Aboveground biomass estimates of sagebrush using terrestrial and airborne LiDAR data in a dryland ecosystem

Airborne lidar remote sensing applications in non-forested short stature environments: a review

“…(Hopkinson et al 2005). Furthermore, in sparsely vegetated environments, as in the case of most dry land ecosystems, fewer vegetation returns (as compared to densely foliated forested ecosystems) are recorded (Li et al 2015, Mitchel et al 2015, Rango et al 2000, Ritchie et al 1992, Weltz et al 1994) and may not provide sufficient details to capture relatively larger spatial variation in vegetation surfaces, which may lead to increased errors in vegetation estimates. On the other hand, when the plant cover is dense, these pulses may not be able to penetrate all the vegetation layers and reach the ground surface (Cobby et al 2001, Estornell et al 2010, Gopfert & Heipke 2006, Hodgson et al 2005, Raber et al 2002, Riano et al 2007).…”

“…Thus a larger ratio implies a higher vegetation density while a small ratio is indicative of the higher canopy openings. Over the recent past an increasing number of studies reported using laser penetration indices for vegetation cover and biomass estimates in short stature environments, more specifically over crop lands (Luo et al 2016) grassland dominated rangeland environments (Mograbi et al 2015, Ritchie et al 1992, Weltz et al 1994, sagebrush dominated landscapes (Li et al 2015, Mitchel et al 2015, Sankey et al 2010, Struetker & Glenn 2006, forest understorey (Estornell et al 2012) and wetlands (Luo et al 2014, Kulawardhana et al 2014.…”

“…Only a very few studies evaluated the effects of variable filtering window sizes and lidar point densities on the accuracies of lidar derived cover variables (Luo et al 2014(Luo et al , 2016. Over shrub dominated ecosystems, insufficient returns from vegetation in particular over heterogeneous cover conditions is one of the major limitations in using laser penetration indices for canopy cover and/ or volume estimates (Li et al 2015, Mitchel et al 2015. In general, when sufficient canopy openings are available to allow laser penetration into the ground surfaces, first and last returns are expected to return from the top of vegetation and ground surfaces, respectively.…”

“…First, dense vegetation, characterized by relatively less openings in vegetation cover limits laser penetration into the ground (Toyra et al 2003), making terrain and thus vegetation height estimates increasingly challenging and less accurate (Chassereau et al 2011, Hopkinson et al 2005. Second, relatively shorter vegetation and low variation in vegetation height and canopy characteristics along vertical profile of the canopy erode predictability of lidar derived variables in vegetation estimates (Li et al 2015, Rosso et al 2006, Wang et al 2007). Theoretically in lidar remote sensing, vegetation structure can be better characterized using information provided by both first and last returns recorded for each emitted laser pulse.…”

Assessing Greater Sage-Grouse Breeding Habitat With Aerial and Ground Imagery

“…The location of the point in 3-D space is calculated by knowing the angle of the pulsed energy and the precise time of flight. The TLS point cloud is very dense (∼100-1000 points m -2 ), but typically covers a small area (∼0.01-1 km 2 ), making it ideal for projects requiring high detail at smaller scales for local studies or for use in scaling to larger landscapes (Li et al 2015) (Fig. 2).…”