An Evaluation of Lidar-derived Elevation and Terrain Slope in Leaf-off Conditions

Hodgson, Michael E.; Jensen, John R.; Raber, George T.; Tullis, Jason A.; Davis, Bruce A.; Thompson, G. S.; Schuckman, Karen

doi:10.14358/pers.71.7.817

Cited by 147 publications

(109 citation statements)

References 12 publications

(21 reference statements)

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“…Slope errors display little discernable pattern across the x-axis. Slope errors plotted by road grade did exhibit a slight tendency to under-predict surveyed slope at higher gradients, similar results were reported by Hodgson et al [53]. …”

Section: Lidar-derived Feature Accuracysupporting

confidence: 90%

“…In addition, the accuracy of road slope measurements was not significantly affected by increases in overhead canopy cover or road slope. A relatively small sample size was used for this analysis, though results fall in-line with previously reported values for forested areas [20,53]. While road grade measurements may be used with confidence, a host of other road characteristics are typically needed to accurately estimate road erosion.…”

Section: Discussionsupporting

confidence: 52%

See 1 more Smart Citation

Forest Roads Mapped Using LiDAR in Steep Forested Terrain

et al. 2010

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LiDAR-derived digital elevation models can reveal road networks located beneath dense forest canopy. This study tests the accuracy of forest road characteristics mapped using LiDAR in the Santa Cruz Mountains, CA. The position, gradient, and total length of a forest haul road were accurately extracted using a 1 m DEM. In comparison to a field-surveyed centerline, the LiDAR-derived road exhibited a positional accuracy of 1.5 m, road grade measurements within 0.53% mean absolute difference, and total road length within 0.2% of the field-surveyed length. Airborne LiDAR can provide thorough and accurate road inventory data to support forest management and watershed assessment activities.

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Section: Lidar-derived Feature Accuracysupporting

confidence: 90%

Section: Discussionsupporting

confidence: 52%

Forest Roads Mapped Using LiDAR in Steep Forested Terrain

et al. 2010

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“…WGEW is located within the San Pedro River basin, in a semi arid brush-grassland complex in the transition zone between Sonoran and Chihuahuan deserts [15]. The study area is a grass-dominated, small 1.91-ha watershed with an average slope of 9.4%.…”

Section: Study Areamentioning

confidence: 99%

“…The last return pulse is often considered the best estimate of the ground and is often assumed to be the -bald earth‖. However, even the last return will not necessarily be the ground as vegetation canopy may totally obscure the ground [15,16]. In addition, at small scales the utility of first and last return acquisition can be lost when the scanning device is stationary and the returns yield identical results do to the relative size of the footprint.…”

Section: Introductionmentioning

confidence: 99%

DEM Development from Ground-Based LiDAR Data: A Method to Remove Non-Surface Objects

2010

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Topography and land cover characteristics can have significant effects on infiltration, runoff, and erosion processes on watersheds. The ability to model the timing and routing of surface water and erosion is affected by the resolution of the digital elevation model (DEM). High resolution ground-based Light Detecting and Ranging (LiDAR) technology can be used to collect detailed topographic and land cover characteristic data. In this study, a method was developed to remove vegetation from ground-based LiDAR data to create high resolution DEMs. Research was conducted on intensively studied rainfall-runoff plots on the USDA-ARS Walnut Gulch Experimental Watershed in Southeast Arizona. LiDAR data were used to generate 1 cm resolution digital surface models (DSM) for 5 plots. DSMs created directly from LiDAR data contain non-surface objects such as vegetation cover. A vegetation removal method was developed which used a slope threshold and a focal mean filter method to remove vegetation and create bare earth DEMs. The method was validated on a synthetic plot, where rocks and vegetation were added incrementally. Results of the validation showed a vertical error of ±7.5 mm in the final DEM.

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“…Several studies have also demonstrated that vegetation cover, terrain slope, and terrain variability can have a significant effect on elevation errors [21] [22] [23] [24] [25]. In general, elevation errors increase with vegetation cover and amount of understory as well as with increasing terrain slope and variability [26] [27] [28].…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Accuracy of LiDAR-Derived DEM in Deciduous Eastern Forests of the Cumberland Plateau

Contreras¹,

Staats²,

Yiang³

et al. 2017

JGIS

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Digital elevation models (DEMs) derived from light detection and ranging (LiDAR) technology are becoming the standard in representing terrain surfaces. They have numerous applications in forestry, agriculture, and natural resources. Although elevation errors are much lower than those derived from traditional methods, accuracies have been reported to decrease with terrain slope and vegetation cover. In this study, we quantified the accuracy of airborne Li-DAR-derived DEM in deciduous eastern forests of the Cumberland Plateau. We measured relative elevation changes within field plots located across different slope and ruggedness classes to quantify DEM accuracy. We compared elevation change errors of DEMs derived from three LiDAR datasets: a low-density (~1.5 pts•m ), and a combined dataset. We also compared DEMs obtained by interpolating the ground points using four interpolation methods. Results indicate that mean elevation change error (MECE) increased with terrain slope and ruggedness with an average of 73.6 cm. MECE values ranged from 23.2 cm in areas with lowest slope (0% -39%) and ruggedness (0% -28%) classes to 145.5 cm in areas with highest slope (50% -103%) and ruggedness (46% -103%) classes. We found no significant differences among interpolation methods or LiDAR datasets; the latter of which indicates that similar accuracy levels can be achieved with the low-density datasets.

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An Evaluation of Lidar-derived Elevation and Terrain Slope in Leaf-off Conditions

Cited by 147 publications

References 12 publications

Forest Roads Mapped Using LiDAR in Steep Forested Terrain

Forest Roads Mapped Using LiDAR in Steep Forested Terrain

DEM Development from Ground-Based LiDAR Data: A Method to Remove Non-Surface Objects

Quantifying the Accuracy of LiDAR-Derived DEM in Deciduous Eastern Forests of the Cumberland Plateau

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