Centre dedocumentation
scientifique

Unsupervised semantic and instance segmentation of forest point clouds / Di Wang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 165 (July 2020) . - pp 86 - 97 Titre : Unsupervised semantic and instance segmentation of forest point clouds Type de document : Article/Communication Auteurs : Di Wang, Auteur Année de publication : 2020 Article en page(s) : pp 86 - 97 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] classification non dirigée [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] étiquetage sémantique [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] houppier [Termes descripteurs IGN] indice foliaire [Termes descripteurs IGN] interprétation automatique [Termes descripteurs IGN] segmentation sémantique [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] télémètre laser terrestre Résumé : (auteur) Terrestrial Laser Scanning (TLS) has been increasingly used in forestry applications including forest inventory and plant ecology. Tree biophysical properties such as leaf area distributions and wood volumes can be accurately estimated from TLS point clouds. In these applications, a prerequisite is to properly understand the information content of large scale point clouds (i.e., semantic labelling of point clouds), so that tree-scale attributes can be retrieved. Currently, this requirement is undergoing laborious and time consuming manual works. In this work, we jointly address the problems of semantic and instance segmentation of forest point clouds. Specifically, we propose an unsupervised pipeline based on a structure called superpoint graph, to simultaneously perform two tasks: single tree isolation and leaf-wood classification. The proposed method is free from restricted assumptions of forest types. Validation using simulated data resulted in a mean Intersection over Union (mIoU) of 0.81 for single tree isolation, and an overall accuracy of 87.7% for leaf-wood classification. The single tree isolation led to a relative root mean square error (RMSE%) of 2.9% and 19.8% for tree height and crown diameter estimations, respectively. Comparisons with existing methods on other benchmark datasets showed state-of-the-art results of our method on both single tree isolation and leaf-wood classification tasks. We provide the entire framework as an open-source tool with an end-user interface. This study closes the gap for using TLS point clouds to quantify tree-scale properties in large areas, where automatic interpretation of the information content of TLS point clouds remains a crucial challenge. Numéro de notice : A2020-347 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.020 date de publication en ligne : 28/05/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.020 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95228 [article]

Evaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada / Wushuang Li in Forest ecology and management, Vol 466 (15 June 2020)  

Public [article]  inForest ecology and management > Vol 466 (15 June 2020) Titre : Evaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada Type de document : Article/Communication Auteurs : Wushuang Li, Auteur ; John A. Kershaw, Auteur ; Kara K. L. Costanza, Auteur ; Anthony R. Taylor, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] azote [Termes descripteurs IGN] Canada [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] Picea rubens [Termes descripteurs IGN] température de l'air [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Numéro de notice : A2020-407 Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118139 date de publication en ligne : 20/04/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118139 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95464 [article]

Using machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests / Jiaxin Chen in Forest ecology and management, Vol 466 (15 June 2020)  

Public [article]  inForest ecology and management > Vol 466 (15 June 2020) Titre : Using machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests Type de document : Article/Communication Auteurs : Jiaxin Chen, Auteur ; Hongqiang Yang, Auteur ; Rongzhou Man, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] Canada [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] données environnementales [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] gestion forestière durable [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] surveillance forestière Résumé : (auteur) Sustainable forest management requires the ability to accurately model forest dynamics under a changing environment, which is difficult using conventional statistical methods as many factors that interactively affect forest growth must be considered. As well, statistical model development is often limited by the lack of broad-scale repeated forest measurements needed to capture changes in 1 or more variables and the corresponding changes in forest dynamics (e.g., growth in diameter and height), while assuming other variables do not change, or their changes do not significantly affect the forest dynamics of interest. In many forested countries, comprehensive monitoring programs have amassed large amounts of diverse forest measurement data. Here we propose a new approach for using artificial neural network-based machine learning to synthesize spatiotemporal tree measurement data collected over a vast area of boreal forest in central Canada to model diameter at breast height (DBH)-height and DBH-height-age relationships for 6 dominant tree species. More than 30 potentially important stand structure, site, and climate variables were considered. We used an individual-based modelling approach by considering each individual tree measurement as an instance of the complex relationships modelled; together, broad-scale long-term monitoring data contain many such instances, representing considerable spatial and temporal scale variation in forest growth and growing conditions. Using this approach, we significantly improved DBH-height and DBH-height-age models. And the models developed allowed us to analyze the effects of environmental conditions or changes in these conditions on forest growth. This may be the first attempt at applying this type of approach, which can be used to more accurately model, for example, forest growth, mortality, and how they are affected by changing climate in a variety of forest types. Numéro de notice : A2020-406 Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2020.118104 date de publication en ligne : 04/04/2020 En ligne : https://doi.org/10.1016/j.foreco.2020.118104 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95463 [article]

