Descripteur
Documents disponibles dans cette catégorie (1275)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Comparative use of PPK-integrated close-range terrestrial photogrammetry and a handheld mobile laser scanner in the measurement of forest road surface deformation / Remzi Eker in Measurement, vol 206 (January 2023)
[article]
Titre : Comparative use of PPK-integrated close-range terrestrial photogrammetry and a handheld mobile laser scanner in the measurement of forest road surface deformation Type de document : Article/Communication Auteurs : Remzi Eker, Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre
[Termes IGN] analyse comparative
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] chemin forestier
[Termes IGN] déformation de surface
[Termes IGN] lidar mobile
[Termes IGN] positionnement cinématique
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] télémétrie laser terrestre
[Termes IGN] TurquieRésumé : (auteur) This study aimed to compare a handheld mobile laser scanning (HMLS), called TORCH that uses the SLAM algorithm, and a PPK-integrated close-range terrestrial photogrammetry (CRTP) to measure forest road surface deformation. The PPK-integrated CRTP includes a multiband GNSS-module and a camera mounted on a 5-m prism pole. 3D point-clouds were gathered/produced at three different dates with approximately 3-month intervals. And then road surface deformations were determined by applying the M3C2 algorithm. Each method was compared by considering some advantages and disadvantages. PPK-integrated CRTP, which could only be used in areas where the GPS signal is not blocked, provided highly denser 3D point clouds than HMLS. However, for the first period, the difference of mean deformation values between the two methods was not statistically significant, whereas it was statistically significant for the second period. Both methods can be suggested to use in forest road surface deformation yet considering their limitations. Numéro de notice : A2023-043 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.measurement.2022.112322 Date de publication en ligne : 14/12/2022 En ligne : https://doi.org/10.1016/j.measurement.2022.112322 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102330
in Measurement > vol 206 (January 2023)[article]Detection of growth change of young forest based on UAV RGB images at single-tree level / Xiaocheng Zhou in Forests, vol 14 n° 1 (January 2023)
[article]
Titre : Detection of growth change of young forest based on UAV RGB images at single-tree level Type de document : Article/Communication Auteurs : Xiaocheng Zhou, Auteur ; Hongyu Wang, Auteur ; Chongcheng Chen, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 141 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Abies (genre)
[Termes IGN] âge du peuplement forestier
[Termes IGN] Chine
[Termes IGN] croissance des arbres
[Termes IGN] détection de changement
[Termes IGN] hauteur des arbres
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] jeune arbre
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] surveillance forestièreRésumé : (auteur) With the rapid development of Unmanned Aerial Vehicle (UAV) technology, more and more UAVs have been used in forest survey. UAV (RGB) images are the most widely used UAV data source in forest resource management. However, there is some uncertainty as to the reliability of these data when monitoring height and growth changes of low-growing saplings in an afforestation plot via UAV RGB images. This study focuses on an artificial Chinese fir (Cunninghamia lancelota, named as Chinese Fir) young forest plot in Fujian, China. Divide-and-conquer (DAC) and the local maximum (LM) method for extracting seedling height are described in the paper, and the possibility of monitoring young forest growth based on low-cost UAV remote sensing images was explored. Two key algorithms were adopted and compared to extract the tree height and how it affects the young forest at single-tree level from multi-temporal UAV RGB images from 2019 to 2021. Compared to field survey data, the R2 of single saplings’ height extracted from digital orthophoto map (DOM) images of tree pits and original DSM information using a divide-and-conquer method reached 0.8577 in 2020 and 0.9968 in 2021, respectively. The RMSE reached 0.2141 in 2020 and 0.1609 in 2021. The R2 of tree height extracted from the canopy height model (CHM) via the LM method was 0.9462. The RMSE was 0.3354 in 2021. The results demonstrated that the survival rates of the young forest in the second year and the third year were 99.9% and 85.6%, respectively. This study shows that UAV RGB images can obtain the height of low sapling trees through a computer algorithm based on using 3D point cloud data derived from high-precision UAV images and can monitor the growth of individual trees combined with multi-stage UAV RGB images after afforestation. This research provides a fully automated method for evaluating the afforestation results provided by UAV RGB images. In the future, the universality of the method should be evaluated in more afforestation plots featuring different tree species and terrain. Numéro de notice : A2023-115 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f14010141 Date de publication en ligne : 10/01/2023 En ligne : https://doi.org/10.3390/f14010141 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102482
in Forests > vol 14 n° 1 (January 2023) . - n° 141[article]Forest road extraction from orthophoto images by convolutional neural networks / Erhan Çalişkan in Geocarto international, vol 38 n° inconnu ([01/01/2023])
