scholarly journals Integrating airborne and mobile lidar data with UAV photogrammetry for rapid assessment of changing forest snow depth and cover

2021 ◽  
Vol 4 ◽  
pp. 100029
Author(s):  
Jonathon Donager ◽  
Temuulen Ts. Sankey ◽  
Andrew J. Sánchez Meador ◽  
Joel B. Sankey ◽  
Abraham Springer
Keyword(s):  
Snow Depth ◽  
Rapid Assessment ◽  
Lidar Data

scholarly journals Brief Communication: Initializing RAMMS with High Resolution LiDAR Data for Avalanche Simulations

2021 ◽  
Author(s):  
James Dillon ◽  
Kevin Hammonds
Keyword(s):  
High Resolution ◽  
Snow Depth ◽  
Software Tool ◽  
Lidar Data ◽  
Mass Movements ◽  
Flow Volume ◽  
Vegetative Cover ◽  
Avalanche Forecasting ◽  
Simulation Results ◽  
Rapid Mass

Abstract. The Rapid Mass Movements Simulator (RAMMS) is an avalanche dynamics software tool for research and forecasting. Since the model’s conception, the sensitivity of inputs on simulation results has been well-documented. Here, we introduce a new method for initializing RAMMS that can be easily operationalized for avalanche forecasting using high resolution LiDAR data. As a demonstration, hypothetical avalanche simulations were performed while incrementally incorporating semi-automated LiDAR-derived values for snow depth, interface topography, and vegetative cover from field-collected LiDAR data. Results show considerable variation in the calculated runout extent, flow volume, pressure, and velocity of the simulated avalanches when incorporating these LiDAR-derived values.

scholarly journals Orographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from LiDAR data

2015 ◽  
Vol 9 (4) ◽  
pp. 4377-4405
Author(s):  
Z. Zheng ◽  
P. B. Kirchner ◽  
R. C. Bales
Keyword(s):  
Sierra Nevada ◽  
Snow Depth ◽  
Canopy Gaps ◽  
Snow Accumulation ◽  
Absolute Difference ◽  
Lidar Data ◽  
Vegetation Effects ◽  
Topographic Features ◽  
Canopy Coverage ◽  
Combining Data

Abstract. Airborne light detection and ranging (LiDAR) snow-on and snow-off measurements collected in the southern Sierra Nevada in the 2010 water year were analyzed for orographic and vegetation effects on snow accumulation during the winter season. Combining data from four sites separated by 10 to 64 km and together covering over 106 km2 area, the 1 m elevation-band-averaged snow depth in canopy gaps as a function of elevation increased at a rate of 15 cm per 100 m until reaching the elevation of 3300 m. The averaged snow depth of the same elevation band from different sites matched up with minor deviation, which could be partially attributed to the variation in other topographic features, such as slope and aspect. As vegetation plays a role in the snow accumulation, the distribution of the vegetation was also studied and shows that the canopy coverage consistently decreased along the elevation gradient from 80 % at 1500 m to near 0 % at above 3300 m. Also, the absolute difference of the averaged snow depth between snow found in canopy gaps and under the canopy increased with elevation, and decreased with canopy coverage disregarding the variation of other topographic features. The influence from the forest density on snow accumulation was quantified based on the snow-depth residuals from 1 m elevation-band-averaged snow depth and the attribute penetration fraction, which is the ratio of the number of ground points to the number of total points per pixel of LiDAR data. The residual increases from −25 to 25 cm at the penetration fraction range of 0 to 80 %; and the relationship could be modeled by exponential functions, with minor fluctuations along the gradient fraction of canopy and small deviation between sites.

Zone-axis ALCHEMI for the rapid assessment of site occupancies in garnets

1986 ◽  
Vol 44 ◽  
pp. 706-707
Author(s):  
M.T. Otten ◽  
P.R. Buseck
Keyword(s):  
Single Crystals ◽  
Rapid Assessment ◽  
Site Occupancy ◽  
Zone Axis ◽  
Synthetic Compounds ◽  
X Ray ◽  
Large Group ◽  
Crystallographic Planes

ALCHEMI (Atom Location by CHannelling-Enhanced Microanalysis) is a TEM technique for determining site occupancies in single crystals. The method uses the channelling of incident electrons along specific crystallographic planes. This channelling results in enhanced x-ray emission from the atoms on those planes, thereby providing the required site-occupancy information. ALCHEMI has been applied with success to spinel, olivine and feldspar. For the garnets, which form a large group of important minerals and synthetic compounds, the channelling effect is weaker, and significant results are more difficult to obtain. It was found, however, that the channelling effect is pronounced for low-index zone-axis orientations, yielding a method for assessing site occupancies that is rapid and easy to perform.

Implementing a Snow Depth Measurement Sensor for the IoT

2019 ◽  
Vol 139 (12) ◽  
pp. 412-416
Author(s):  
Sou Takahashi ◽  
Daigo Kamata
Keyword(s):  
Snow Depth ◽  
Depth Measurement ◽  
Measurement Sensor
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