Encroachment surveying; LiDAR vs. Photogrammetry.

In the past, LiDAR has been the technology of choice for accurately mapping vegetation growth along power lines. In the last couple of years, however, new technology has evolved to become a serious competitor to LiDAR; Photogrammetry.

The purpose of this white paper, is to use results from a proof of concept project using the newest photogrammetry encroachment modeling-technology, in an attempt to answer the question: Is Photogrammetry a viable replacement for LiDAR in encroachment surveying considering the factors; price, time and accuracy?

LiDAR

Or Light Detection And Ranging uses light to determine the distance of an object from the LiDAR-sensor. The sensor (here: attached to a flying object) sends down pulses of laser, which reflect off the surface of objects below it.

The LiDAR-sensor also contains a GPS-receiver, which constantly measures x- and y-coordinates alongside the sensors’ height above the ground.

The final component of the sensor is the Inertial Measurement Unit. The IMU tracks the position of the sensor relative to the ground, to account for the movements of the object, the sensor is attached to.

Data from these three components is computed, to give a very accurate and detailed 3D point-cloud of the landscape below the LiDAR-sensor. The point-cloud needs to be further processed, to achieve a true view of the landscape/object.

Photogrammetry

This paper will focus on aerial photogrammetry, where images are captured from a flying object.

Photogrammetry uses the x, y, z coordinates of two or more overlapping images, to create a 3D-model of an object or an area. Images from almost any camera can be used in this process, as long as they meet resolution requirements. Photogrammetry 3D-models are accurate enough, to be used as basis for aerial measurements of heights above ground level, and distance between two or more points.

A camera and post-processing software is needed to create the 3D-model.

The project.

The following sections will focus on the POC-project in question, where a stretch of line was surveyed and the photos processed using photogrammetry, to determine the distances between lines and vegetation.

The companies involved are FlyTech UAV (responsible for post-processing) and Remote Operations (responsible for data-capture). 

1. Flight-plan
2. Time spent
3. Post processing
4. Accuracy
5. Data representation
6. Price
7. Conclusion

1. Flight

FlyTech UAV have very few conditions when it comes to the data captured. This meant that Remote Operations did not have to re-think their usual approach to flight-planning.

They were limited to flying during daylight, for the photos to be properly lit. Remote Operations flew 63 meters above ground level, using a 20-megapixel resolution camera. The flight plan that was used, is visualized in UgCS software below.

Requirements for data obtained:

• Type of drone is unimportant (VTOL or fixed-wing)
• Drone must fly in linear motion parallel to line
• 2 runs is enough, but 4 is recommended to obtain the best data set
• Image resolution must be 1-2 cm

2. Time spent

Capturing data for photogrammetry typically takes longer compared to LiDAR. Two factors contribute to this; firstly, a certain amount of light is needed, in order to get photographs with a high enough resolution. Secondly, 2-4 runs are needed, where LiDAR only requires 1 run.

It is worth noting that even though it is theoretically possible to use LiDAR during periods of low of no light, it is restricted to operations with BVLOS waivers.

For this specific stretch of 1,6 kilometers, where four runs was completed, Remote Operations pilots used a DJI Mavic 2 PRO (M2P) and spend a total of 30 minutes flying.

The data was uploaded to Scopito immediately, and sent to FlyTech UAV for analysis.

Approximate data processing times in FlyTech UAV’s software:

• Powerline detection 40 Kilometers/day using one operator
• Powerline detection + point cloud 15 Kilometers/day using one operator

Processing times will often be shorter for LiDAR, as the data is largely processed during the flight. However, to obtain an image where trees and lines are visible, rather than a point cloud, further post-processing is needed.

3. Post-processing

Once images are uploaded in Scopito, they are sent to FlyTech UAV for analysis, and loaded into their software. The first two photos are manually marked to identify the power line and vegetation.

Afterwards, the software is able to automatically process remaining photos, stitch them together and create a complete 3D-model of the line.

Before sending an inspection, the customer has to specify what they are looking for in terms of encroachment; how close can vegetation be to the line, before it has to be marked?

Remote operations were looking for anything closer than or 3 meters away. Once the finished data is returned to Scopito, all areas where vegetation is <= 3 meters from the line, will be marked.

4. Accuracy

There are several possible distance measurements when using FlyTech UAV’s photogrammetry software:

• Distance from wires to ground
• Sag of the wires
• Distance from vegetation to line

The accuracies vary, but since the distance between vegetation and wires is the focus of this paper, only that will be included. This measurement has an accuracy of approximately 10 cm.

After Remote Operations received the finished report, they walked the stretch of line to double-check the results.

The surveying was done in the fall, where most of the trees were nearly leaf-less, and yet even the smallest branches were detected by the software. When asked, whether they would have preferred the accuracy of LiDAR, Remote Operations responded that the data they got from Photogrammetry was more than sufficient. They elaborated to say, that the added accuracy provided by LiDAR, is not needed and simply: “Overkill.”

5. Data representation

Having the data in Scopito proved very useful to Remote Operations, as they could use it to easily identify areas that needed trimming.

At first, they provided workers with the report in print, but this presented a problem, as all the trees looked alike, making it hard to identify the exact location.

Remote Operations then sent out the digital version of the report and presented each worker with a iPad; an approach which yielded much better results. From the digital report, it is possible to pinpoint the exact GPS coordinates of a tree, and open these directly in the iPad’s or phone’s navigation.

Having knowledge of the problematic areas beforehand was especially useful to Remote Operations, as several areas of line was located on smaller islands, which were hard and time-consuming to traverse.
These efforts could now be coordinated, and that greatly reduced the time spent correcting encroaching areas.

Remote Operations’ customer Lyse was very happy with both the report and the final result of the project.

6. Prices

In the first section of this report it was established, that the price of investment is much lower for Photogrammetry compared to that of a LiDAR system.

7. Conclusion

So is Photogrammetry a viable replacement for LiDAR for encroachment surveying in terms of price, time and accuracy?

Price the overall price of Photogrammetry is lower.

Time the process of obtaining and processing data is a little faster using LiDAR. However, since encroachment surveying is a routing maintenance task, it is rarely time-sensitive enough for the difference to be relevant.

Accuracy the accuracy of LiDAR is greater. Photogrammetry is accurate enough to fulfill the requirements. The added accuracy provided by LiDAR, is not useful when looking at encroachment.

Based on the project covered in this paper, we can conclude that Photogrammetry is a viable replacement for LiDAR.

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