Abstract
igital elevation models (DEMs) form the basis of LiDAR derived tree height measurements and other topographic modeling needs within natural resource applications. We compared 2873 digital total station elevations to the closest discrete LiDAR elevation point and DEM raster cell across several forest and topographic settings. We also examined limiting comparisons to points within 0.5 m and within one meter. Using all nearest LiDAR points, average total station plot elevation differences ranged from -0.06 m (SD 0.40) to -0.59 m (SD 0.23) indicating that LiDAR elevations are higher than actual elevations. LiDAR DEM differences ranged from -0.09 (SD 0.41) to -0.56 m (SD 0.70). We also compared mapping-grade GPS receiver measurements to LiDAR point elevation and DEMs. Average plot GPS elevation differences ranged from 0.24 (SD 1.55) to 2.82 m (SD 4.58) for the nearest LiDAR point, and from 0.27 (SD 2.33) to 2.69 m (SD 5.06) for LiDAR DEMs. We believe that our efforts represent one of the most robust studies of LiDAR measurement errors available in published literature. The relatively small measurement differences that we found between LiDAR elevations and our most reliable field-based method of elevations, the digital total station, demonstrate the potential for LiDAR in forestry and natural resource applications.
Highlights
Light Detection and Ranging (LiDAR), known as airborne laser scanning, has emerged since its initial applications in the mid 1980’s into many activities including forest management, urban planning, natural resource modeling, ice sheet mapping, and road design (Lim et al 2003; Aguilar and Mills 2008)
We examined the influence of limiting discrete point comparisons to only points that were within 0.5 m and only those that were within one meter
When only points that were within 0.5 m of each other were selected, resulting mean error (ME) values ranged from -0.06 (SD 0.37 ) to -0.60 m (SD 0.17) (Table 5)
Summary
Light Detection and Ranging (LiDAR), known as airborne laser scanning, has emerged since its initial applications in the mid 1980’s into many activities including forest management, urban planning, natural resource modeling, ice sheet mapping, and road design (Lim et al 2003; Aguilar and Mills 2008). An aerial LiDAR system configuration for terrain mapping consists of a laser scanning sensor mounted on an aircraft (either fixed or rotary wing), Inertial Measurement Unit (IMU), and global positioning system (GPS) (Hodgson et al 2005; Reutebuch et al 2005; Liu 2008). Reutebuch et al (2003) compared 1.5 m post spacing DEM elevations derived from LiDAR data to 347 checkpoints located in forest settings including clearcut, heavily thinned, lightly thinned, and uncut. Hodgson et al (2005) conducted a similar study within terrain described as gently rolling with elevations ranging from 44 to 136 m above mean sea level They reported an error range from 0.15 to 0.36 m RMSE with the highest error occurring in scrub/shrub land cover at 0.36 m RMSE. Errors in pine and leaf-off deciduous forest were approximately the same at 0.28 and 0.27 m RMSE, respectively, while mixed forest error was lower at 0.24 m RMSE
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