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Silvicultural experiment assessment using lidar data collected from an unmanned aerial vehicle / Diogo N. Cosenza in Forest ecology and management, vol 522 (October-15 2022)  

Public [article]  inForest ecology and management > vol 522 (October-15 2022) . - n° 120489 Titre : Silvicultural experiment assessment using lidar data collected from an unmanned aerial vehicle Type de document : Article/Communication Auteurs : Diogo N. Cosenza, Auteur ; Jason Vogel, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 120489 Langues : Anglais (eng) Descripteur : [Termes IGN] croissance végétale [Termes IGN] données allométriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] modélisation de la forêt [Termes IGN] Pinus taeda [Termes IGN] plantation forestière [Termes IGN] sylviculture [Vedettes matières IGN] Foresterie Résumé : (auteur) Collecting field data in silvicultural experiments can be challenging and time-consuming. Alternatively, unmanned aerial vehicles using laser scanners (UAV-lidar) can be used for cost-effective data collection in forest stands. This work aims to assess the capability of UAV-lidar to estimate biophysical forest attributes in silvicultural experiments. The showcase experiment refers to the IMPAC II (Intensive Management Practices Assessment Center II), a long-term project of 24 plots aiming to assess the effects of fertilization and weed control on forest growth and nutrient cycling in past and ongoing silvicultural treatments in a second rotation of loblolly pine (Pinus taeda L.) plantation at age 12 years. Treatment performances were assessed based on four biometric attributes related to forest productivity: Growing stock biomass (Mg ha−1), stem volume (m3 ha−1), dominant height (m), and leaf area index (LAI, m2 m−2). We used the area-based approach (ABA) and multiple linear models to characterize these forest attributes in the different silvicultural treatments and use their predictions to run the experiment analysis. Two groups of ALS-derived metrics were tested in the modeling, traditional metrics and a novel group of metrics based on plant area density (PAD) distribution. Models using PAD-based metrics increased the correlation between observed and predicted values (R2) from 0.27–0.40 to 0.50–0.85 when compared to the same models using traditional metrics, while the relative root mean square errors (RMSE%) of the predictions were reduced from 6–18% to 4–12%. Experiment analysis using UAV-lidar data and PAD-based model predictors led to the same results as those using field observations: i) fertilization was the most effective treatment for enhancing stand attributes, especially in terms of biomass, stem volume, and LAI; ii) weed control alone provided marginal improvements in the stands; iii) actively retreating stands in both first and second rotation led to increased growth when compared to the carryover effects. UAV-lidar using PAD-based metrics was effective in characterizing enhanced silvicultural treatments and might benefit studies involving understory assessment. Numéro de notice : A2022-314 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.foreco.2022.120489 En ligne : https://doi.org/10.1016/j.foreco.2022.120489 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102250 [article]

Funding for planting missing species financially supports the conversion from pure even-aged to uneven-aged mixed forests and climate change mitigation / Joerg Roessinger in European Journal of Forest Research, vol 141 n° 3 (June 2022)  

Public [article]  inEuropean Journal of Forest Research > vol 141 n° 3 (June 2022) . - pp 517 - 534 Titre : Funding for planting missing species financially supports the conversion from pure even-aged to uneven-aged mixed forests and climate change mitigation Type de document : Article/Communication Auteurs : Joerg Roessinger, Auteur ; Ladislav Kulla, Auteur ; Vlastimil Murgaš, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 517 - 534 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] Carpates [Termes IGN] conversion forestière [Termes IGN] Fagus sylvatica [Termes IGN] forêt équienne [Termes IGN] forêt inéquienne [Termes IGN] modélisation de la forêt [Termes IGN] peuplement mélangé [Termes IGN] Picea abies [Termes IGN] plantation forestière [Termes IGN] politique de conservation (biodiversité) [Termes IGN] régénération (sylviculture) [Termes IGN] service écosystémique [Termes IGN] volume en bois [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Mountain spruce forests in Central Europe decline under storms and bark beetle calamities driven by climate change. A stabilisation by planting rare or missing tree species is expensive and requires funding. A funding policy should mitigate climate change and support biodiversity. The goal of this study was to identify a conversion strategy of even-aged spruce-dominated forest stands to uneven-aged mixed stands with spruce (Picea abies (L.) H.Karst.), beech (Fagus sylvatica L.), and fir (Abies alba Mill.). A simultaneous nonlinear optimisation of the number of planted trees and harvested trees per species and per period schedules stand treatments aiming to maximise the long-term financial outcome. Planting modelling extends a density-dependent stand-level matrix transition model based on diameter classes with an age-class-based model for artificial regeneration. An optimal conversion strategy was applied for five funding policy schemes, each for five initial states representing different stages of age and species composition typical for spruce forest conversion in the mountain zone of the Western Carpathians. Only 50% and higher funding of planting costs for the minor/missing fir and beech species facilitates a substantial increase of their shares in stand volume. Funding decreases the volume failure due to mortality. Funding increases the standing and harvested volume, which mitigates climate change by increasing the carbon sequestration. Funding causes unintended effects on ecosystem services by lowering harvest diameters, decreasing the volume of less profitable beech, and temporarily reducing the stand density aimed at supporting plantings and their diameter increments. Numéro de notice : A2022-418 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-022-01456-6 Date de publication en ligne : 07/05/2022 En ligne : https://doi.org/10.1007/s10342-022-01456-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100781 [article]

