Loading…
UAV-BASED LIDAR HIGH-RESOLUTION SNOW DEPTH MAPPING IN THE SWISS ALPS: COMPARING FLAT AND STEEP FORESTS
Snow depth mapping in Alpine forests is of high importance for hydrogeology, ecology, tourism, and natural hazards prevention. Different remote sensing approaches have been employed for the precise mapping of snow depth within forests. However, optical sensors cannot provide below-canopy information...
Saved in:
Published in: | International archives of the photogrammetry, remote sensing and spatial information sciences. remote sensing and spatial information sciences., 2021-06, Vol.XLIII-B3-2021, p.477-484 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Snow depth mapping in Alpine forests is of high importance for hydrogeology, ecology, tourism, and natural hazards prevention. Different remote sensing approaches have been employed for the precise mapping of snow depth within forests. However, optical sensors cannot provide below-canopy information. While Airborne Laser Scanning (ALS) systems have been used successfully in this context and allow obtaining data below canopies, the costs of acquisitions are very high, not allowing frequent data acquisitions. UAV-based Lidar technology potentially can provide the critical below-canopy information at lower cost and allows for frequent acquisitions.First attempts to employ a UAV-based Lidar system in forests have proven promising, but they are limited to flat forests and to grid-level snow depth calculations. In this study, we present UAV-based Lidar data of both flat and steep forests. Different Lidar processing workflows are analyzed and compared, and snow depth algorithms are used both at the point and the grid level. Whereas the UAV-Lidar system proved capable of mapping snow in both environments, the steep forests' data processing comes with greater challenges, especially for the 3D registration, ground classification, and point-to-point snow depth calculations. |
---|---|
ISSN: | 2194-9034 1682-1750 2194-9034 |
DOI: | 10.5194/isprs-archives-XLIII-B3-2021-477-2021 |