Point cloud data

Point cloud data is any data collected as the (x, y, z) location of a surface point based on some sort of focused energy return. Point cloud data can be created using lasers, radar waves, acoustic soundings, or other waveform generation devices. The spacing between points is arbitrary and dependent on the type and position of the sensor collecting the data. In this book, we will primarily be concerned with LIDAR data and radar data. Radar point cloud data is typically collected on space missions while LIDAR is typically collected by terrestrial or airborne vehicles. Conceptually, both the types of data are similar.

LIDAR uses powerful laser range-finding systems to model the world with very high precision. The term LIDAR or LiDAR is a combination of the words light and radar. Some people claim it also stands for Light Detection and Ranging. LIDAR sensors can be mounted on aerial platforms including satellites, airplanes, or helicopters. They can also be mounted on vehicles for ground-based collection.

Due to the high-speed, continuous data collection provided by LIDAR, and a wide field of view—often 360 degrees of the sensor—LIDAR data doesn't typically have a rectangular footprint the way other forms of raster data do. LIDAR datasets are usually called point clouds because the data is a stream of (x,y,z) locations, where z is the distance from the laser to a detected object and the (x,y) values are the projected location of the object calculated from the location of the sensor. The following image, courtesy of USGS, shows a point cloud LIDAR dataset in an urban area using a terrestrial sensor as opposed to an aerial one. The colors are based on the strength of the laser's energy return with red areas being closer to the LIDAR sensor and green areas farther away, which can give a precise height to within a few centimeters:

The most common data format for LIDAR data is LIDAR Exchange Format (LAS), which is a community standard. LIDAR data can be represented in many ways including a simple text file with one (x, y, z) tuple per line. Sometimes, LIDAR data can be colorized using image pixel colors collected at the same time. LIDAR data can also be used to create 2D elevation rasters. This technique is the most common use for LIDAR in geospatial analysis. Any other use requires specialized software that allows the user to work in 3D. In that case, other geospatial data cannot be combined with the point cloud.