Mapping Snow Grain Size Using LiDAR Intensity (Extended Abstract)
Title | Mapping Snow Grain Size Using LiDAR Intensity (Extended Abstract) |
Publication Type | Conference Proceedings |
Year of Conference | 2021 |
Authors | Ackroyd, Chelsea, and S. Skiles McKenzie |
Conference Name | 88th Annual Western Snow Conference |
Conference Location | Bozeman, MT |
Keywords | intensity, LiDAR, radiometric correction, remote sensing, snow grain size |
Abstract | Net solar radiation is the primary driver of snowmelt, which is mainly determined by snow albedo. Controls on snow albedo vary spectrally: in the visible wavelengths it is controlled by light-absorbing particles, including dust and black carbon. For clean snow, snow albedo is dependent upon ice absorption in the near infrared wavelengths, typically characterized using the effective grain size (Warren, 1982). Grain size is currently estimated using radiative transfer inversion methods that leverage reflectance data from passive optical remote sensing imagery. Theoretically, it may also be possible to relate lidar intensity to grain size when the wavelength of the lidar is in the near-infrared wavelengths: smaller grains would reflect more light back to the sensor, larger grains would reflect less. This indicates that lidar could be used to retrieve surface optical properties. Here, we evaluate how well aerial lidar intensity at 1064 nm can be related to the grain size of snow at the basin-scale. |
URL | /files/PDFs/2021Ackroyd.pdf |