The influence of LiDAR pulse density on the precision of inventory metrics in young unthinned Douglas-fir stands during initial and subsequent LiDAR acquisitions

BackgroundLiDAR is an established technology that is increasingly being used to characterise spatial variation in stand metrics used in forest inventory. As the cost of LiDAR acquisition markedly declines with LiDAR pulse density, it is useful to identify how far pulse density can be reduced without compromising the precision of relationships between LiDAR and stand metrics. Using plot measurements and LiDAR data obtained from highly stocked and unthinned Douglas-fir plantations (Pseudotsuga menziesii [Mirb.] Franco), the objective of this research was to characterise the precision of regressions between LiDAR metrics and stand metrics (mean top height, Hm, volume, V and mean diameter, D) under a range of pulse densities using Digital Terrain Models (DTMs) representing two common scenarios. Under the first scenario, which represents an initial acquisition, the point cloud was sequentially culled and used for creation of a DTM and corresponding LiDAR cloud metrics. In the second scenario, which represents a subsequent acquisition, a DTM generated at high pulse density (10 pulses m−2) was used for the creation of the corresponding LIDAR cloud metrics.MethodsModels describing the precision of regressions between LiDAR metrics and stand metrics were developed at 10 pulses m−2. LiDAR data were culled to pulse densities ranging from 10 to 0.01 pulses m−2 and the impact of culling on the precision of these regressions was examined under the two scenarios.ResultsFor the scenario with the culled DTM, precision of the three models remained stable until densities of 2 – 3 pulses m−2 were reached. Below this threshold, there was a gradual decline in precision to pulse densities of 0.7 – 1 pulses m−2 at which point the R2 was 95% of the maximum values. Further culling of the data resulted in a sharp decline in model precision for all three regressions. For the scenario where the DTM was held at a high pulse density, little change in the precision of the regressions was found until pulse densities of 0.04 to 0.2 pulses m−2 were reached. There was a sharp decline in precision below pulse densities of 0.04 pulses m−2 for all three models.ConclusionThis study was undertaken in highly stocked unthinned Douglas-fir stands located in areas with complex topography. Consequently, the pulse density thresholds described here are likely to be conservative and could be used to guide acquisition of high-quality LiDAR datasets for this species.

[1]  D. A. Crouse,et al.  Horizontal resolution and data density effects on remotely sensed LIDAR-based DEM , 2006 .

[2]  AND OTHER DATA USING 2 D AND 3 D VISUALIZATION TECHNIQUES , 2003 .

[3]  P. Watt,et al.  Influence of stand and site conditions on the quality of digital elevation models underlying New Zealand forests , 2013, New Zealand Journal of Forestry Science.

[4]  E. Næsset Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data , 2002 .

[5]  J. Means Use of Large-Footprint Scanning Airborne Lidar To Estimate Forest Stand Characteristics in the Western Cascades of Oregon , 1999 .

[6]  Nicholas C. Coops,et al.  Assessment of forest structure with airborne LiDAR and the effects of platform altitude , 2006 .

[7]  T. Nord-Larsen,et al.  Estimation of forest resources from a country wide laser scanning survey and national forest inventory data , 2012 .

[8]  J. Means,et al.  Predicting forest stand characteristics with airborne scanning lidar , 2000 .

[9]  Emmanuel P. Baltsavias,et al.  Airborne laser scanning: basic relations and formulas , 1999 .

[10]  Erik Næsset,et al.  Assessing sensor effects and effects of leaf-off and leaf-on canopy conditions on biophysical stand properties derived from small-footprint airborne laser data , 2005 .

[11]  Michael S. Watt,et al.  Development of a national model of Pinus radiata stand volume from lidar metrics for New Zealand , 2013 .

[12]  Am Mudabeti,et al.  Remote sensing 1 , 2013 .

[13]  E. Næsset Effects of different sensors, flying altitudes, and pulse repetition frequencies on forest canopy metrics and biophysical stand properties derived from small-footprint airborne laser data , 2009 .

[14]  E. Næsset Practical large-scale forest stand inventory using a small-footprint airborne scanning laser , 2004 .

[15]  E. Næsset,et al.  Estimating tree heights and number of stems in young forest stands using airborne laser scanner data , 2001 .

[16]  Terje Gobakken,et al.  Assessing effects of laser point density, ground sampling intensity, and field sample plot size on biophysical stand properties derived from airborne laser scanner data , 2008 .

[17]  Kevin Lim,et al.  LiDAR Sampling Density for Forest Resource Inventories in Ontario, Canada , 2012, Remote. Sens..

[18]  I. Burke,et al.  Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests , 2005 .

[19]  Erik Næsset,et al.  Effects of different flying altitudes on biophysical stand properties estimated from canopy height and density measured with a small-footprint airborne scanning laser , 2004 .

[20]  Marek K. Jakubowski,et al.  Tradeoffs between lidar pulse density and forest measurement accuracy , 2013 .

[21]  Kazukiyo Yamamoto,et al.  The penetration rate of laser pulses transmitted from a small-footprint airborne LiDAR: a case study in closed canopy, middle-aged pure sugi (Cryptomeria japonica D. Don) and hinoki cypress (Chamaecyparis obtusa Sieb. et Zucc.) stands in Japan , 2006, Journal of Forest Research.

[22]  N. Coops,et al.  Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR , 2007, Trees.

[23]  R. McMurtrie Modelling of canopy carbon and water balance , 1993 .

[24]  E. Næsset,et al.  Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve , 2002 .

[25]  D. Hall Photosynthesis and production in a changing environment : a field and laboratory manual , 1993 .

[26]  Johan E. S. Fransson,et al.  Effects on estimation accuracy of forest variables using different pulse density of laser data , 2007 .

[27]  R. Nelson,et al.  Determining forest canopy characteristics using airborne laser data , 1984 .

[28]  R. K. Hermann,et al.  Douglas-fir planted forests , 2004, New Forests.

[29]  Nicholas C. Coops,et al.  Simulation study for finding optimal lidar acquisition parameters for forest height retrieval , 2005 .