ENGLISH
La vitrine de diffusion des publications et contributions des chercheurs de l'ÉTS
RECHERCHER

A new interpolation method to resolve under-sampling of UAV-lidar snow depth observations in coniferous forests

Téléchargements

Téléchargements par mois depuis la dernière année

Plus de statistiques...

Dharmadasa, Vasana, Kinnard, Christophe et Baraër, Michel. 2024. « A new interpolation method to resolve under-sampling of UAV-lidar snow depth observations in coniferous forests ». Cold Regions Science and Technology, vol. 220.

[thumbnail of Baraer-M-2024-28388.pdf]
Prévisualisation
PDF
Baraer-M-2024-28388.pdf - Version publiée
Licence d'utilisation : Creative Commons CC BY.

Télécharger (8MB) | Prévisualisation

Résumé

Obtaining accurate snow depth estimates under dense canopies using airborne lidar (light detection and ranging) techniques is challenging due to the under-sampling of ground and snow surfaces. Existing interpolation techniques do not adequately address this problem and they often result in an overestimation of under-canopy snow depths. To address this issue, we introduce and evaluate a new interpolation method that incorporates intracanopy snow depth variability to provide more accurate estimations at unsampled locations. Four interpolation methods were tested, considering systematic trends (landscape trend, canopy vs. gap trend, and intra-canopy trend) along with spatial interpolation of the residuals. Our results show that spatial interpolation methods without consideration of trends are sufficient to capture and reconstruct the small-scale variability of snow depths below a separation distance of 1 m between sampled and unsampled locations, (i.e., ground surface point density > 1 pt. m▯ 2). However, beyond a separation distance of 2.5–3 m (point density < 0.33–0.40 pt. m▯ 2), spatial interpolation based on proximity alone becomes unreliable because point separation becomes larger than the snow depth spatial correlation scale. Within these limiting distances, the method that incorporates trends along with spatial interpolation techniques can resolve the small-scale variability and thereby reduce the likely overestimation of snow depths under the canopy.

Type de document: Article publié dans une revue, révisé par les pairs
Professeur:
Professeur
Baraër, Michel
Affiliation: Génie de la construction
Date de dépôt: 04 mars 2024 15:50
Dernière modification: 11 mars 2024 16:08
URI: https://espace2.etsmtl.ca/id/eprint/28388

Actions (Authentification requise)

Dernière vérification avant le dépôt Dernière vérification avant le dépôt