While both LiDAR and PhoDAR are 3D point cloud formats, the process of creating each is completely different. The nature of the collection process dictates the structural characteristics of the data and its usefulness for specific applications.
In this blog entry, we look at some of the distinct differences between each collection method, and their ideal uses.
LiDAR – The Good
Active Collection Process
Individual 3D points are collected and processed in real time.
More Return Data
Each point includes a range of useful data including return intensity, return count, and classification (added as a post process).
Data structure has been standardized providing optimal conditions for data sharing and interoperability.
Scanners mounted on aircraft allow for a wide-geographic area to be captured relatively quickly.
Unlike early LiDAR hardware, scanners are now relatively compact and can even be mounted on a UAV.
LiDAR can penetrate foliage and similar obstructions providing a complete 3D representation of the target area. This allows for ground detection even in heavily forested areas.
Rapidly Evolving Tech
For instance, Geiger-mode LiDAR can provide point densities of 100/sq m or greater.
The points are theoretically more accurate, especially the height value.
LiDAR is ideal for generating Digital Terrain Models because, unlike photogrammetry, it can “see” through canopies to ground.
LiDAR – The Not So Good
Traditional LiDAR requires a manned aircraft to house the necessary hardware.
Sensitivity to Flight Conditions
Collection requires optimal atmospheric conditions for flying. The altitude and speed of the aircraft can also effect the point density.
Poor Anomaly Identification
Raw LiDAR cannot recognize anomalies in the data (e.g. birds underneath the flight path)
Inconsistency in Processing
It is not uncommon to encounter publically available LiDAR files that have been erroneously classified
PhoDAR – The Good
Minimal Technical Requirements
It’s a more accessible way of creating a point cloud with hardware that can cost as little as $1,000.
On Demand & Versatile Collection
Data can be collected on demand, in a relatively confined area, and with minimal preplanning required.
Greater Point Cloud Density
Point densities are typically much greater than those of traditional LiDAR
While not natively LiDAR, a photogrammetric point cloud can have classification values applied and can be exported to a las or laz file.
Each point automatically inherits the color from the corresponding images.
Ideal for Digital Surface Model generation since it is unable to penetrate vegetation like LiDAR can.
PhoDAR – The Not So Good
Requires Distinct Features
Points derived from image analysis require distinct visible features in the geographic area of focus.
Requires Surface Variety
Photogrammetric point cloud generation doesn’t work well when there is a lack of variety in surface texture in images, such as the surface of a desert area or large parking lot.
Requires Sufficient Light
Unlike LiDAR, photogrammetry depends on sufficient ambient light. Clear images are required for generating a point cloud, so shooting images in low-light conditions is not ideal.
Poor Ground Detection
Photographs cannot “see” through canopies like LiDAR can.
Shadows and Sky Don’t Work
Point cloud generation doesn’t work well with images that contain large shadows or a lot of sky.
Accuracy Depends on Ground Control
Horizontal accuracy and elevation values are not as accurate unless ground control points have been used in the processing phase.
Coverage is Usually Limited
Photogrammetric point cloud generation isn’t as practical for large area coverage.
There is often inconsistent coloring across a surface area due to variations in the color balance of the individual images
Reflective surfaces can sometimes cause more noise points or anomalies in the data, which would require manual removal. Finer features, such as power lines, may not show up as well as they would in LiDAR data.
Ideal Uses for LiDAR
LiDAR is ideal for collecting data of larger areas and of finer details, such as power lines, pipe lines, and the edges of objects. It’s also ideal for creating digital terrain models, since sensors can penetrate vegetation, allowing for the collection of real ground points.
Ideal Uses of Photogrammetry
Photogrammetry is ideal for surveying smaller areas that contain minimal vegetation. Since it can’t penetrate vegetation like LiDAR, photogrammetry is often better for generating digital surface models, rather than terrain models.
Ideal Software for Both LiDAR and Photogrammetry
Whichever point cloud generation method you choose, Global Mapper and the LiDAR Module are well-equipped to efficiently and effectively process the resulting data. The extensive list of editing, visualization, and analysis tools include point cloud editing and filtering, DTM or DSM creation, feature extraction, contour generation, volume calculation, and much more.