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Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation / Kathrin Maier in ISPRS Journal of photogrammetry and remote sensing, vol 186 (April 2022)
[article]
Titre : Direct photogrammetry with multispectral imagery for UAV-based snow depth estimation Type de document : Article/Communication Auteurs : Kathrin Maier, Auteur ; Andrea Nascetti, Auteur ; Ward van Pelt, Auteur ; Gunhild Rosqvist, Auteur Année de publication : 2022 Article en page(s) : pp 1 - 18 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] bande infrarouge
[Termes IGN] épaisseur
[Termes IGN] erreur moyenne quadratique
[Termes IGN] géoréférencement direct
[Termes IGN] image captée par drone
[Termes IGN] image multibande
[Termes IGN] manteau neigeux
[Termes IGN] modèle numérique de surface
[Termes IGN] photogrammétrie aérienne
[Termes IGN] positionnement cinématique en temps réel
[Termes IGN] qualité du modèle
[Termes IGN] reconstruction 3D
[Termes IGN] structure-from-motion
[Termes IGN] SuèdeRésumé : (Auteur) More accurate snow quality predictions are needed to economically and socially support communities in a changing Arctic environment. This contrasts with the current availability of affordable and efficient snow monitoring methods. In this study, a novel approach is presented to determine spatial snow depth distribution in challenging alpine terrain that was tested during a field campaign performed in the Tarfala valley, Kebnekaise mountains, northern Sweden, in April 2019. The combination of a multispectral camera and an Unmanned Aerial Vehicle (UAV) was used to derive three-dimensional (3D) snow surface models via Structure from Motion (SfM) with direct georeferencing. The main advantage over conventional photogrammetric surveys is the utilization of accurate Real-Time Kinematic (RTK) positioning which enables direct georeferencing of the images, and therefore eliminates the need for ground control points. The proposed method is capable of producing high-resolution 3D snow-covered surface models (7 cm/pixel) of alpine areas up to eight hectares in a fast, reliable and affordable way. The test sites’ average snow depth was 160 cm with an average standard deviation of 78 cm. The overall Root-Mean-Square Errors (RMSE) of the snow depth range from 11.52 cm for data acquired in ideal surveying conditions to 41.03 cm in aggravated light and wind conditions. Results of this study suggest that the red components in the electromagnetic spectrum, i.e., the red, red edge, and near-infrared (NIR) band, contain the majority of information used in photogrammetric processing. The experiments highlighted a significant influence of the multi-spectral imagery on the quality of the final snow depth estimation as well as a strong potential to reduce processing times and computational resources by limiting the dimensionality of the imagery through the application of a Principal Component Analysis (PCA) before the photogrammetric 3D reconstruction. The proposed method is part of closing the scale gap between discrete point measurements and regional-scale remote sensing and complements large-scale remote sensing data and snow model output with an adequate validation source. Numéro de notice : A2022-066 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.01.020 Date de publication en ligne : 09/02/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.01.020 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99783
in ISPRS Journal of photogrammetry and remote sensing > vol 186 (April 2022) . - pp 1 - 18[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2022041 SL Revue Centre de documentation Revues en salle Disponible 081-2022043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2022042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Radar measurements of snow depth over sea ice on an unmanned aerial vehicle / Adrian Eng-Choon Tan in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 3 (March 2021)
[article]
Titre : Radar measurements of snow depth over sea ice on an unmanned aerial vehicle Type de document : Article/Communication Auteurs : Adrian Eng-Choon Tan, Auteur ; Josh McCulloch, Auteur ; Wolfgang Rack, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1868 - 1875 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Austral (océan)
[Termes IGN] épaisseur
[Termes IGN] glace de mer
[Termes IGN] image captée par drone
[Termes IGN] image radar
[Termes IGN] manteau neigeux
[Termes IGN] précision centimétrique
[Termes IGN] rapport signal sur bruit
[Termes IGN] variation saisonnièreRésumé : (Auteur) We propose a lightweight radar that autonomously measures snow depth over sea ice from an unmanned aerial vehicle (UAV). Development of this snow radar and its integration with an octocopter UAV is presented. Field trials of the UAV-mounted snow radar, conducted in Antarctica during the summer season of 2017/2018, are also described. The radar allows measurements of snow depths on sea ice between 10 and 100 cm. Additional reflections due to internal layers within the snow are evident at a few measurement points. The snow radar is evaluated for various flight parameters: stationary; flying at speeds between 1 and 3 m/s, and at heights from 5 to 15 m. Evaluation of snow-depth results indicates that a depth accuracy of ±3.2 cm is achieved with stationary measurements, and of ±9.1 cm with measurements at the various flight speeds. Numéro de notice : A2021-212 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3006182 Date de publication en ligne : 14/07/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3006182 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97197
