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Termes descripteurs IGN > 1- Outils - instruments et méthodes > Instrument > instrument de mesure > instrument de mesurage de distances > télémètre > distancemètre > télémètre laser > télémètre laser à balayage
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Stereophotogrammetry for 2-D building deformation monitoring using Kalman Filter / J.O. Odumosu in Reports on geodesy and geoinformatics, vol 110 n°1 (December 2020)
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Titre : Stereophotogrammetry for 2-D building deformation monitoring using Kalman Filter Type de document : Article/Communication Auteurs : J.O. Odumosu, Auteur ; V.C. Nnam, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1 - 7 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre
[Termes descripteurs IGN] corrélation croisée normalisée
[Termes descripteurs IGN] déformation d'édifice
[Termes descripteurs IGN] filtre de Kalman
[Termes descripteurs IGN] Matlab
[Termes descripteurs IGN] modèle stéréoscopique
[Termes descripteurs IGN] Nigéria
[Termes descripteurs IGN] point d'appui
[Termes descripteurs IGN] surveillance d'ouvrage
[Termes descripteurs IGN] télémètre laser terrestre
[Termes descripteurs IGN] transformation polynomialeRésumé : (auteur) Stereo photogrammetry has been used in this study to analyse and detect movements within the Lecture theater of School of Environmental Technology of Federal University of Technology Minna via the use of Kalman filter algorithm. The essential steps for implementation of this method are herein highlighted and results obtained indicate Ins. Mov.s (velocity) ranging from ±0.0000001 m/epoch to ±0.000007 m/epoch with greater movements noticed in the horizontal direction than in the vertical direction of the building. Because the observed movements were insignificant, the building has been classified as stable. However, a longer period of observation with a bi-monthly observational interval has been recommended to enable decision on the rate of rise/sink and deformation of the building. Numéro de notice : A2020-785 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.2478/rgg-2020-0006 date de publication en ligne : 07/08/2020 En ligne : https://doi.org/10.2478/rgg-2020-0006 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96530
in Reports on geodesy and geoinformatics > vol 110 n°1 (December 2020) . - pp 1 - 7[article]Evaluating the accuracy of ALS-based removal estimates against actual logging data / Ville Vähä-Konka in Annals of Forest Science [en ligne], vol 77 n° 3 (September 2020)
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Titre : Evaluating the accuracy of ALS-based removal estimates against actual logging data Type de document : Article/Communication Auteurs : Ville Vähä-Konka, Auteur ; Matti Maltamo, Auteur ; Timo Pukkala, Auteur ; Kalle Kärhä, Auteur Année de publication : 2020 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes descripteurs IGN] éclaircie (sylviculture)
[Termes descripteurs IGN] fiabilité des données
[Termes descripteurs IGN] Finlande
[Termes descripteurs IGN] gestion forestière
[Termes descripteurs IGN] inventaire forestier étranger (données)
[Termes descripteurs IGN] récolte de bois
[Termes descripteurs IGN] télédétection par lidar
[Termes descripteurs IGN] télémètre laser aéroporté
[Termes descripteurs IGN] volume en boisRésumé : (auteur) Key message: We examined the accuracy of the stand attribute data based on airborne laser scanning (ALS) provided by the Finnish Forest Centre. The precision of forest inventory data was compared for the first time with operative logging data measured by the harvester.
Context: Airborne laser scanning (ALS) is increasingly used together with models to predict the stand attributes of boreal forests. The information is updated by growth models. Information produced by remote sensing, model prediction, and growth simulation needs field verification. The data collected by harvesters on logging sites provide a means to evaluate and verify the accuracy of the ALS-based data.
Aims: This study investigated the accuracy of ALS-based forest inventory data provided by the Finnish Forest Centre at the stand level, using harvester data as the reference. Special interest was on timber assortment volumes where the quality reductions of sawlog are model predictions in ALS-based data and true realized reductions in the logging data.
Methods: We examined the accuracy of total volume and timber assortment volumes by comparing ALS-based data and operative logging data measured by a harvester. This was done both for clear cuttings and thinning sites. Accuracy of the identification of the dominant tree species of the stand was examined using the Kappa coefficient.
Results: In clear-felling sites, the total harvest removals based on ALS and model prediction had a RMSE% of 26.0%. In thinning, the corresponding difference in the total harvested removal was 42.4%. Compared to logged volume, ALS-based prediction overestimated sawlog removals in clear cuttings and underestimated pulpwood removals.
