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  4. Uav-Based LIDAR High-Resolution Snow Depth Mapping in the Swiss Alps: Comparing Flat and Steep Forests

Uav-Based LIDAR High-Resolution Snow Depth Mapping in the Swiss Alps: Comparing Flat and Steep Forests

Author(s)
Koutantou, Kalliopi  
Faculté des sciences  
Mazzotti, Giulia
Brunner, Philip  
Décanat de la faculté des sciences  
Publisher
ISPRS Congress
Date issued
November 10, 2021
In
XXIV Congress 2021 from the International Society for Photogrammetry and Remote Sensing (ISPRS)
From page
477
To page
481
Subjects
UAV Lidar forests snow depth mapping 3D registration C2C DoD
Abstract
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.
Event name
XXIV Congress 2021 from the International Society for Photogrammetry and Remote Sensing (ISPRS)
Location
Nice
Publication type
conference paper
Identifiers
https://libra.unine.ch/handle/20.500.14713/21747
DOI
10.5194/isprs-archives-XLIII-B3-2021-477-2021
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2021-11-10_110_9062.pdf

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