ABSTRACT INFORMATION
Title: Relationships Between Snowpack Depth and Primary Lidar Point Cloud Derivatives in a Mountainous Environment
Presentation Type: Oral
Special Session: 2- The application of lidar to problems in cold-regions hydrometeorology and water resources
Abstract: Two equivalent lidar datasets were acquired with an Airborne Laser Terrain Mapper over the Marmot Creek watershed. The first acquired during snow free conditions in August 2007, and the second during snow covered conditions in March 2008. A lidar snow depth model (LSDM) was derived by subtracting the snow free digital elevation model from the snow covered digital surface model. Field crews were deployed to collect snow depth transects in: a) valley locations of shallow discontinuous snow cover; b) alpine locations of deep discontinuous snowpack; and c) canopy covered locations displaying variable depth but continuous cover. Field and lidar snow depth data were compared. Based on assumptions that depth typically increases with elevation and that snow is highly reflective at the NIR wavelength of the ALTM (1064 nm), the LSDM was compared with lidar-based elevation and intensity (first order derivatives of the point cloud). Further, the influence of lidar-derived canopy cover on the snow / intensity relationship was explored due to signal attenuation and multiple backscatter properties. The DSM required a minor block adjustment of elevation (0.2 m) calibrated over snow free highway surfaces to enable accurate relative positioning of the DEM and DSM surfaces. Following this ‘calibration’ of the surfaces, it was found that the LSDM performed favourably over alpine transects with no significant bias (r2 ~ 0.9), with the valley transects demonstrating a slight over-estimation of ~0.07 m (r2 ~ 0.4) and intermediate elevation forest covered transects demonstrating no significant correlation but depth estimates within 0.10 m. Canopy cover provides a challenge for mapping shallow snow depth with lidar in mountainous environments. However, it needs to be acknowledged that dense canopy also reduces the accuracy of GPS data and it is likely that the valley and forest transects are not perfectly aligned. This introduces an unknown quantity of uncertainty into the validation that given the heterogeneity of actual snow depth over short distances, likely increases the apparent error. The LSDM illustrated increasing snow depth up to tree line at approximately 2250 m a.e. with reducing depth and cover in the alpine zone. Overall, high lidar intensities were weakly correlated with snow cover at the basin scale with only 44% spatial correspondence. However, above tree line this increased to 76%, suggesting that lidar intensity has some value for snow covered area (SCA) mapping as long as there is no forest canopy to attenuate or split the laser pulse returns.
Presenters are listed in the order they will be listed in the program materials.
Person Type: POC,Primary Presenter,Author
First Name: Christopher
Last Name: Hopkinson
Organization: Centre of Geographic Sciences Applied Geometrics Research Group
Mailing Address:
 
City: Middleton
State: Nova Scotia
Zip:
Phone:
E-mail: chris.hopkinson@nscc.ca
Authors are listed in the order they will be listed in the program materials.
Person Type: POC,Primary Presenter,Author
First Name: Christopher
Last Name: Hopkinson
Organization: Centre of Geographic Sciences Applied Geometrics Research Group
Mailing Address:
 
City: Middleton
State: Nova Scotia
Zip:
Phone:
E-mail: chris.hopkinson@nscc.ca
Person Type: Author
First Name: John
Last Name: Pomeroy
Organization: University of Saskatchewan
Mailing Address:
 
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E-mail: john.pomeroy@usask.ca
Person Type: Author
First Name: Chris
Last Name: DeBeer
Organization:
Mailing Address:
 
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E-mail: cmd225@mail.usask.ca
Person Type: Author
First Name: Chad
Last Name: Ellis
Organization:
Mailing Address:
 
City:
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E-mail: cre152@mail.usask.ca
Person Type: Author
First Name: Axel
Last Name: Anderson
Organization:
Mailing Address:
 
City:
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E-mail: Axel.Anderson@gov.ab.ca