Under-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 41 - 60 Titre : Under-canopy UAV laser scanning for accurate forest field measurements Type de document : Article/Communication Auteurs : Eric Hyyppä, Auteur ; Juha Hyyppä, Auteur ; Teemu Hakala, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 41 - 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] balayage laser [Termes descripteurs IGN] canopée [Termes descripteurs IGN] densité du bois [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] erreur moyenne quadratique [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] hauteur à la base du houppier [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] inventaire forestier local [Termes descripteurs IGN] modèle de croissance [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] Simultaneous Localisation And Mapping [Termes descripteurs IGN] télédétection aérienne [Termes descripteurs IGN] télémètre laser terrestre [Termes descripteurs IGN] télémétrie laser aéroporté [Termes descripteurs IGN] tronc Résumé : (auteur) Surveying and robotic technologies are converging, offering great potential for robotic-assisted data collection and support for labour intensive surveying activities. From a forest monitoring perspective, there are several technological and operational aspects to address concerning under-canopy flying unmanned airborne vehicles (UAV). To demonstrate this emerging technology, we investigated tree detection and stem curve estimation using laser scanning data obtained with an under-canopy flying UAV. To this end, we mounted a Kaarta Stencil-1 laser scanner with an integrated simultaneous localization and mapping (SLAM) system on board an UAV that was manually piloted with the help of video goggles receiving a live video feed from the onboard camera of the UAV. Using the under-canopy flying UAV, we collected SLAM-corrected point cloud data in a boreal forest on two 32 m 32 m test sites that were characterized as sparse ( = 42 trees) and obstructed ( = 43 trees), respectively. Novel data processing algorithms were applied for the point clouds in order to detect the stems of individual trees and to extract their stem curves and diameters at breast height (DBH). The estimated tree attributes were compared against highly accurate field reference data that was acquired semi-manually with a multi-scan terrestrial laser scanner (TLS). The proposed method succeeded in detecting 93% of the stems in the sparse plot and 84% of the stems in the obstructed plot. In the sparse plot, the DBH and stem curve estimates had a root-mean-squared error (RMSE) of 0.60 cm (2.2%) and 1.2 cm (5.0%), respectively, whereas the corresponding values for the obstructed plot were 0.92 cm (3.1%) and 1.4 cm (5.2%). By combining the stem curves extracted from the under-canopy UAV laser scanning data with tree heights derived from above-canopy UAV laser scanning data, we computed stem volumes for the detected trees with a relative RMSE of 10.1% in both plots. Thus, the combination of under-canopy and above-canopy UAV laser scanning allowed us to extract the stem volumes with an accuracy comparable to the past best studies based on TLS in boreal forest conditions. Since the stems of several spruces located on the test sites suffered from severe occlusion and could not be detected with the stem-based method, we developed a separate work flow capable of detecting trees with occluded stems. The proposed work flow enabled us to detect 98% of trees in the sparse plot and 93% of the trees in the obstructed plot with a 100% correction level in both plots. A key benefit provided by the under-canopy UAV laser scanner is the short period of time required for data collection, currently demonstrated to be much faster than the time required for field measurements and TLS. The quality of the measurements acquired with the under-canopy flying UAV combined with the demonstrated efficiency indicates operational potential for supporting fast and accurate forest resource inventories. Numéro de notice : A2020-240 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.021 date de publication en ligne : 11/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94994 [article]