Green infrastructure planning through EO and GIS analysis: the canopy plan of Liège, Belgium, to mitigate its urban heat island / Benjamin Beaumont in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-4-2022 (2022 edition)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-4-2022 (2022 edition) . - pp 243 - 250 Titre : Green infrastructure planning through EO and GIS analysis: the canopy plan of Liège, Belgium, to mitigate its urban heat island Type de document : Article/Communication Auteurs : Benjamin Beaumont, Auteur ; Yasmina Loozen, Auteur ; Thibault Castin, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 243 - 250 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] arbre urbain [Termes IGN] ilot thermique urbain [Termes IGN] image aérienne [Termes IGN] Liège [Termes IGN] planification urbaine [Termes IGN] plantation forestière Résumé : (auteur) As a place to live, work and play, urban spaces are the nerve centers of human activity. The urban spaces, which are becoming increasingly extensive and dense, are particularly sensitive to the effects of climate change. Greening cities has been identified as one of the most effective ways to mitigate one of these effects, the urban heat island. In this context, the city of Liège, Belgium, has adopted a greening plan, called “Plan canopée”, to increase the tree canopy area at city level. The aim of this study is to present the methodology used to objectivize and prioritize the selection of potential planting sites. This research proposes the production of a series of spatial indicators allowing, on the one hand, the precise mapping of urban surfaces ready for planting, and on the other hand, the objective prioritization of city districts to be vegetated. The research integrates airborne image classification, urban heat island modeling and a series of reference geodata combinations. The set of data produced provides a transparent decision support tool to the authorities for the operational planning of tree plantations. These results contribute to the development of a planting strategy that maximizes the chances of ownership by the citizens, and consequently the sustainable and effective impact of the achievements. Numéro de notice : A2022-423 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-V-4-2022-243-2022 Date de publication en ligne : 18/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-4-2022-243-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100727 [article]

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]

Classification of Eucalyptus plantation Site Index (SI) and Mean Annual Increment (MAI) prediction using DEM-based geomorphometric and climatic variables in Brazil / Aliny Aparecida Dos Reis in Geocarto international, vol 37 n° 5 ([01/03/2022])  

Public [article]  inGeocarto international > vol 37 n° 5 [01/03/2022] . - pp 1256 - 1273 Titre : Classification of Eucalyptus plantation Site Index (SI) and Mean Annual Increment (MAI) prediction using DEM-based geomorphometric and climatic variables in Brazil Type de document : Article/Communication Auteurs : Aliny Aparecida Dos Reis, Auteur ; Steven E. Franklin, Auteur ; Fausto Weimar Acerbi Júnior, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1256 - 1273 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Brésil [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données météorologiques [Termes IGN] Eucalyptus (genre) [Termes IGN] géomorphométrie [Termes IGN] MNS SRTM [Termes IGN] plantation forestière [Termes IGN] rendement Résumé : (Auteur) Digital elevation model (DEM) data were used with climate data to estimate productivity in 19 Eucalyptus plantations in Minas Gerais state, Brazil. Typically, plantation and individual stand growth and productivity estimates, such as Site Index (SI) and Mean Annual Increment (MAI), are based on field measures of height, tree diameter and age. Using a Random Forest modelling approach, SI and MAI were related to: (i) DEM-based geomorphometric variables and (ii) WorldClim historical macro-climatic measures. Three operational SI classes (high, medium and low productivity) in 180 stands were mapped with an overall accuracy of 91.6%. Medium and high productivity sites were the most accurately classified. Low productivity sites had 76.5% producer’s accuracy and 92.9% user’s accuracy, and were the most extensive in the study area. Such sites are considered of high importance from a plantation management perspective since additional forestry operations are likely required to address low productivity and growth. Numéro de notice : A2022-275 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1778103 Date de publication en ligne : 19/06/2020 En ligne : https://doi.org/10.1080/10106049.2020.1778103 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100782 [article]

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