Centre dedocumentation
scientifique

Forest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics / Jakob Wernicke in Remote sensing of environment, vol 279 (15 September 2022)  

Public [article]  inRemote sensing of environment > vol 279 (15 September 2022) . - n° 113134 Titre : Forest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics Type de document : Article/Communication Auteurs : Jakob Wernicke, Auteur ; Christian Torsten Seltmann, Auteur ; Ralf Wenzel, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 113134 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Allemagne [Termes IGN] analyse comparative [Termes IGN] canopée [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] fusion d'images [Termes IGN] image Sentinel-MSI [Termes IGN] indice de végétation [Termes IGN] inventaire forestier étranger (données) [Termes IGN] semis de points [Termes IGN] stratification Résumé : (auteur) Knowledge about the forest canopy stratification is of essential importance for forest management and planning. Collecting structural information (e.g. natural regeneration) still depends on cost and labour intensive forest inventories with a coarse spatio-temporal resolution. Remote sensing partly overcomes these limitations and particularly active sensors of type light detection and ranging (LiDAR) have proven their great potential of separating forest strata. The applicability of LiDAR metrics for the differentiation of the spruce dominated forest strata in Central Germany has not been tested yet. Additionally, studying the potential of Sentinel-2 metrics for the classification of forest strata is lacking too. In this study, we investigated the capabilities of six different classification approaches for the differentiation of five forest strata that are typical for the study region. Reference data were derived from forest inventory measurements surveyed on a dense 200 × 200 m grid. The six classification approaches were trained with fused and un-fused LiDAR and Sentinel-2 inferred metrics. The classification results were compared using the overall mean accuracy, sensitivity and specificity via receivers operating characteristics of multi-class problems. We were interested in the classification abilities of Sentinel-2 metrics due to the obvious advantages of Sentinel-2 based metrics (free of charge, high spatio-temporal coverage). We assumed that the canopy structure determines the reflection on stand level and thus might facilitate the classification of different canopy strata. Beforehand, it was important to examine the influence of distinctly imbalanced and collinear reference data on the classification results. We found that the Random Forest classifier most accurately separated the five forest strata with a mean overall accuracy of 83.3% (Kappa = 76.2%). These values were achieved from balanced training data and the classification capability was confirmed by classification results from an independent test data set. Fused predictors of active (LiDAR) and passive (Sentinel-2) remote sensing revealed no substantial improvement in the classification accuracy due to the dominant role of LiDAR metrics. Herein, we identified that especially the height variability, top height, portion of LiDAR-returns between 2 m and 10 m and the standard deviation of the return number between the 25th and 50th height percentile, predominately contributed to the classification accuracy. Classification results purely based on Sentinel-2 metrics revealed a rather small overall mean accuracy of 54.7%. The metrics (e.g. median, variance, entropy) were derived from Sentinel-2 indices, covering the visible and near to short infrared spectrum. Variable importance computations unraveled a detectable but minor contribution of MSI, TCG, NDVI to the classification result. Finally, our data driven observations illustrated serious drawbacks associated to data imbalance, collinearity and autocorrelation and presented practical guidance to cope with these issues. Numéro de notice : A2022-510 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113134 Date de publication en ligne : 28/06/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113134 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101047 [article]

Direct and automatic measurements of stem curve and volume using a high-resolution airborne laser scanning system / Eric Hyyppä in Science of remote sensing, vol 5 (June 2022)  

