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Automated inventory of broadleaf tree plantations with UAS imagery / Aishwarya Chandrasekaran in Remote sensing, vol 14 n° 8 (April-2 2022)  

Public [article]  inRemote sensing > vol 14 n° 8 (April-2 2022) . - n° 1931 Titre : Automated inventory of broadleaf tree plantations with UAS imagery Type de document : Article/Communication Auteurs : Aishwarya Chandrasekaran, Auteur ; Guofan Shao, Auteur ; Songlin Fei, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1931 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] feuillu [Termes IGN] hauteur à la base du houppier [Termes IGN] hauteur des arbres [Termes IGN] image captée par drone [Termes IGN] Indiana (Etats-Unis) [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] orthophotoplan numérique [Termes IGN] plantation forestière [Termes IGN] R (langage) [Termes IGN] semis de points [Termes IGN] structure-from-motion Résumé : (auteur) With the increased availability of unmanned aerial systems (UAS) imagery, digitalized forest inventory has gained prominence in recent years. This paper presents a methodology for automated measurement of tree height and crown area in two broadleaf tree plantations of different species and ages using two different UAS platforms. Using structure from motion (SfM), we generated canopy height models (CHMs) for each broadleaf plantation in Indiana, USA. From the CHMs, we calculated individual tree parameters automatically through an open-source web tool developed using the Shiny R package and assessed the accuracy against field measurements. Our analysis shows higher tree measurement accuracy with the datasets derived from multi-rotor platform (M600) than with the fixed wing platform (Bramor). The results show that our automated method could identify individual trees (F-score > 90%) and tree biometrics (root mean square error Numéro de notice : A2022-351 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14081931 Date de publication en ligne : 16/04/2022 En ligne : https://doi.org/10.3390/rs14081931 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100539 [article]

Afforestation with Pinus nigra Arn ssp salzmannii along an elevation gradient: controlling factors and implications for climate change adaptation / Manuel Esteban Lucas-Borja in Trees, vol 36 n° 1 (February 2022)  

Public [article]  inTrees > vol 36 n° 1 (February 2022) . - pp 93 - 102 Titre : Afforestation with Pinus nigra Arn ssp salzmannii along an elevation gradient: controlling factors and implications for climate change adaptation Type de document : Article/Communication Auteurs : Manuel Esteban Lucas-Borja, Auteur ; Xin Jing, Auteur ; David Candel-Perez, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 93 - 102 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] afforestation [Termes IGN] bassin méditerranéen [Termes IGN] Espagne [Termes IGN] gradient d'altitude [Termes IGN] mortalité [Termes IGN] Pinus nigra salzmannii [Termes IGN] plantation forestière [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Spanish black pine (Pinus nigra Arn ssp. salzmannii) is the most widely distributed pine species in mountain areas of the Mediterranean Basin and is commonly used for afforestation in endangered and degraded areas. Despite its importance, little is known regarding the factors driving seedling survival for this species, which may hamper afforestation success in Mediterranean areas. In this study, we assessed the effects of seed origin and plantation site along a natural gradient with contrasting elevation and climatic conditions in a Mediterranean forest in Central-Eastern Spain. Our results showed: (1) higher seedling survival rates when seed origin differed from plantation site (25.3 ± 5.4%) compared to same origin and plantation site (5.3 ± 2.7%); (2) higher survival probability (~ 20%) for high and medium elevation seeds (colder and wetter locations) compared to the warmer and drier low elevation sites (15%); (3) higher seedling survival (~ 40%) at higher elevation sites compared to low-elevation sites ( Numéro de notice : A2021-975 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s00468-021-02184-x Date de publication en ligne : 22/07/2021 En ligne : http://dx.doi.org/10.1007/s00468-021-02184-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100418 [article]

The long-term development of temperate woodland creation sites: from tree saplings to mature woodlands / Elisa Fuentes-Montemayor in Forestry, an international journal of forest research, vol 95 n° 1 (January 2022)  

Public [article]  inForestry, an international journal of forest research > vol 95 n° 1 (January 2022) . - pp 28 - 37 Titre : The long-term development of temperate woodland creation sites: from tree saplings to mature woodlands Type de document : Article/Communication Auteurs : Elisa Fuentes-Montemayor, Auteur ; Kirsty J. Park, Auteur ; Kypfer Cordts, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 28 - 37 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] adaptation (biologie) [Termes IGN] aménagement forestier [Termes IGN] boisement artificiel [Termes IGN] détection de changement [Termes IGN] forêt ancienne [Termes IGN] parcelle forestière [Termes IGN] plantation forestière [Termes IGN] résilience écologique [Termes IGN] Royaume-Uni [Termes IGN] sous-étage [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Tree planting is at the forefront of the current environmental agenda to mitigate climate change and tackle the biodiversity crisis. In the United Kingdom (UK), tree planting has been a priority for more than a century and has helped increase woodland cover from a historic low of 5 per cent at the beginning of the 20th century to a current figure of 13 per cent. However, we still know relatively little about the long-term development of woodland creation sites (particularly of native woodlands) over ecologically realistic timescales. We surveyed a chronosequence of 133 temperate woodland patches encompassing 106 woodland creation sites (10–160 years old) and 27 mature ‘ancient’ woodlands (>250 years old), using a combination of field surveys and remote sensing techniques to quantify vegetation structural changes associated with woodland development. Woodland creation sites displayed similar vegetation development patterns to those described for other woodland systems, i.e. a gradual transition as woodlands undergo ‘stand initiation’, ‘stem exclusion’ and ‘understorey re-initiation’ stages, and became more similar to ‘ancient’ woodlands over time. Structural heterogeneity, average tree size and tree density were the attributes that varied the most among woodland developmental stages. In general, structural heterogeneity and average tree size increased with woodland age, whilst tree density decreased as would be expected. Younger sites in stand initiation were strongly dominated by short vegetation, stem exclusion sites by taller trees and older sites had a more even vegetation height distribution. There was a large degree of overlap between the vegetation characteristics of woodlands in understorey re-initiation stages and older ancient woodlands (partly driven by a lack of regeneration in the understorey); these results suggest that it takes between 80 and 160 years for woodland creation sites to develop certain vegetation attributes similar to those of mature ancient woodlands included in this study. Woodland management practices to create canopy gaps and reducing grazing/browsing pressure to promote natural regeneration are likely to accelerate this transition, increase the structural heterogeneity and biodiversity value of woodland creation sites and enable adaptation and resilience to climate change. Numéro de notice : A2022-115 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1093/forestry/cpab027 Date de publication en ligne : 03/06/2021 En ligne : https://doi.org/10.1093/forestry/cpab027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99639 [article]