in IEEE Transactions on geoscience and remote sensing > Vol 59 n° 3 (March 2021) . - pp 1868 - 1875[article]The effect of different sampling schemes on estimation precision of snow water equivalent (SWE) using geostatistics techniques in a semi-arid region of Iran / Hojatolah Ganjkhanlo in Geocarto international, vol 35 n° 16 ([01/12/2020])
[article]
Titre : The effect of different sampling schemes on estimation precision of snow water equivalent (SWE) using geostatistics techniques in a semi-arid region of Iran Type de document : Article/Communication Auteurs : Hojatolah Ganjkhanlo, Auteur ; Mehdi Vafakhah, Auteur ; Hossein Zeinivand, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1769 - 1782 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bassin hydrographique
[Termes IGN] carte thématique
[Termes IGN] classification hypercube
[Termes IGN] eau de fonte
[Termes IGN] échantillonnage de données
[Termes IGN] épaisseur
[Termes IGN] géostatistique
[Termes IGN] Iran
[Termes IGN] krigeage
[Termes IGN] manteau neigeux
[Termes IGN] neige
[Termes IGN] précision de l'estimation
[Termes IGN] zone semi-arideRésumé : (auteur) The aim of this study is to compare the effect of two sampling patterns: systematic sampling and Latin hypercube sampling (LHS), on estimation precision of snow water equivalent (SWE), and also comparing different geostatistics methods of kriging, cokriging and radial basin functions for mapping SWE. To achieve the study purpose, the semi-arid mountainous watershed of Sohrevard in Zanjan Province of Iran was selected. Snow depth in 150 points with systematic sampling and 150 points with LHS sampling and snow density in 18 points were randomly measured. In addition, SWE was calculated in the study area, and its map was derived based on both the sampling methods using geostatistical techniques. The results showed that the accuracy of the SWE map using LHS was higher than systematic sampling. According to the most statistical indicators, in both methods of sampling, accuracy of mapping using regular spline was better than other methods. Numéro de notice : A2020-725 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1581267 Date de publication en ligne : 03/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1581267 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96328
in Geocarto international > vol 35 n° 16 [01/12/2020] . - pp 1769 - 1782[article]Non-stationary extreme value analysis of ground snow loads in the French Alps: a comparison with building standards / Erwann Le Roux in Natural Hazards and Earth System Sciences, vol 20 n° 11 (November 2020)
[article]
Titre : Non-stationary extreme value analysis of ground snow loads in the French Alps: a comparison with building standards Type de document : Article/Communication Auteurs : Erwann Le Roux, Auteur ; Guillaume Evin, Auteur ; Nicolas Eckert, Auteur ; Juliette Blanchet, Auteur Année de publication : 2020 Article en page(s) : pp 2961 – 2977 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Alpes (France)
[Termes IGN] changement climatique
[Termes IGN] construction
[Termes IGN] épaisseur
[Termes IGN] estimation des charges
[Termes IGN] manteau neigeux
[Termes IGN] norme
[Termes IGN] sécurité
[Termes IGN] série temporelle
[Termes IGN] toit
[Termes IGN] valeur limiteMots-clés libres : Ground snow load surcharge de neige Résumé : (auteur) In a context of climate change, trends in extreme snow loads need to be determined to minimize the risk of structure collapse. We study trends in 50-year return levels of ground snow load (GSL) using non-stationary extreme value models. These trends are assessed at a mountain massif scale from GSL data, provided for the French Alps from 1959 to 2019 by a meteorological reanalysis and a snowpack model. Our results indicate a temporal decrease in 50-year return levels from 900 to 4200 m, significant in the northwest of the French Alps up to 2100 m. We detect the most important decrease at 900 m with an average of −30 % for return levels between 1960 and 2010. Despite these decreases, in 2019 return levels still exceed return levels designed for French building standards under a stationary assumption. At worst (i.e. at 1800 m), return levels exceed standards by 15 % on average, and half of the massifs exceed standards. We believe that these exceedances are due to questionable assumptions concerning the computation of standards. For example, these were devised with GSL, estimated from snow depth maxima and constant snow density set to 150 kg m−3, which underestimate typical GSL values for the snowpack. Numéro de notice : A2020-713 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/nhess-20-2961-2020 Date de publication en ligne : 06/11/2020 En ligne : https://doi.org/10.5194/nhess-20-2961-2020 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96279
in Natural Hazards and Earth System Sciences > vol 20 n° 11 (November 2020) . - pp 2961 – 2977[article]
Titre : The measurement of wood shrinkage and bark thickness on increment cores Type de document : Article/Communication Auteurs : Baptiste Kerfriden , Auteur ; Lucile Savagner, Auteur ; Kévin Dupont-Marin, Auteur ; Jean-Michel Leban , Auteur Editeur : Paris [France] : Institut national de recherche pour l’agriculture, l’alimentation et l’environnement INRAE (2020-) Année de publication : 2018 Conférence : Hardwood 2018, 8th hardwood conference, New aspects of hardwood utilization - from science to technology 25/10/2018 26/10/2018 Sopron Hongrie Langues : Anglais (eng) Descripteur : [Termes IGN] anatomie du bois
[Termes IGN] bois sur pied
[Termes IGN] écorce
[Termes IGN] épaisseur
[Termes IGN] phytobiologie
[Vedettes matières IGN] BotaniqueNuméro de notice : C2018-127 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Poster nature-HAL : Poster-avec-CL DOI : sans En ligne : https://hal.inrae.fr/hal-02786020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100049 Documents numériques
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