Réservation

Réserver ce document

Exemplaires (3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2020061	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2020063	DEP-RECP	Revue	MATIS	Dépôt en unité	Exclu du prêt
081-2020062	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Warming effects on morphological and physiological performances of four subtropical montane tree species Authors Authors and affiliations / Yiyong Li in Annals of Forest Science [en ligne], Vol 77 n° 1 (March 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 77 n° 1 (March 2020) . - 11 p. Titre : Warming effects on morphological and physiological performances of four subtropical montane tree species Authors Authors and affiliations Type de document : Article/Communication Auteurs : Yiyong Li, Auteur ; Yue Xu, Auteur ; Ting Wu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] diagnostic foliaire [Termes descripteurs IGN] effet thermique [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] montagne [Termes descripteurs IGN] morphologie [Termes descripteurs IGN] photosynthèse [Termes descripteurs IGN] stress hydrique [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Key message: In a downward transplantation experiment, warming stimulated growth and photosynthesis of Schima superba Gardn. et Champ., Syzygium rehderianum Merr. et Perry and Itea chinensis Hook. et Arn. via increased stomatal conductance. Warming had no effect on growth of Machilus breviflora (Benth.) Hemsl., indicating species-specific differences in response to warming. Context: Climate change has been shown to shift species composition and community structure in subtropical forests. Thus, understanding the species-specific responses of growth and physiological processes to warming is essential. Aims: To investigate how climate warming affects growth, morphological and physiological performance of co-occurring tree species when they are growing at different altitudes. Methods: Soils and 1-year-old seedlings of four subtropical co-occurring tree species (Schima superba Gardn. et Champ., Syzygium rehderianum Merr. et Perry, Itea chinensis Hook. et Arn. and Machilus breviflora (Benth.) Hemsl.) were transplanted to three altitudes (600 m, 300 m and 30 m a.s.l.), inducing an effective warming of 1.0 °C and 1.5 °C. Growth, morphological, and physiological performances of these seedlings were monitored. Results: When exposed to warmer conditions, aboveground growth of the four species except M. breviflora was strongly promoted, accompanied by increased light-saturated photosynthetic rate and stomatal conductance. Warming also significantly increased concentrations of non-structural carbohydrates in leaves of S. rehderianum and M. breviflora, stems of S. superba and S. rehderianum, and roots of I. chinensis. However, we did not detect any effect of warming on stomatal length and stomatal density. Conclusion: Our results provide evidence that climate warming could have species-specific impacts on co-occurring tree species, which might subsequently shift species composition and forest structure. Numéro de notice : A2020-037 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0910-3 date de publication en ligne : 10/01/2020 En ligne : https://doi.org/10.1007/s13595-019-0910-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94491 [article]

Applications of photogrammetry for environmental research / Francesco Mancini (2020)  

Permalink

Potential of UAV photogrammetry for characterization of forest canopy structure in uneven-aged mixed conifer–broadleaf forests / Sadeepa Jayathunga in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)  

Permalink

Spatiotemporal variation in the relationship between boreal forest productivity proxies and climate data / Clémentine Ols in Dendrochronologia, vol 58 (December 2019)  

Permalink

Estimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry / Juliana Batistoti in Remote sensing, Vol 11 n° 20 (October 2019)  

Permalink

The utility of terrestrial photogrammetry for assessment of tree volume and taper in boreal mixedwood forests / Christopher Mulverhill in Annals of Forest Science [en ligne], Vol 76 n° 3 (September 2019)  

Permalink

A general method for the classification of forest stands using species composition and vertical and horizontal structure / Miquel de Cáceres in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

Permalink

RegisTree: a registration algorithm to enhance forest inventory plot georeferencing / Maryem Fadili in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

Permalink

Bayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory / Francesco Minunno in Forest ecology and management, vol 440 (15 May 2019)  

Permalink

Estimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery / Yanan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)  

Permalink

Estimation of aboveground biomass and carbon in a tropical rain forest in Gabon using remote sensing and GPS data / Kalifa Goïta in Geocarto international, vol 34 n° 3 ([01/03/2019])  

Permalink