Automatic detection of planted trees and their heights using photogrammetric rpa point clouds / Kênia Samara Mourão Santos in Boletim de Ciências Geodésicas, vol 27 n° 3 ([01/10/2021])  

Public [article]  inBoletim de Ciências Geodésicas > vol 27 n° 3 [01/10/2021] Titre : Automatic detection of planted trees and their heights using photogrammetric rpa point clouds Type de document : Article/Communication Auteurs : Kênia Samara Mourão Santos, Auteur ; Christel Lingnau, Auteur ; Daniel Rodrigues dos Santos, Auteur Année de publication : 2021 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] détection d'arbres [Termes IGN] hauteur des arbres [Termes IGN] image aérienne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Parana (Brésil) [Termes IGN] Pinus taeda [Termes IGN] plantation forestière [Termes IGN] semis de points Résumé : (auteur) This work aims to analyze the potential of the Photogrammetric Point Cloud (PPC) obtained from Remote Piloted Aircraft (RPA) optical images for detecting and obtaining tree heights in a loblolly pine plantation using a global maximum filter. The enhanced algorithm used in this study is then named STD (Single Tree Detection). Field surveys were conducted to count all the trees in the field (Forest Census) and measure the trees’ height with a vertex hypsometer. The results were faced to PCC outcomes. The detection rate (r) was equal to the precision rate (p), indicating that the algorithm reaches a high tree detection performance. In summary, the STD algorithm segmented 2,192 trees, representing 89% of trees recorded in the forest census. The retrieved tree height reached, on average, a height of 17.05 m, whereas slightly higher by the traditional forest inventory (17.42 m). The root-mean-square error (RMSE) and Bias were 47 cm (2.8%) and -37 cm (-2.2%), respectively. The Dunnett test showed that the tree height did not significantly differ between the results obtained by traditional forest inventory from those generated by the STD. It confirms the potential use of PPC for forest inventory procedures. Numéro de notice : A2021-958 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1590/s1982-21702021000300025 En ligne : https://doi.org/10.1590/s1982-21702021000300025 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100075 [article]

Automated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN) / Zhenbang Hao in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 178 (August 2021) . - pp 112 - 123 Titre : Automated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN) Type de document : Article/Communication Auteurs : Zhenbang Hao, Auteur ; Lili Lin, Auteur ; Christopher J. Post, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 112 - 123 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Abies (genre) [Termes IGN] Abies numidica [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection automatique [Termes IGN] hauteur des arbres [Termes IGN] houppier [Termes IGN] image captée par drone [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] plantation forestière Résumé : (auteur) Tree-crown and height are primary tree measurements in forest inventory. Convolutional neural networks (CNNs) are a class of neural networks, which can be used in forest inventory; however, no prior studies have developed a CNN model to detect tree crown and height simultaneously. This study is the first-of-its-kind that explored training a mask region-based convolutional neural network (Mask R-CNN) for automatically and concurrently detecting discontinuous tree crown and height of Chinese fir (Cunninghamia lanceolata (Lamb) Hook) in a plantation. A DJI Phantom4-Multispectral Unmanned Aerial Vehicle (UAV) was used to obtain high-resolution images of the study site, Shunchang County, China. Tree crown and height of Chinese fir was manually delineated and derived from this UAV imagery. A portion of the ground-truthed tree height values were used as a test set, and the remaining measurements were used as the model training data. Six different band combinations and derivations of the UAV imagery were used to detect tree crown and height, respectively (Multi band-DSM, RGB-DSM, NDVI-DSM, Multi band-CHM, RGB-CHM, and NDVI-CHM combination). The Mask R-CNN model with the NDVI-CHM combination achieved superior performance. The accuracy of Chinese fir’s individual tree-crown detection was considerable (F1 score = 84.68%), the Intersection over Union (IoU) of tree crown delineation was 91.27%, and tree height estimates were highly correlated with the height from UAV imagery (R2 = 0.97, RMSE = 0.11 m, rRMSE = 4.35%) and field measurement (R2 = 0.87, RMSE = 0.24 m, rRMSE = 9.67%). Results demonstrate that the input image with an CHM achieves higher accuracy of tree crown delineation and tree height assessment compared to an image with a DSM. The accuracy and efficiency of Mask R-CNN has a great potential to assist the application of remote sensing in forests. Numéro de notice : A2021-563 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2021.06.003 Date de publication en ligne : 18/06/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.06.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98128 [article]

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