Foreword
By V.A. Thomas, PhD
Associate Professor
Department of Forest Resources and Environmental Conservation
Director, Center for Environmental Analytics and Remote Sensing
Virginia Tech
Lidar remote sensing enables us to map the world in three dimensions. In the past three decades, use of lidar data has dramatically expanded to the point where it is hard to imagine an application that doesn’t benefit from a 3-dimensional understanding of the world. The lidar community has evolved from a relatively small group of highly trained and technically advanced users to include people of all levels of skills and knowledge across a wide variety of disciples. To name but a few, the benefits of lidar data have been widely demonstrated for such applications as topographic mapping, geography, geology, geomorphology, urban transportation and infrastructure modeling, the impacts of built form, disaster management, flood mapping, hydrological modeling, forestry applications (inventory monitoring, above-ground biomass and carbon mapping, disturbance, biodiversity, urban forestry), archeological discoveries under forest canopies, signal propagation, visualization and viewshed modeling, and vehicle automation. With such a wide and varied user community, it is critical to have tools that enable the viewing and analysis of lidar data alongside other types of geospatial data. The lidar capabilities within ArcGIS Pro are a good example of this, and this manual serves an important role in helping the large community of ArcGIS users through the improved ArcGIS Pro lidar environment.
In the past decade, remote sensing data has become widely available to the public, and lidar data are no exception to this trend. Wall-to-wall lidar data are not available in the United States, and few states even have reliable repeated acquisitions. However, there is an ever-building archive of lidar data in the United States, which is composed of many disparate lidar acquisitions, all of which have varying acquisition specifications (sensors, altitude, wavelength, pulse density, seasonality, etc.). The United States Geological Survey (USGS) and the American Society for Photogrammetry and Remote Sensing (ASPRS) have invested considerable effort toward attempting to standardize lidar data acquisition deliverables (USGS) and the most widely used binary format of lidar datasets (i.e., LAS data – ASPRS). Determining whether or not there is lidar data available in a specific area can be a challenge and is often the first step in the process. A number of archives are emerging that are dedicated to this purpose, including 3DEP (3D Elevation Program), which recently made lidar point clouds available to the public in a searchable fashion. Section 2 of this manual addresses this topic specifically and is a valuable resource to help users obtain the data they need and understand the metadata.
The main products derived from a lidar dataset are elevation models of the bare ground with features removed (such as trees and buildings), models of the surface that include features, and normalized models of the heights of features (often called canopy height models for forest applications, and normalized heights for other applications). The wide variety of applications mentioned above typically use one or more of these products as inputs to an analysis framework, usually within a GIS. Some user groups also analyze the lidar points or waveforms themselves. For forest-related applications, where the canopy is “pervious”, it is often desirable to analyze the vertical distribution of points within the forest canopy and calculate metrics from these points that are descriptive of the point configuration to enable the modeling of forest canopy attributes and inventory variables.
The improvement to and tools available for lidar processing in ArcGIS Pro have greatly expanded the utility of this package to process lidar data and incorporate products into a geospatial modeling framework all within the same environment. Users can work with LAS point clouds directly and can accomplish tasks from the classification and filtering of point clouds, point cloud feature measurement and 3-D viewing, interpolation of DEMs, calculation of height models and sophisticated 3D analysis and geospatial modeling. This manual walks the user through many of these steps, opening the door to a 3D geospatial workflow.
