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A comparison of ALS and dense photogrammetric point clouds for individual tree detection in radiata pine plantations / Irfan A. Iqbal in Remote sensing, vol 13 n° 17 (September-1 2021)  

Public [article]  inRemote sensing > vol 13 n° 17 (September-1 2021) . - n° 3536 Titre : A comparison of ALS and dense photogrammetric point clouds for individual tree detection in radiata pine plantations Type de document : Article/Communication Auteurs : Irfan A. Iqbal, Auteur ; Jon Osborn, Auteur ; Christine Stone, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 3536 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] arbre isolé [Termes IGN] détection d'arbres [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] image aérienne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] photogrammétrie aérienne [Termes IGN] Pinus radiata [Termes IGN] semis de points [Termes IGN] Tasmanie Résumé : (auteur) Digital aerial photogrammetry (DAP) has emerged as a potentially cost-effective alternative to airborne laser scanning (ALS) for forest inventory methods that employ point cloud data. Forest inventory derived from DAP using area-based methods has been shown to achieve accuracy similar to that of ALS data. At the tree level, individual tree detection (ITD) algorithms have been developed to detect and/or delineate individual trees either from ALS point cloud data or from ALS- or DAP-based canopy height models. An examination of the application of ITDs to DAP-based point clouds has not yet been reported. In this research, we evaluate the suitability of DAP-based point clouds for individual tree detection in the Pinus radiata plantation. Two ITD algorithms designed to work with point cloud data are applied to dense point clouds generated from small- and medium-format photography and to an ALS point cloud. Performance of the two ITD algorithms, the influence of stand structure on tree detection rates, and the relationship between tree detection rates and canopy structural metrics are investigated. Overall, we show that there is a good agreement between ALS- and DAP-based ITD results (proportion of false negatives for ALS, SFP, and MFP was always lower than 29.6%, 25.3%, and 28.6%, respectively, whereas, the proportion of false positives for ALS, SFP, and MFP was always lower than 39.4%, 30.7%, and 33.7%, respectively). Differences between small- and medium-format DAP results were minor (for SFP and MFP, differences between recall, precision, and F-score were always less than 0.08, 0.03, and 0.05, respectively), suggesting that DAP point cloud data is robust for ITD. Our results show that among all the canopy structural metrics, the number of trees per hectare has the greatest influence on the tree detection rates. Numéro de notice : A2021-689 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs13173536 Date de publication en ligne : 06/09/2021 En ligne : https://doi.org/10.3390/rs13173536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98425 [article]

Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest / Laura Alonso-Martinez in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2021 (July 2021)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2021 (July 2021) . - pp 203 - 210 Titre : Forest cover mapping and Pinus species classification using very high-resolution satellite images and random forest Type de document : Article/Communication Auteurs : Laura Alonso-Martinez, Auteur ; J. Picos, Auteur ; Julia Armesto, Auteur Année de publication : 2021 Article en page(s) : pp 203 - 210 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de la végétation [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] couvert forestier [Termes IGN] Espagne [Termes IGN] Eucalyptus (genre) [Termes IGN] image multibande [Termes IGN] image Worldview [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Pinus pinaster [Termes IGN] Pinus radiata [Termes IGN] Pinus sylvestris [Termes IGN] ressources forestières [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Advances in remote sensing technologies are generating new perspectives concerning the role of and methods used for National Forestry Inventories (NFIs). The increase in computation capabilities over the last several decades and the development of new statistical techniques have allowed for the automation of forest resource map generation through image analysis techniques and machine learning algorithms. The availability of large-scale data and the high temporal resolution that satellite platforms provide mean that it is possible to obtain updated information about forest resources at the stand level, thus increasing the quality of the spatial information. However, photointerpretation of satellite and aerial images is still the most common way that remote sensing information is used for NFIs or forest management purposes. This study describes a methodology that automatically maps the main forest covers in Galicia (Eucalyptus spp., conifers and broadleaves) using Worldview-2 and the random forest classifier. Furthermore, the method also evaluates the separate mapping of the three most abundant Pinus tree species in Galicia (Pinus pinaster, Pinus radiata and Pinus sylvestris). According to the results, Worldview-2 multispectral images allow for the efficient differentiation between the main forest classes that are present in Galicia with a very high degree of accuracy (91%) and ample spatial detail. Pinus species can also be efficiently differentiated (83%). Numéro de notice : A2021-493 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-V-3-2021-203-2021 Date de publication en ligne : 17/06/2021 En ligne : http://dx.doi.org/10.5194/isprs-annals-V-3-2021-203-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97958 [article]