[article]
Titre : Forest road extraction from orthophoto images by convolutional neural networks Type de document : Article/Communication Auteurs : Erhan Çalişkan, Auteur ; Yusuf Sevim, Auteur Année de publication : 2023 Article en page(s) : pp Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] chemin forestier
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] extraction automatique
[Termes IGN] orthoimage
[Termes IGN] segmentation sémantiqueRésumé : (auteur) Continuous monitoring of the forest road infrastructure and keeping track of the changes occurred are important for forestry practices, map updating, forest fire and forest transport decision support systems. In this context, the most of up to date data can be obtained by automatic forest road extraction from satellite images via machine learning (ML). Acquiring sufficient data is one of the most important factors which affect the success of ML and deep learning (DL). DL architectures yield more consistent results for complex data sets compared with ML algorithms. In the present study, three different deep learning (Resnet-18, MobileNet-V2 and Xception) architectures with semantic segmentation architecture were compared for extracting the forest road network from high-resolution orthophoto images and the results were analyzed. The architectures were evaluated through a multiclass statistical analysis based precision, recall, F1 score, intersection over union and overall accuracy (OA). The results present significant values obtained by the Resnet-18 architecture, with 99.72% of OA and 98.87% of precision and by the MobileNet-V2 architecture, with 97.76% of OA and 98.28% of precision. Also the results show that Resnet-18, MobileNet-V2 semantic segmentation architectures can be used efficiently for forest road extraction. Numéro de notice : A2022-159 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1080/10106049.2022.2060319 Date de publication en ligne : 06/04/2022 En ligne : https://doi.org/10.1080/10106049.2022.2060319 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100380
in Geocarto international > vol 38 n° inconnu [01/01/2023] . - pp[article]Improving generalized models of forest structure in complex forest types using area- and voxel-based approaches from lidar / Andrew W. Whelan in Remote sensing of environment, vol 284 (January 2023)
[article]
Titre : Improving generalized models of forest structure in complex forest types using area- and voxel-based approaches from lidar Type de document : Article/Communication Auteurs : Andrew W. Whelan, Auteur ; Jeffery B. Cannon, Auteur ; Seth W. Bigelow, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 113362 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] diagnostic foliaire
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Géorgie (Etats-Unis)
[Termes IGN] modélisation de la forêt
[Termes IGN] Pinus palustris
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] surface forestière
[Termes IGN] volume en bois
[Termes IGN] voxelRésumé : (auteur) Modeling forest attributes using lidar data has been a useful tool for forest management but the need to correlate lidar to ground-based measurements creates challenges to modeling in diverse forest landscapes. Many lidar models have been based on metrics derived from summarizations of individual lidar returns over sample plot areas, but more recently, metrics based on summarization by volumetric pixel (voxel) have shown promise to better characterize forest structure and distinguish between diverse forest types. Voxel-based metrics may improve characterization of leaf area distribution and horizontal forest structure, which could help create general models of forest attributes applicable in complex landscapes composed of many distinct forest types. We modeled wood volume in longleaf pine woodlands and associated forests to compare how area- and voxel- based lidar metrics predicted wood volume in forest type specific and general predictive models. We created four area-based and six voxel-based metrics to fit models of wood volume using a multiplicative power function. We selected models and compared metric importance using AIC and evaluated model performance using cross-validated mean prediction error. We found that one area-based metric and four voxel-based metrics consistently improved model predictions We suggest that area-based metrics alone may have limitations for characterizing complex forest structure. Area-based summarizes of lidar returns are more heavily influenced by upper canopy returns because lidar returns attenuate below the canopy. By contrast, summarizing lidar returns into a single value per voxel prior to summarization over plots homogenizes point density, giving added weight to sub-canopy returns. Thus voxel-based metrics may be more sensitive to structural variation that may not be adequately captured by area-based metrics alone. This study highlights the potential of voxel-based metrics for characterizing complex forest structure and model generalization capable of accurate forest attribute prediction across diverse forest types. Numéro de notice : A2023-016 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113362 Date de publication en ligne : 23/11/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113362 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102150
in Remote sensing of environment > vol 284 (January 2023) . - n° 113362[article]Management of birch spruce mixed stands with consideration of carbon stock in biomass and harvested wood products / Jānis Vuguls in Forests, vol 14 n° 1 (January 2023)
[article]
