| Titre | Method for measurement of snow depth using time-lapse photography |
| Télécharger | Téléchargements |
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| Licence | Veuillez noter que la Licence du gouvernement
ouvert - Canada remplace toutes les licences antérieures. |
| Auteur | Fernandes, R A ;
Bariciak, T; Prévost, C; Yao, H; Field, T; McConnell, C; Luce, J; Metcalfe, R |
| Source | Géomatique Canada, Dossier public 47, 2019, 32p., https://doi.org/10.4095/314726  Accès ouvert |
| Année | 2019 |
| Éditeur | Ressources naturelles Canada |
| Document | dossier public |
| Lang. | anglais |
| DOI | https://doi.org/10.4095/314726 |
| Media | en ligne; numérique |
| Formats | pdf (Adobe® Reader®) |
| Sujets | neige; climat; inondations; etudes de l'environnement; télédétection; méthodes photogrammétriques; photographie; instruments d'observation; logiciel; modèles; Méthodologie; surveillance; Automatisation;
Infrastructure; Habitat; géophysique; Nature et environnement |
| Illustrations | photographies; images numériques; représentations schématiques; cartes de localisation; images satellitaires; séries chronologiques; tableaux; graphiques; graphique à barres; diagrammes
schématiques |
| Programme | Science de la télédétection spatiale |
| Diffusé | 2019 06 05 |
| Résumé | (disponible en anglais seulement)
Snow depth (SD) is an essential climate variable widely used for flood forecasting, water quantity assessments, road and building safety assessment, habitat
assessment, and climate studies. Currently, SD is systematically monitored using manual ruler measurements or dedicated instrumentation with a limited spatial footprint (~1m2). Here, an approach for automated SD estimation using images of narrow
stakes remotely acquired by a 3Mpixel trail camera is described. The approach relies on the automated application of image processing and machine learning algorithms packaged within a single freely available application deployed on a personal
computer or cloud computing environment. The application requires minimal user input to define an initial template image and provides two independent estimates of SD at each stake that can be used to produce an estimate of total uncertainty and
sources of error. The system is compared to both manual ruler and ultrasonic instrument SD estimates at an open site and in a deciduous forest. Initial results over a melt period indicate the automated method agreed to within 1cm (RMSE) of manual
ruler estimates and to within 3.6cm of ultrasonic estimates; with the latter comparison including spatial variability between measurement locations. The automated system should be considered for further deployment and evaluation over a range of
surface and climate conditions. |
| Sommaire | (Résumé en langage clair et simple, non publié)
Une méthode d'estimation automatique de la hauteur de neige à partir d'images laps de temps de pieux placés dans des paysages naturels est
décrite et évaluée. |
| GEOSCAN ID | 314726 |
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