Testing the generality of below-ground biomass allometry across plant functional types / Keryn I. Paul in Forest ecology and management, vol 432 (15 January 2019)  

Public [article]  inForest ecology and management > vol 432 (15 January 2019) . - pp 102 - 114 Titre : Testing the generality of below-ground biomass allometry across plant functional types Type de document : Article/Communication Auteurs : Keryn I. Paul, Auteur Année de publication : 2019 Article en page(s) : pp 102 - 114 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes IGN] Acacia (genre) [Termes IGN] allométrie [Termes IGN] arbuste [Termes IGN] Australie [Termes IGN] biomasse souterraine [Termes IGN] bois sur pied [Termes IGN] diamètre des arbres [Termes IGN] écosystème forestier [Termes IGN] Eucalyptus (genre) [Termes IGN] forêt tropicale [Termes IGN] modèle fonctionnel [Termes IGN] Pinus radiata [Termes IGN] puits de carbone [Termes IGN] sous-bois Résumé : (auteur) Accurate quantification of below-ground biomass (BGB) of woody vegetation is critical to understanding ecosystem function and potential for climate change mitigation from sequestration of biomass carbon. We compiled 2054 measurements of planted and natural individual tree and shrub biomass from across different regions of Australia (arid shrublands to tropical rainforests) to develop allometric models for prediction of BGB. We found that the relationship between BGB and stem diameter was generic, with a simple power-law model having a BGB prediction efficiency of 72–93% for four broad plant functional types: (i) shrubs and Acacia trees, (ii) multi-stemmed mallee eucalypts, (iii) other trees of relatively high wood density, and; (iv) a species of relatively low wood density, Pinus radiata D. Don. There was little improvement in accuracy of model prediction by including variables (e.g. climatic characteristics, stand age or management) in addition to stem diameter alone. We further assessed the generality of the plant functional type models across 11 contrasting stands where data from whole-plot excavation of BGB were available. The efficiency of model prediction of stand-based BGB was 93%, with a mean absolute prediction error of only 6.5%, and with no improvements in validation results when species-specific models were applied. Given the high prediction performance of the generalised models, we suggest that additional costs associated with the development of new species-specific models for estimating BGB are only warranted when gains in accuracy of stand-based predictions are justifiable, such as for a high-biomass stand comprising only one or two dominant species. However, generic models based on plant functional type should not be applied where stands are dominated by species that are unusual in their morphology and unlikely to conform to the generalised plant functional group models. Numéro de notice : A2019-003 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.08.043 Date de publication en ligne : 15/09/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.08.043 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91596 [article]