Public [article]  inScience of remote sensing > vol 5 (June 2022) . - n° 100050 Titre : Direct and automatic measurements of stem curve and volume using a high-resolution airborne laser scanning system Type de document : Article/Communication Auteurs : Eric Hyyppä, Auteur ; Antero Kukko, Auteur ; Harri Kaartinen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 100050 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canopée [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] modèle de croissance végétale [Termes IGN] modèle numérique de terrain [Termes IGN] Picea abies [Termes IGN] semis de points [Termes IGN] volume en bois Résumé : (auteur) Today, high-quality reference tree measurements, including the position, diameter, height and volume, are cumbersome and slow to carry out, but highly needed for forest inventories based on airborne laser scanning. Mobile laser scanning technologies hold the promise for collecting reference data for forest inventories with an extremely high efficiency. Perhaps, the most efficient approach for reference data collection would be to mount a high-resolution laser scanning system on board an airborne vehicle flying at a low altitude above the forest canopy since this would allow recording reference samples of individual trees with the speed of flight. To demonstrate the potential of this technology, we mounted an in-house developed HeliALS-DW laser scanning system on board a helicopter and collected point cloud data in a boreal forest on three test sites containing a total of 1469 trees. The obtained point clouds incorporated sufficiently many high-quality stem hits for estimating the stem curves and stem volumes of individual trees since the point clouds had a relatively high point density of 2200–3800 echoes/m2, and the scanner had been tilted by 15° from the nadir to increase the possibility of recording stem hits. To automatically estimate the diameters at breast height (DBH) and stem curves of individual trees, we used algorithms designed to tolerate moderate drifts in the trajectory of the laser scanner. Furthermore, the stem volumes of individual trees were computed by using the estimated stem curves and tree heights without any allometric models. Using the proposed methods, we were able to estimate the stem curves with a root-mean-square error (RMSE) of 1.7–2.6 cm (6–9%) while detecting 42–71% of the trees. The RMSE of stem volume estimates was 0.1–0.15 m3 (12–21%). We also showed that the tree detection rate could be improved up to 87–96% for trees with a DBH exceeding 20 cm if slightly larger average errors for the stem attributes were allowed. Our results pave the way for using high-resolution airborne laser scanning for field reference data collection by conducting direct measurements of tree stems with a high efficiency. Numéro de notice : A2022-298 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.srs.2022.100050 Date de publication en ligne : 09/04/2022 En ligne : https://doi.org/10.1016/j.srs.2022.100050 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100464 [article]

A voxel-based method for the three-dimensional modelling of heathland from lidar point clouds: first results / N. Homainejad in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-3-2022 (2022 edition) . - pp 697 - 704 Titre : A voxel-based method for the three-dimensional modelling of heathland from lidar point clouds: first results Type de document : Article/Communication Auteurs : N. Homainejad, Auteur ; Sisi Zlatanova, Auteur ; Norbert Pfeifer, Auteur Année de publication : 2022 Article en page(s) : pp 697 - 704 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] canopée [Termes IGN] classification par nuées dynamiques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] incendie de forêt [Termes IGN] lande [Termes IGN] modélisation 3D [Termes IGN] Nouvelle-Galles du Sud [Termes IGN] segmentation en régions [Termes IGN] semis de points [Termes IGN] voxel Résumé : (auteur) Bushfires are an intrinsic part of the New South Wales’ (NSW) environment in Australia, especially in the Blue Mountains region (11400km2), that is dominated by fire prone vegetation that includes heathland. Many of the Australian native plants in this region are fire-prone and combustible, and many species even require fire to regenerate. The classification of the lateral and vertical distribution of living vegetation is necessary to manage the complexity of bushfires. Currently, interpretation of aerial and satellite images is the prevalent method for the classification of vegetation in NSW. The result does not represent important vegetation structural attributes, such as vegetation height, subcanopy height, and destiny. This paper presents an automated method for the three-dimensional modelling of heathland and important heathland parameters, such as heath shrub height and continuity, and sparse tree and mallee height and density in support of bushfire behaviour modelling. For this study airborne lidar point clouds with a density of 120 points per square meter are used. For the processing and modelling the study is divided into a point cloud processing phase and a voxel-based modelling phase. The point cloud processing phase consists of the normalisation of the height and extraction of the above ground vegetation, while the voxel phase consists of seeded region growing for segmentation, and K-means clustering for the classification of the vegetation into three different canopy layers: a) heath shrubs, b) sparse trees and mallee, c) tall trees. Numéro de notice : A2022-436 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.5194/isprs-annals-V-3-2022-697-2022 Date de publication en ligne : 17/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-3-2022-697-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100783 [article]

