SGM as an Affordable Alternative to LiDAR February 2016 by Frank Wilson of ControlCam, LLC

1. SGM as an Affordable Alternative to LiDAR February 2016 by Frank Wilson of ControlCam, LLC

2. Overview • What is LIDAR? • What is SGM? • Key Differences • Accuracy Comparison • SGM Examples • Popular SGM Applications

3. What is LiDAR? • LIDAR, which stands for Light Detection and Ranging, is a remote sensing method that uses light in the form of a pulsed laser to measure ranges (variable distances) to the Earth. • Travel time of light pulses can be used to create a three-dimensional representation of the surface • Can penetrate low density objects including trees • The data generated forms a point cloud and is output into a .LAS format

4. What is SGM? • Semi-Global Matching (SGM) is a robust stereo method that is derived from aerial images and can be used to extract three dimensional dense point clouds of a surface • SGM data derived from this process creates a point cloud dataset comparable to LiDAR • It can be exported into a .LAS format to be utilized by third party software similar to LiDAR data

5. Key Differences SGM • Semi-Global Matching (SGM) can be based on high resolution imagery and each pixel can be processed to render a 3-D Point Cloud of high density (150 to 380 points per square meter) LiDAR ~ 172 points per Square Meter at 3” GSD • LiDAR derived point clouds are limited by the sampling frequency of the sweeping beam and the laser beam width (1 to 9 points per square meter) Up to 9 points per Square Meter

6. Key Differences (contd.) • A LiDAR derived 3-D Model is lower resolution and thus lacks sufficient resolution to see surface changes that Semi-Global Matching (SGM) detects • However, current SGM software renders surfaces that have more low level noise than LiDAR surfaces LiDAR Derived SGM Derived Images from the paper SEMI-GLOBAL MATCHING: AN ALTERNATIVE TO LIDAR FOR DSM GENERATION? By S. Gehrke, et al,

7. Key Differences (contd.) • Both LiDAR and SGM methods result in high density digital surfaces, which typically require additional processing or editing before they can be used in an application. • SGM is typically 15 to 30 times more dense than LiDAR • Both can have data classified automatically to determine bare earth, buildings or vegetation content with minor changes to classification rules • The higher density of the SGM DSMs can ease identification of structures in the data, making manual editing less error prone • LiDAR data can be captured regardless of light conditions (even at night) and the laser pulses can penetrate into a forest canopy to measure the ground directly • With SGM color can be accurately co-registered in the 3D point cloud and oblique imagery can be used to reconstruct building facades

8. Accuracy Comparisons • Due to a combination of sensing methods and geometry, LiDAR has a greater accuracy in height than in horizontal position • For high precision work typically 5 cm in Z and 10 to 30 cm in XY • LiDAR point accuracy can also be affected by atmospheric conditions (such as mist or volcanic ash) or by target reflectance Table 1. Comparison between LiDAR and SGM • SGM accuracies are driven by the triangulation accuracies of the imagery, which is typically 0.5 GSD horizontally and 1.5 GSD vertically • The resulting pixel level correlation generated point cloud is photogrammetrically accurate to the same level as the mapping • A USGS Accuracy Assessment of LiDAR found that it had a mean accuracy of 30 cm and variability of +1557 cm and -2464 cm Units in meters. Table from the USGS Accuracy Assessment of the U.S. Geological Survey National Elevation Dataset By Dean B. Gesch, et al,

9. SGM Example • SGM of Mayport NAS in Jacksonville, FL • Not an image, but rather a 2.5 dimensional model of the NAS rendered from Nadir Stereo Pairs

10. 2nd SGM Example • SGM of Port of Palm Beach FL • Also a 2.5-D model, but rendered from both Nadir Stereo Pairs and Oblique Imagery to reduce noise and fill in object sides

11. 3rdSGM Example • Winterhaven, FL • Also a 2.5-D model, but rendered from both Nadir Stereo Pairs and Oblique Imagery to reduce noise and fill in object sides

12. SGM Applications • SGM can be a more cost effect method to do traditional applications of LiDAR including: • Local County Government tax assessing departments usage for cost effectively generating building footprints for tax purposes and then perform YoY change detection • Detection of progress/changes in the Construction or Mining industry • Utility Industry can use Imagery and SGM to detect changes to Right of Ways and assess alternative routes • Transportation departments can use SGM for highway and corridor mapping • Commercial industry can use SGM combined with aerial imagery for a host of business opportunities

13. Questions