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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)
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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 IGN] croissance des arbres
[Termes IGN] diamètre des arbres
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] erreur systématique
[Termes IGN] Finlande
[Termes IGN] humidité du sol
[Termes IGN] indice d'humidité
[Termes IGN] Leaf Area Index
[Termes IGN] modèle de croissance végétale
[Termes IGN] Perceptron multicoucheRésumé : (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 Affiliation des auteurs : non IGN 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
in Forestry, an international journal of forest research > vol 92 n° 3 (July 2019) . - pp 253 - 263[article]Analyzing the recent dynamics of wildland fires in Quercus suber L. woodlands in Sardinia (Italy), Corsica (France) and Catalonia (Spain) / Michele Salis in European Journal of Forest Research, vol 138 n° 3 (June 2019)
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Titre : Analyzing the recent dynamics of wildland fires in Quercus suber L. woodlands in Sardinia (Italy), Corsica (France) and Catalonia (Spain) Type de document : Article/Communication Auteurs : Michele Salis, Auteur ; Bachisio Arca, Auteur ; Fermin Alcasena-Urdiroz, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 415 - 431 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] bassin méditerranéen
[Termes IGN] Catalogne (Espagne)
[Termes IGN] Corse
[Termes IGN] données socio-économiques
[Termes IGN] incendie de forêt
[Termes IGN] précipitation
[Termes IGN] Quercus suber
[Termes IGN] régression logistique
[Termes IGN] SardaigneRésumé : (Auteur) Wildland fires represent a major threat to Quercus suber L. ecosystems, which provide relevant socioeconomic and ecological services in the Mediterranean Basin. In this work, we analyzed recent wildland fire dynamics in cork oak woodlands along the fire-prone areas of Sardinia (Italy), Corsica (France) and Catalonia (Spain). We first characterized geographic extent and main characteristics of cork oak woodlands in these regions and analyzed how environmental (climate and elevation) and socioeconomic factors (population and land uses) vary in the areas covered by Quercus suber L. We then evaluated how wildfires affected cork oak stands and, by logistic regression analysis, to what extent wildfires in cork oak areas were related to the above set of environmental and anthropic explanatory variables. Results revealed specific variations across study areas in cork oak characteristics as well as in environmental and social factors. We highlighted the spatial and temporal patterns of wildfires on cork oak woodlands, in terms of extent, seasonality, frequency and main driving factors. In the period 2003–2015, the percentage of cork oak woodlands burned ranged from 3.42% in Corsica to 11.30% in Sardinia. A few large and severe wildfires accounted for most of the area burned in cork oak woodlands. The most significant predictive variable that explained the spatial variation in wildland fire ignitions inside or nearby cork oaks was summer precipitation, while the weight of other factors varied depending on the region. This study provides evidence on recent fire dynamics in cork oak woodlands and gives valuable information and insights for the implementation of forest management and planning strategies in the Mediterranean area. Numéro de notice : A2019-243 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10342-019-01179-1 Date de publication en ligne : 20/02/2019 En ligne : https://doi.org/10.1007/s10342-019-01179-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92746
in European Journal of Forest Research > vol 138 n° 3 (June 2019) . - pp 415 - 431[article]Combining low-density LiDAR and satellite images to discriminate species in mixed Mediterranean forest / Angela Blázquez-Casado in Annals of Forest Science, vol 76 n° 2 (June 2019)
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Titre : Combining low-density LiDAR and satellite images to discriminate species in mixed Mediterranean forest Type de document : Article/Communication Auteurs : Angela Blázquez-Casado, Auteur ; Rafael Calama, Auteur ; Manuel Valbuena, Auteur ; Marta Vergarechea, Auteur ; Francisco Rodriguez, Auteur Année de publication : 2019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse discriminante
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt méditerranéenne
[Termes IGN] houppier
[Termes IGN] image Pléiades-HR
[Termes IGN] Pinus pinaster
[Termes IGN] Pinus pineaRésumé : (Auteur) Context : The discrimination of tree species at individual level in mixed Mediterranean forest based on remote sensing is a field which has gained greater importance. In these stands, the capacity to predict the quality and quantity of non-wood forest products is particularly important due to the very different goods the two species produce.
Aims : To assess the potential of using low-density airborne LiDAR data combined with high-resolution Pleiades images to discriminate two different pine species in mixed Mediterranean forest (Pinus pinea L. and Pinus pinaster Ait.) at individual tree level.
Methods : A Random Forest model was trained using plots from the pure stand dataset, determining which LiDAR and satellite variables allow us to obtain better discrimination between groups. The model constructed was then validated by classifying individuals in an independent set of pure and mixed stands.