Comparison of high-density LiDAR and satellite photogrammetry for forest inventory / Grant D. Pearse in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 257 - 267 Titre : Comparison of high-density LiDAR and satellite photogrammetry for forest inventory Type de document : Article/Communication Auteurs : Grant D. Pearse, Auteur ; Jonathan P. Dash, Auteur ; Henrik J. Persson, Auteur ; Michael S. Watt, Auteur Année de publication : 2018 Article en page(s) : pp 257 - 267 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] densité de la végétation [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] forêt [Termes IGN] hauteur des arbres [Termes IGN] image multibande [Termes IGN] image Pléiades-HR [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] Nouvelle-Zélande [Termes IGN] photogrammétrie numérique [Termes IGN] Pinus radiata [Termes IGN] semis de points [Termes IGN] surface terrière [Termes IGN] sylviculture [Termes IGN] volume en bois [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Point cloud data derived from stereo satellite imagery has the potential to provide large-scale forest inventory assessment but these methods are known to include higher error than airborne laser scanning (ALS). This study compares the accuracy of forest inventory attributes estimated from high-density ALS (21.1 pulses m−2) point cloud data (PCD) and PCD derived from photogrammetric methods applied to stereo satellite imagery obtained over a Pinus radiata D. Don plantation forest in New Zealand. The statistical and textural properties of the canopy height models (CHMs) derived from each point cloud were included alongside standard PCD metrics as a means of improving the accuracy of predictions for key forest inventory attributes. For mean top height (a measure of dominant height in a stand), ALS data produced better estimates (R2 = 0.88; RMSE = 1.7 m) than those obtained from satellite data (R2 = 0.81; RMSE = 2.1 m). This was attributable to a general over-estimation of canopy heights in the satellite PCD. ALS models produced poor estimates of stand density (R2 = 0.48; RMSE = 112.1 stems ha−1), as did the satellite PCD models (R2 = 0.42; RMSE = 118.4 stems ha−1). ALS models produced accurate estimates of basal area (R2 = 0.58; RMSE = 12 m2 ha−1), total stem volume (R2 = 0.72; RMSE = 107.5 m3 ha−1), and total recoverable volume (R2 = 0.74; RMSE = 92.9 m3 ha−1). These values differed little from the estimates of basal area (R2 = 0.57; RMSE = 12.2 m2 ha−1), total stem volume (R2 = 0.70; RMSE = 112.6 m3 ha−1), and total recoverable volume (R2 = 0.73; RMSE = 96 m3 ha−1) obtained from satellite PCD models. The statistical and textural metrics computed from the CHMs were important variables in all of the models derived from both satellite and ALS PCD, nearly always outranking the standard PCD metrics in measures of importance. For the satellite PCD models, the CHM-derived metrics were nearly exclusively identified as important variables. These results clearly show that point cloud data obtained from stereo satellite imagery are useful for prediction of forest inventory attributes in intensively managed forests on steeper terrain. Furthermore, these data offer forest managers the benefit of obtaining both inventory data and high-resolution multispectral imagery from a single product. Numéro de notice : A2018-295 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.06.006 Date de publication en ligne : 22/06/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.06.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90413 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018081	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018083	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018082	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Modeling diameter distributions in radiata pine plantations in Spain with existing countrywide LiDAR data / Manuel Arias-Rodil in Annals of Forest Science, vol 75 n° 2 (June 2018)  

Public [article]  inAnnals of Forest Science > vol 75 n° 2 (June 2018) Titre : Modeling diameter distributions in radiata pine plantations in Spain with existing countrywide LiDAR data Type de document : Article/Communication Auteurs : Manuel Arias-Rodil, Auteur ; Ulises Diéguez-Aranda, Auteur ; Juan Gabriel Álvarez-González, Auteur ; César Pérez-Cruzado, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] diamètre des arbres [Termes IGN] distance de Kolmogorov-Smirnov [Termes IGN] données altimétriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Espagne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Pinus radiata [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Key message: We evaluated the use of low-density airborne laser scanning data to estimate diameter distributions in radiata pine plantations. The moment-based parameter recovery method was used to estimate the diameter distributions, considering LiDAR metrics as explanatory variables. The fitted models explained more than 77% of the observed variability. This approach can be replicated every 6 years (temporal cover planned for countrywide LiDAR flights in Spain). Context:The estimation of stand diameter distribution is informative for forest managers in terms of stand structure, forest growth model inputs, and economic timber value. In this sense, airborne LiDAR may represent an adequate source of information. Aims: The objective was to evaluate the use of low-density Spanish countrywide LiDAR data for estimating diameter distributions in Pinus radiata D. Don stands in NW Spain. Methods: The empirical distributions were obtained from 25 sample plots. We applied the moment-based parameter recovery method in combination with the Weibull function to estimate the diameter distributions, considering LiDAR metrics as explanatory variables. We evaluated the results by using the Kolmogorov–Smirnov (KS) test and a classification tree and random forest (RF) to relate the KS test result for each plot to stand-level variables. Results: The models used to estimate average (dm) and quadratic (dg) mean diameters from LiDAR metrics, required for recovery of the Weibull parameters, explained a high percentage of the observed variance (77 and 80%, respectively), with RMSE values of 3.626 and 3.422 cm for the same variables. However, the proportion of plots accepted by the KS was low. This poor performance may be due to the strictness of the KS test and/or by the characteristics of the LiDAR flight. Conclusion: The results justify the assessment of this approach over different species and forest types in regional or countrywide surveys. Numéro de notice : A2018-327 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-018-0712-z Date de publication en ligne : 16/03/2018 En ligne : https://doi.org/10.1007/s13595-018-0712-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90470 [article]

The pine shoot beetle Tomicus piniperda as a plausible vector of Fusarium circinatum in northern Spain / Diana Bezos in Annals of Forest Science, vol 72 n° 8 (December 2015)  

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Potential use of pine plantations to restore native forests in a highly fragmented river basin / Miren Onaindia in Annals of Forest Science, Vol 66 n° 3 (April - May 2009)  

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