Drought impacts in forest canopy and deciduous tree saplings in Central European forests / Mirela Beloiu in Forest ecology and management, vol 509 (1 April 2022)  

Public [article]  inForest ecology and management > vol 509 (1 April 2022) . - n° 120075 Titre : Drought impacts in forest canopy and deciduous tree saplings in Central European forests Type de document : Article/Communication Auteurs : Mirela Beloiu, Auteur ; Reinhold Stahlmann, Auteur ; Carl Beierkuhnlein, Auteur Année de publication : 2022 Article en page(s) : n° 120075 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Bavière (Allemagne) [Termes IGN] bois mort [Termes IGN] canopée [Termes IGN] dendrométrie [Termes IGN] données de terrain [Termes IGN] écosystème forestier [Termes IGN] jeune arbre [Termes IGN] mortalité [Termes IGN] peuplement mélangé [Termes IGN] phénomène climatique extrême [Termes IGN] Pinophyta [Termes IGN] régénération (sylviculture) [Termes IGN] résilience écologique [Termes IGN] sécheresse [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Forests worldwide are increasingly exposed to extreme weather events. Drought deteriorates the health, structure, and functioning of forests, which can lead to reduced diversity, decreased productivity, and increased tree mortality. Therefore, it is an urgent need to assess the impact of drought on tree species. Due to differences in tree physiology, saplings and mature trees are likely to respond specifically to drought conditions. In contrast to mature trees, little is known about the response of saplings to drought. Here, we combine in-situ field measurements for saplings of deciduous tree species with remote sensing for forest canopy to assess drought damage, recovery, and sapling mortality patterns during a centennial drought (2018, 2019) and beyond (2020). We measured 2051 saplings out of 214 plots in Central Germany. Forest canopy health was assessed using 10 × 10 m resolution satellite observations for the same locations. We (1) demonstrate that forest canopy exhibits long-lasting drought-induced effects, (2) show that saplings have a remarkable capacity to recover from drought and survive a subsequent drought, (3) demonstrate that reduced sapling recovery leads to their mortality, (4) reveal that drought damage on saplings increases from pioneer to non-pioneer species, and mortality is ranking from Sorbus aucuparia > Sambucus nigra > Fraxinus excelsior, Acer campestre, Frangula alnus > Ulmus glabra > Carpinus betulus > Betula pendula, Fagus sylvatica > Acer pseudoplatanus > Quercus petraea > Corylus avellana, Crataegus spp., > Prunus avium, Quercus robur; and (5) link drought response to site conditions, indicating that species diversity and winter precipitation as relevant indicators of tree health. If periods of drought become more frequent, as expected, this could negatively impact mid-term forest recovery, alter long-term tree species assemblages and reduce biodiversity and functional resilience of forest ecosystems. We suggest that models of forest response to drought should differentiate between the forest canopy and understory and also consider species-specific responses as we found a broad spectrum of responses within the same plant functional type of deciduous tree species in terms of drought damage and recovery. Numéro de notice : A2022-191 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2022.120075 Date de publication en ligne : 12/02/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120075 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99947 [article]

Estimation and testing of linkages between forest structure and rainfall interception characteristics of a Robinia pseudoacacia plantation on China’s Loess Plateau / Changkun Ma in Journal of Forestry Research, vol 33 n° 2 (April 2022)  

