LiDAR Enhanced DEM and soil moisture prediction

LiDAR Enhanced DEM and Soil Moisture Prediction

Lead Researcher: Shudao Ni, MSc, P.Geo, RPF

To extrapolate the impacts of regional climate change across the landscape, accurate terrain mapping is critical. Airborne Light Detection and Ranging (LiDAR) is one of the most effective and reliable means of terrain data collection to generate a digital elevation model (DEM) (Figure 1).

Figure 1: LiDAR DEM map of Prince George, BC, 2012

The effects of DEM resolutions on terrain attribute calculations, and the reliably of Topographic Wetness Index (TWI) in modeling soil moisture patterns in a boreal forest environment were evaluated.

Year one activities (2011-2012)

  • Generated digital elevation models (DEM) at different resolutions using both TRIM and LiDAR data (Figure 2).

Figure 2: North Nechako River study site, Prince George, BC.

  • Generated Topographic Wetness Index (TWI) models that predict soil and site characteristics using different analytical tools in ArcGIS.
  • Collected field measurement data for soil moisture prediction and analysis (Figure 3).

Figure 3: Field measurement location on orthophoto and classified slope map, North Nechako River site

Field measurements included soil moisture, surficial material composition, soil texture and coarse fragments, slope and slope position, aspect, and vegetation information (Figures 4 and 5).

Figure 4: Collection of field soil moisture measurements using a Theta Probe ML2x

Figure 5: Field measurements collection on Cranbrook Hill, Prince George, BC

Year two activities (2012-2013)

  • Analyzed and evaluated field measurement data and TWI model for soil moisture prediction.
  • Evaluated the accuracy of terrain attributes generated by DEMs at six different levels of resolution (Figure 6).

Figure 6. TWI map for 1,2,5,10,15,20 m resolution at North Nechako Rive site.

Results and analysis

Effects of Digital Elevation Model (DEM) Resolution on Terrain Attributes
  • Terrain attributes vary strongly with DEM resolutions.
  • Coarse DEM resolution results in: smaller mean slope, higher Topographic Wetness Index (TWI) values that indicate higher soil moisture, narrow range of TWI distribution.
Soil moisture prediction
  • Moderate but significant correlation between field measurements and TWI derived from Digital Elevation Models (DEMs) with different resolutions.
  • Better correlation between soil moisture at 10 cm depth and TWI of a DEM with 10m resolution (Maximum r=0.63).

Information dissemination

Construction of a weather station: taking microclimate measurements for the assisted migration projects