nundle.sf: Nundle State Forest LiDAR data

In NCSampling: Nearest Centroid (NC) Sampling

Description

LiDAR data from two strata acquired by over-flying the Nundle State Forest (SF), NSW, Australia in 2011

Usage

data(nundle.sf)

Format

A data frame with 2068 observations on the following 12 variables.

PID

numeric vector containing unique plot IDs

height

numeric vector containing LiDAR heights

meanht

numeric vector containing LiDAR mean heights

mam

a numeric vector containing mean above mean heights

mdh

a numeric vector containing LiDAR mean dominant heights

pstk

a numeric vector containing LiDAR stocking rate

cc

a numeric vector containing LiDAR canopy cover

OV

a numeric vector containing LiDAR occupied volume

var

a numeric vector containing LiDAR height variances

Strata

a factor with levels O, Y

x

a numeric vector containing x-coordinates

y

a numeric vector containing y-coordinates

Details

The LiDAR variables were calculated as outlined in Turner et al. (2011).

Source

Forestry Corporation of NSW

References

Melville G, Stone C, Turner R (2015). Application of LiDAR data to maximize the efficiency of inventory plots in softwood plantations. New Zealand Journal of Forestry Science, 45:9,1-16. doi:10.1186/s40490-015-0038-7.

Stone C, Penman T, Turner R (2011). Determining an optimal model for processing lidar data at the plot level: results for a Pinus radiata plantation in New SouthWales, Australia. New Zealand Journal of Forestry Science, 41, 191-205.

Turner R, Kathuria A, Stone C (2011). Building a case for lidar-derived structure stratification for Australian softwood plantations. In Proceedings of the SilviLaser 2011 conference, Hobart, Tasmania, Australia.

Examples

data(nundle.sf)

NCSampling documentation built on May 1, 2019, 10:15 p.m.