Discrete Return Lidar in Natural Resources: Recommendations for Project Planning, Data Processing, and Deliverables

Jeffrey Evans, Andrew Hudak, Russ Faux, Alistair M. Smith
2009 Remote Sensing  
Recent years have seen the progression of light detection and ranging (lidar) from the realm of research to operational use in natural resource management. Numerous government agencies, private industries, and public/private stakeholder consortiums are planning or have recently acquired large-scale acquisitions, and a national U.S. lidar acquisition is likely before 2020. Before it is feasible for land managers to integrate lidar into decision making, resource assessment, or monitoring across
more » ... e gambit of natural resource applications, consistent standards in project planning, data processing, and user-driven products are required. This paper introduces principal lidar acquisition parameters, and makes recommendations for project planning, processing, and product standards to better serve natural resource managers across multiple disciplines. Accuracy: The statistical comparison between known (surveyed) points and measured laser points. Typically measured as the standard deviation (σ 2 ) and root mean square error (RMSE). Bin: A set of aerial units that can be overlaid on the lidar point cloud to summarize or aggregate the data. Commonly a raster surface with a defined cell size is used, although a bin can be any set of landscape units such as stand boundaries. Canopy Height Model (CHM): The maximum lidar height value identified in a cell after the lidar point data are binned or interpolated. Classification: The process of identifying points as ground or non-ground (also referred to as filtering). The LAS standard defines several classes including: ground, low vegetation, medium vegetation, high vegetation, building, and water. Contours: Lines that represent known elevations with intervals typically recorded in feet. It is standard practice to develop minimum contour intervals with data that have an accuracy of two standard deviations (σ 2 ). Canopy Cover (Crown Cover): The proportion of ground covered by a vertical projection of the outermost perimeter of the natural spread of foliage or plants, including small openings within the canopy. Canopy Density (Crown Density): Amount and compactness of the foliage of the crowns of trees and shrubs. Digital Elevation Model (DEM): A raster surface derived from interpolating the elevation values of the classified lidar ground points. Digital Surface Model (DSM): A raster surface derived from interpolating the elevation values of all lidar points. Filtering: A term commonly used for point classification based on the notion of filtering out (discarding) non-ground points. Footprint: The size (radius) of the laser pulse once it starts interacting with objects. Geometric Correction: The process correcting the GPS readings, tying the data to local controls, and applying a coordinate system to the lidar point cloud. Geometric correction is performed by the vendor and is a critical step in the QA/QC. Error should be reported as vertical and horizontal. Height: A value calculated for every lidar point representing the height of a point above the ground surface once the ground elevations are subtracted. See also, canopy height model (CHM). Intensity: The peak power ratio of the laser return to the emitted laser. This is a function of surface reflectivity. Last Return: The last measurement in a laser pulse.
doi:10.3390/rs1040776 fatcat:xoxscl5uijhepmrdllef2u6vt4