Public [article]  inJournal of Forestry Research > vol 33 n° 2 (April 2022) . - pp 529 - 542 Titre : Estimation and testing of linkages between forest structure and rainfall interception characteristics of a Robinia pseudoacacia plantation on China’s Loess Plateau Type de document : Article/Communication Auteurs : Changkun Ma, Auteur ; Yi Luo, Auteur ; Mingan Shao, Auteur ; Xiaoxu Jia, Auteur Année de publication : 2022 Article en page(s) : pp 529 - 542 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] canopée [Termes IGN] capacité de stockage [Termes IGN] Chine [Termes IGN] pluie [Termes IGN] régression multiple [Termes IGN] Robinia pseudoacacia [Termes IGN] structure d'un peuplement forestier [Termes IGN] zone semi-aride [Vedettes matières IGN] Foresterie Mots-clés libres : Rainfall interception loss Résumé : (auteur) Understanding the interaction between canopy structure and the parameters of interception loss is essential in predicting the variations in partitioning rainfall and water resources as affected by changes in canopy structure and in implementing water-based management in semiarid forest plantations. In this study, seasonal variations in rainfall interception loss and canopy storage capacity as driven by canopy structure were predicted and the linkages were tested using seasonal filed measurements. The study was conducted in nine 50 m × 50 m Robinia pseudoacacia plots in the semiarid region of China’s Loess Plateau. Gross rainfall, throughfall and stemflow were measured in seasons with and without leaves in 2015 and 2016. Results show that measured average interception loss for the nine plots were 17.9% and 9.4% of gross rainfall during periods with leaves (the growing season) and without leaves, respectively. Average canopy storage capacity estimated using an indirect method was 1.3 mm in the growing season and 0.2 mm in the leafless season. Correlations of relative interception loss and canopy storage capacity to canopy variables were highest for leaf/wood area index (LAI/WAI) and canopy cover, followed by bark area, basal area, tree height and stand density. Combined canopy cover, leaf/wood area index and bark area multiple regression models of interception loss and canopy storage capacity were established for the growing season and in the leafless season in 2015. It explained 97% and 96% of the variations in relative interception loss during seasons with and without leaves, respectively. It also explained 98% and 99% of the variations in canopy storage capacity during seasons with and without leaves, respectively. The empirical regression models were validated using field data collected in 2016. The models satisfactorily predicted relative interception loss and canopy storage capacity during seasons with and without leaves. This study provides greater understanding about the effects of changes in tree canopy structure (e.g., dieback or mortality) on hydrological processes. Numéro de notice : A2022-334 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s11676-021-01324-w Date de publication en ligne : 06/06/2021 En ligne : https://doi.org/10.1007/s11676-021-01324-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100668 [article]

Are northern German Scots pine plantations climate smart? The impact of large-scale conifer planting on climate, soil and the water cycle / Christoph Leuschner in Forest ecology and management, vol 507 (1 March 2022)  

Permalink

Ultrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach / Linyuan Li in International journal of applied Earth observation and geoinformation, vol 107 (March 2022)  

Permalink

Scorch height and volume modeling in prescribed fires: Effects of canopy gaps in Pinus pinaster stands in Southern Europe / J.R. Molina in Forest ecology and management, vol 506 (15 February 2022)  

Permalink

Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data / Tianyu Hu in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)  

Permalink

Forest floor alteration by canopy trees and soil wetness drive regeneration of a spruce-beech forest / Pavel Daněk in Forest ecology and management, vol 504 (15 January 2022)  

Permalink

Examining the integration of Landsat operational land imager with Sentinel-1 and vegetation indices in mapping southern yellow pines (Loblolly, Shortleaf, and Virginia pines) / Clement E. Akumu in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 1 (January 2022)  

Permalink

Investigating the role of wind disturbance in tropical forests through a forest dynamics model and satellite observations / E-Ping Rau (2022)  

Permalink

Monitoring leaf phenology in moist tropical forests by applying a superpixel-based deep learning method to time-series images of tree canopies / Guangqin Song in ISPRS Journal of photogrammetry and remote sensing, vol 183 (January 2022)  

Permalink

Multi-layer modeling of dense vegetation from aerial LiDAR scans / Ekaterina Kalinicheva (2022)  

Permalink

Assessing the agreement of ICESat-2 terrain and canopy height with airborne lidar over US ecozones / Lonesome Malambo in Remote sensing of environment, vol 266 (December 2021)  

Permalink