion. The results are unambiguous; in a hybrid three-phase sampling framework, both the ground-air and air-satellite model variance components are significant and should be taken into account. Numéro de notice : A2017-655 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2017.04.004 En ligne : https://doi.org/10.1016/j.rse.2017.04.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87050
in Remote sensing of environment > vol 197 (August 2017) . - pp 85 - 97[article]Image matching as a data source for forest inventory – Comparison of semi-global matching and next-generation automatic terrain extraction algorithms in a typical managed boreal forest environment / Mari Kukkonen in International journal of applied Earth observation and geoinformation, vol 60 (August 2017)
![]()
[article]
Titre : Image matching as a data source for forest inventory – Comparison of semi-global matching and next-generation automatic terrain extraction algorithms in a typical managed boreal forest environment Type de document : Article/Communication Auteurs : Mari Kukkonen, Auteur ; Matti Maltamo, Auteur ; Petteri Packalen, Auteur Année de publication : 2017 Article en page(s) : pp 11 - 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] appariement d'images
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle numérique de terrain
[Termes IGN] semis de points
[Termes IGN] sous-boisRésumé : (auteur) Image matching is emerging as a compelling alternative to airborne laser scanning (ALS) as a data source for forest inventory and management. There is currently an open discussion in the forest inventory community about whether, and to what extent, the new method can be applied to practical inventory campaigns. This paper aims to contribute to this discussion by comparing two different image matching algorithms (Semi-Global Matching [SGM] and Next-Generation Automatic Terrain Extraction [NGATE]) and ALS in a typical managed boreal forest environment in southern Finland. Spectral features from unrectified aerial images were included in the modeling and the potential of image matching in areas without a high resolution digital terrain model (DTM) was also explored. Plot level predictions for total volume, stem number, basal area, height of basal area median tree and diameter of basal area median tree were modeled using an area-based approach. Plot level dominant tree species were predicted using a random forest algorithm, also using an area-based approach. The statistical difference between the error rates from different datasets was evaluated using a bootstrap method. Results showed that ALS outperformed image matching with every forest attribute, even when a high resolution DTM was used for height normalization and spectral information from images was included. Dominant tree species classification with image matching achieved accuracy levels similar to ALS regardless of the resolution of the DTM when spectral metrics were used. Neither of the image matching algorithms consistently outperformed the other, but there were noticeably different error rates depending on the parameter configuration, spectral band, resolution of DTM, or response variable. This study showed that image matching provides reasonable point cloud data for forest inventory purposes, especially when a high resolution DTM is available and information from the understory is redundant. Numéro de notice : A2017-364 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2017.03.012 En ligne : https://doi.org/10.1016/j.jag.2017.03.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85791
in International journal of applied Earth observation and geoinformation > vol 60 (August 2017) . - pp 11 - 21[article]Improving Finnish multi-source national forest inventory by 3D aerial imaging / Sakari Tuominen in Silva fennica, vol 51 n° 4 (2017)
![]()
[article]
Titre : Improving Finnish multi-source national forest inventory by 3D aerial imaging Type de document : Article/Communication Auteurs : Sakari Tuominen, Auteur ; Timo P Pitkänen, Auteur ; Andras Balazs, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification barycentrique
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] distribution spatiale
[Termes IGN] Finlande
[Termes IGN] image aérienne
[Termes IGN] image satellite
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] photogrammétrie numérique
[Termes IGN] placette d'échantillonnage
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Optical 2D remote sensing techniques such as aerial photographing and satellite imaging have been used in forest inventory for a long time. During the last 15 years, airborne laser scanning (ALS) has been adopted in many countries for the estimation of forest attributes at stand and sub-stand levels. Compared to optical remote sensing data sources, ALS data are particularly well-suited for the estimation of forest attributes related to the physical dimensions of trees due to its 3D information. Similar to ALS, it is possible to derive a 3D forest canopy model based on aerial imagery using digital aerial photogrammetry. In this study, we compared the accuracy and spatial characteristics of 2D satellite and aerial imagery as well as 3D ALS and photogrammetric remote sensing data in the estimation of forest inventory variables using k-NN imputation and 2469 National Forest Inventory (NFI) sample plots in a study area covering approximately 5800 km2. Both 2D data were very close to each other in terms of accuracy, as were both the 3D materials. On the other hand, the difference between the 2D and 3D materials was very clear. The 3D data produce a map where the hotspots of volume, for instance, are much clearer than with 2D remote sensing imagery. The spatial correlation in the map produced with 2D data shows a lower short-range correlation, but the correlations approach the same level after 200 meters. The difference may be of importance, for instance, when analyzing the efficiency of different sampling designs and when estimating harvesting potential. Numéro de notice : A2017-646 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article En ligne : https://doi.org/10.14214/sf.7743 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87003
in Silva fennica > vol 51 n° 4 (2017)[article]Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data / Timo P Pitkänen in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
PermalinkUsing Landsat time series for characterizing forest disturbance dynamics in the coupled human and natural systems of Central Europe / Cornelius Senf in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
PermalinkVertical stratification of forest canopy for segmentation of understory trees within small-footprint airborne LiDAR point clouds / Hamid Hamraz in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
PermalinkPermalinkL’identification et la mobilisation des peuplements pauvres / Fabienne Benest in Forêt entreprise, n° 235 (juillet - août 2017)
PermalinkNorthern conifer forest species classification using multispectral data acquired from an unmanned aerial vehicle / Steven E. Franklin in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 7 (July 2017)
PermalinkPredicting stem total and assortment volumes in an industrial pinus taeda L. forest plantation using airborne laser scanning data and random forest / Carlos Alberto Silva in Forests, vol 8 n° 7 (July 2017)
PermalinkLa certification FSC s’adapte aux forêts françaises avec un nouveau référentiel / Anonyme in Forestopic, sans n° ([01/06/2017])
PermalinkChange detection in forests and savannas using statistical analysis based on geographical objects / Lucilia Rezende Leite in Boletim de Ciências Geodésicas, vol 23 n° 2 (abr - jun 2017)
PermalinkDevelopment and Comparison of Species Distribution Models for Forest Inventories / Óscar Rodríguez de Rivera in ISPRS International journal of geo-information, vol 6 n° 6 (June 2017)
Permalink