Titre : Management of birch spruce mixed stands with consideration of carbon stock in biomass and harvested wood products Type de document : Article/Communication Auteurs : Jānis Vuguls, Auteur ; Stefanija Dubra, Auteur ; Anete Garanca, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 57 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Betula (genre)
[Termes IGN] bilan du carbone
[Termes IGN] biomasse forestière
[Termes IGN] changement climatique
[Termes IGN] gestion forestière durable
[Termes IGN] peuplement mélangé
[Termes IGN] Picea abies
[Termes IGN] plante ligneuse
[Termes IGN] puits de carbone
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Forests play an important role in climate change mitigation. Usage of harvested wood products (HWP) can extend the carbon cycle by retaining carbon as well as preventing new fossil emission via substitution. We compared carbon balance of different management strategies of birch spruce mixed stands over an eight-year period: unmanaged, representing a decision of prolonged rotation, and managed, representing a decision of final harvest of birch and retention of spruce for continuous forest cover and regeneration harvest. Management resulted in a higher contribution of mixed stands to climate change mitigation, if the carbon stock (CS) in biomass as well carbon balance (CB) of wood product is jointly considered in comparison to no management (prolonged rotation). Assortment structure plays an important role in CB of HWP, therefore a practice ensuring higher outcome of longer-lasting wood products are beneficial to climate change mitigation. Numéro de notice : A2023-041 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f14010057 Date de publication en ligne : 28/12/2022 En ligne : https://doi.org/10.3390/f14010057 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102327
in Forests > vol 14 n° 1 (January 2023) . - n° 57[article]PermalinkMitigating the risk of wind damage at the forest landscape level by using stand neighbourhood and terrain elevation information in forest planning / Roope Ruotsalainen in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)PermalinkA new strategy for improving the accuracy of forest aboveground biomass estimates in an alpine region based on multi-source remote sensing / Yali Zhang in GIScience and remote sensing, vol 60 n° 1 (2023)PermalinkPrescribed fire after thinning increased resistance of sub-Mediterranean pine forests to drought events and wildfires / Lena Vilà-Vilardell in Forest ecology and management, vol 527 (January-1 2023)PermalinkTaller and slenderer trees in Swedish forests according to data from the National Forest Inventory / Alex Appiah Mensah in Forest ecology and management, vol 527 (January-1 2023)PermalinkUAV DTM acquisition in a forested area – comparison of low-cost photogrammetry (DJI Zenmuse P1) and LiDAR solutions (DJI Zenmuse L1) / Martin Štroner in European journal of remote sensing, vol 56 n° 1 (2023)PermalinkInteractive effects of abiotic factors and biotic agents on Scots pine dieback: A multivariate modeling approach in southeast France / Jean Lemaire in Forest ecology and management, vol 526 (December-15 2022)PermalinkAbove ground biomass estimation from UAV high resolution RGB images and LiDAR data in a pine forest in Southern Italy / Mauro Maesano in iForest, biogeosciences and forestry, vol 15 n° 6 (December 2022)PermalinkClimate and ungulate browsing impair regeneration dynamics in spruce-fir-beech forests in the French Alps / Mithila Unkule in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkClimate envelope analyses suggests significant rearrangements in the distribution ranges of Central European tree species / Gàbor Illés in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkForêt amazonienne : de nouveau sous contrôle ? / Laurent Polidori in Géomètre, n° 2208 (décembre 2022)PermalinkHarvested area did not increase abruptly-how advancements in satellite-based mapping led to erroneous conclusions / Johannes Breidenbach in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkIdentification and spatial extent of understory plant species requiring vegetation control to ensure tree regeneration in French forests / Noé Dumas in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkImpact of skidding operations on forest soils: a narrative review / Monica Cecilia Zurita Vintimilla in Revista Padurilor, vol 137 n° 4 (2022)PermalinkInstance segmentation of standing dead trees in dense forest from aerial imagery using deep learning / Aboubakar Sani-Mohammed in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 6 (December 2022)PermalinkOffering the appetite for the monitoring of European forests a diversified diet / Jean-Daniel Bontemps in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkPotentials and limitations of NFIs and remote sensing in the assessment of harvest rates: a reply to Breidenbach et al. / Guido Ceccherini in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkThe contribution of understorey vegetation to ecosystem evapotranspiration in boreal and temperate forests: a literature review and analysis / Philippe Balandier in European Journal of Forest Research, vol 141 n° 6 (December 2022)PermalinkThe role of wood harvest from sustainably managed forests in the carbon cycle / Ernst Detlef Schulze in Annals of Forest Science, vol 79 n° 1 (2022)PermalinkDevelopment and long-term dynamics of old-growth beech-fir forests in the Pyrenees: Evidence from dendroecology and dynamic vegetation modelling / Dario Martín-Benito in Forest ecology and management, vol 524 (November-15 2022)Permalink