LIDAR Method. Comprehensive Model Selection. Models were built and ranked by their back-transformed R2 values.
LIDAR Method. The method used to build this linear regression model is described in further detail in Section 3.1, the LIDAR Method for Canopy Height.
LIDAR Method. This was not studied for this project. LIDAR describes the physical arrangement and crown densities of a stand, and also provides limited near-infrared intensity information. It is only possible to measure age if it can be estimated from structural or intensity information.
LIDAR Method. Vegetation class is a description of how a stand is progressing through a development process and how the individual trees are interacting with each other and their specific, local environment. There are many different schemes used for classifying vegetation into development stages, with possibly one, Xxxxxx and Xxxxxx (Xxxxxx & Xxxxxx, 1990), establishing the most commonly used terminology. As time has passed, schemes for classifying vegetation seem to have become more complicated, increasing the number of classes from the four described in Xxxxxx and Xxxxxx, to as many as six or eight. LIDAR is a tool that can help describe stand structure. Any method to estimate vegetation class from LIDAR must use the structure as a proxy for development progress. To this end, only classes that can be distinguished from one another structurally can be identified using LIDAR. This argues for a simple classification scheme. We chose a four class scheme based on Xxxxxx and Xxxxxx, but because the names of vegetation classes reflect stages of a biological process, and because LIDAR can only tell you structural characteristics, we propose a different naming scheme for these vegetation classes.
LIDAR Method. The methods described here were also used for Conifer/Deciduous Classification and Large Woody Debris. The field crew collecting plot data recorded whether each tree measured was alive or dead, allowing for plot level counts of snags. There were plots with no snags present, creating a non-normal distribution of counts shown in Figure 27 below.
LIDAR Method. Three methods were used to build stand density models from LIDAR. The first approach built a linear regression model based on individual tree objects (ITOs) from a segmented canopy height model. The second approach built a linear regression model using the method described in further detail in Section 3.1, the LIDAR Method for Canopy Height. The third method included the stratified bin of each plot, which indicates information about the height and cover values of each plot.
LIDAR Method. The development of channel locations from LIDAR is a standardized process, but involves making choices, all of which impact the final outcome. The general approach involves the following steps: develop a digital elevation model (DEM), perform a flow accumulation on the DEM, set a flow accumulation threshold to determine the perennial initiation point, and convert the result to a vector GIS dataset. Details of the specific processing performed for this project are available in Appendix A.
LIDAR Method. Currently there are no known large scale, high accuracy methods for identifying species from LIDAR.
LIDAR Method. LIDAR was used to estimate the volume of large woody debris following the methods described in Section 4.1, Snag Detection, LIDAR Method.
LIDAR Method. 15 2.1.1 Digital Elevation Model Resolution 15