Conclusion: The study provided valuable information on the accuracy of ALS-based stand attribute data. Our results showed that ALS-based data need better methods to predict the technical quality of harvested trees, to avoid systematic overestimates of sawlog volume. We also found that the ALS-based estimates do not accurately predict the volume of trees removed in actual thinnings.Numéro de notice : A2020-592 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00985-7 date de publication en ligne : 27/08/2020 En ligne : https://doi.org/10.1007/s13595-020-00985-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95927
in Annals of Forest Science [en ligne] > vol 77 n° 3 (September 2020) . - 11 p.[article]Unsupervised semantic and instance segmentation of forest point clouds / Di Wang in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)
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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 terrestreRésumé : (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 Affiliation des auteurs : non IGN 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
in ISPRS Journal of photogrammetry and remote sensing > vol 165 (July 2020) . - pp 86 - 97[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2020071 SL Revue Centre de documentation Revues en salle Disponible 081-2020073 DEP-RECP Revue MATIS Dépôt en unité Exclu du prêt 081-2020072 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Monitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series / Gherardo Chirici in Annals of Forest Science [en ligne], Vol 77 n° 2 (June 2020)
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Titre : Monitoring clearcutting and subsequent rapid recovery in Mediterranean coppice forests with Landsat time series Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Francesca Giannetti, Auteur ; Erica Mazza, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] brûlis
[Termes descripteurs IGN] canopée
[Termes descripteurs IGN] coupe rase (sylviculture)
[Termes descripteurs IGN] dégradation du signal
[Termes descripteurs IGN] forêt méditerranéenne
[Termes descripteurs IGN] image Landsat
[Termes descripteurs IGN] Normalized Difference Vegetation Index
[Termes descripteurs IGN] reconstruction du signal
[Termes descripteurs IGN] régénération (sylviculture)
[Termes descripteurs IGN] série temporelle
[Termes descripteurs IGN] taillis
[Termes descripteurs IGN] télémètre laser aéroportéRésumé : (auteur) Key message: This work analyses the rate of recovery of the spectral signal from clearcut areas of coppice Mediterranean forests using Landsat Time Series (LTS). The analysis revealed a more rapid rate of spectral signal recovery than what was found in previous investigations in boreal and temperate forests. Context: The rate of post-disturbance vegetation recovery is an important component of forest dynamics. Aims: In this study, we analyze the recovery of the spectral signal from forest clearcut areas in Mediterranean conditions when the coppice system of forest management is applied. Methods:
We used LTS surface reflectance data (1999–2015). We generated an annual reference database of clearcuts using visual interpretation and local forest inventory data, and then derived the Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR) spectral trajectories for these clearcuts. From these spectral trajectories, we calculated the Years to Recovery or Y2R, the number of years it takes for a pixel to return to within a specified threshold (i.e., 70%, 80%, 90%, 100%) of its pre-disturbance value. Spectral recovery rates were then corroborated using measures of canopy height derived from airborne laser scanning (ALS) data. Results: The coppice system is associated with rapid recovery rates when compared to rates of recovery from seeds or seedlings in temperate and boreal forest conditions. We found that the Y2R derived from the spectral trajectories of post-clearcut NBR and NDVI provided similar characterizations of rapid recovery for the coppice system of forest management applied in our study area. The ALS measures of canopy height indicated that the Y2R metric accurately captured the rapid regeneration of coppice systems. Conclusion: The rapid rate of spectral recovery associated with the coppice system is 2–4 years, which contrasts with values reported in boreal and temperate forest environments, where spectral recovery was attained in approximately 10 years. NBR is an effective index for assessing rapid recovery in this forest system.Numéro de notice : A2020-293 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00936-2 date de publication en ligne : 15/04/2020 En ligne : https://doi.org/10.1007/s13595-020-00936-2 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95123
in Annals of Forest Science [en ligne] > Vol 77 n° 2 (June 2020)[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)
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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] Cartographie et localisation simultanées
[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 captée par drone
[Termes descripteurs IGN] inventaire forestier local
[Termes descripteurs IGN] modèle de croissance
[Termes descripteurs IGN] semis de points
[Termes descripteurs IGN] télédétection aérienne
[Termes descripteurs IGN] télémètre laser terrestre
[Termes descripteurs IGN] télémétrie laser aéroporté
[Termes descripteurs IGN] troncRésumé : (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 Affiliation des auteurs : non IGN 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
in ISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 41 - 60[article]Réservation
Réserver ce documentExemplaires (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 How far can we trust forestry estimates from low-density LiDAR acquisitions? The Cutfoot Sioux experimental forest (MN, USA) case study / Enrico Borgogno Mondino in International Journal of Remote Sensing IJRS, vol 41 n°12 (20 - 30 March 2020)
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PermalinkEmpirical stochastic model of detected target centroids: Influence on registration and calibration of terrestrial laser scanners / Tomislav Medic in Journal of applied geodesy, vol 13 n° 3 (July 2019)
PermalinkMise en place d’un système sondeur multifaisceaux dans une embarcation légère semi-rigide pour campagne de mesure bathymétrique et couplage avec un scanner terrestre, GNSS et INS / Alexandre Girard (2019)
PermalinkMethods for quantification of systematic distance deviations under incidence angle with scanning total stations / Miriam Zámečníková in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)
PermalinkComparing nearest neighbor configurations in the prediction of species-specific diameter distributions / Janne Raty in Annals of Forest Science [en ligne], vol 75 n° 1 (March 2018)
PermalinkEvaluation of the range accuracy and the radiometric calibration of multiple terrestrial laser scanning instruments for data interoperability / Kim Calders in IEEE Transactions on geoscience and remote sensing, vol 55 n° 5 (May 2017)
PermalinkMise en place de l’utilisation d’instruments de mesure 3D dans le cadre d’auscultations de barrages / Cyril Cadiou (2017)
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