Results : The model combining LiDAR and Pleiades data provided greater accuracy (83.3% and 63% in pure and mixed validation stands, respectively) than the models which only use one type of covariables.
Conclusion : The automatic crown delineation tool developed allows two very similar species in mixed Mediterranean conifer forest to be discriminated using continuous spatial information at the surface: Pleiades images and open source LiDAR data. This approach is easily applicable over large areas, enhancing the economic value of non-wood forest products and aiding forest managers to accurately predict production.Numéro de notice : A2019-180 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0835-x Date de publication en ligne : 17/05/2019 En ligne : https://doi.org/10.1007/s13595-019-0835-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92700
in Annals of Forest Science > vol 76 n° 2 (June 2019)[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)
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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 forestierRésumé : (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
in ISPRS Journal of photogrammetry and remote sensing > vol 152 (June 2019) . - pp 66 - 78[article]Réservation
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Titre : A general method for the classification of forest stands using species composition and vertical and horizontal structure Type de document : Article/Communication Auteurs : Miquel De Cáceres, Auteur ; Santiago Martín-Alcón, Auteur ; José Ramon Gonzalez-Olabarria, Auteur ; Lluis Coll, Auteur Année de publication : 2019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse bivariée
[Termes IGN] analyse univariée
[Termes IGN] Catalogne (Espagne)
[Termes IGN] composition floristique
[Termes IGN] diamètre des arbres
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] peuplement forestier
[Termes IGN] similitude
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] typologie forestière
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) Context : Forest typologies are useful for many purposes, including forest mapping, assessing habitat quality, studying forest dynamics, or defining sustainable management strategies. Quantitative typologies meant for forestry applications normally focus on horizontal and vertical structure of forest plots as main classification criteria, with species composition often playing a secondary role. The selection of relevant variables is often idiosyncratic and influenced by a priori expectations of the forest types to be distinguished.
Aims : We present a general framework to define forest typologies where the dissimilarity between forest stands is assessed using coefficients that integrate the information of species composition with the univariate distribution of tree diameters or heights or the bivariate distribution of tree diameters and heights.
Methods : We illustrate our proposal with the classification of forest inventory plots in Catalonia (NE Spain), comparing the results obtained using the bivariate distribution of diameters and heights to those obtained using either tree heights or tree diameters only.
Results : The number of subtypes obtained using the tree diameter distribution for the calculation of dissimilarity was often the same as those obtained from the tree height distribution or to those using the bivariate distribution. However, classifications obtained using the three approaches were often different in terms of forest plot membership.
Conclusion : The proposed classification framework is particularly suited to define forest typologies from forest inventory data and allows taking advantage of the bivariate distribution of diameters and heights if both variables are measured. It can provide support to the development of typologies in situations where fine-scale variability of topographic, climatic, and legacy management factors leads to fine-scale variation in forest structure and composition, including uneven-aged and mixed stands.Numéro de notice : A2019-183 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0824-0 Date de publication en ligne : 12/04/2019 En ligne : https://doi.org/10.1007/s13595-019-0824-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92704
in Annals of Forest Science > vol 76 n° 2 (June 2019)[article]Genetic diversity and structure of Silver fir (Abies alba Mill.) at the south-eastern limit of its distribution range / Maria Teodosiu in Annals of forest research, vol 62 n° 2 (June - December 2019)
PermalinkInvestigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data : A case study of Wuhan, Central China / Xin Huang in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)
PermalinkLong-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia / Enkhjargal Natsagdorj in Geocarto international, vol 34 n° 7 ([01/06/2019])
PermalinkA new stochastic simulation algorithm for image-based classification : Feature-space indicator simulation / Qing Wang in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)
PermalinkObject-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment / Eduarda M.O. Silveira in International journal of applied Earth observation and geoinformation, vol 78 (June 2019)
PermalinkRegisTree: a registration algorithm to enhance forest inventory plot georeferencing / Maryem Fadili in Annals of Forest Science, vol 76 n° 2 (June 2019)
PermalinkSite and age-dependent responses of Picea abies growth to climate variability / Petr Čermák in European Journal of Forest Research, vol 138 n° 3 (June 2019)
PermalinkTélédétection radar : de l'image d'intensité initiale au choix du mode de calibration des coefficients de diffusion / Jean-Paul Rudant in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)
PermalinkThe conservation status assessment of Natura 2000 forest habitats in Europe: capabilities, potentials and challenges of national forest inventories data / Iciar A. Alberdi in Annals of Forest Science, vol 76 n° 2 (June 2019)
PermalinkTree and stand level estimations of Abies alba Mill. aboveground biomass / Andrzej M. Jagodzinski in Annals of Forest Science, vol 76 n° 2 (June 2019)
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