Neither snow nor rain nor heat nor gloom of night...

With the recent snow storms impacting the country, I thought of no better topic than a discussion of weather and Mobile LiDAR.  It is relatively easy to work around localized weather events when utilizing a vehicle as opposed to an airplane or helicopter.  But sometimes, it's absolutely necessary to work in such conditions.

As discussed in earlier posts, LiDAR is an active sensor which uses a laser to measure distance to an object (same premise as total stations - traditional surveying instrument).  Therefore, our system can operate day or night and in virtually every weather condition.  We have several examples of night collections (Downtown Norfolk and I-85/285 in Atlanta), rain conditions (The Narrows - State College, PA) and now snow as shown below.

The image above was captured at our Beaver, PA office during snow flurries.  The image is colored by height to show all the snow in the scan (red dusting of points).  While the image below illustrates the same collection with the snow "cleaned" from the scan.  There are several different ways to accomplish this. But, it simply boils down to the intensity of the reflected light from the snow flakes and the elevation of those points.  Rain and snow each pose various processing challenges, but when you need information, sometimes it takes a little extra effort.

Question of the Day

Typically, when I make presentations on Mobile LiDAR, I take a brief moment to step into a point cloud to introduce the audience to the unlimited perspectives one can take when visualizing the information.  Taking the 3D data and flattening it into a 2D screen capture does not do the information justice.

In today's presentation, I pulled up an interchange system with 4 levels of interstate highway and ramps with a similar aspect to what you see below - an aerial view.  The question from an attendee was (to paraphrase) "how do you get an aerial view from a system mounted on a suburban?"  My response was to make an analogy to ArcGIS and various feature datasets as these were well versed GIS users.  I have had this question in the past but moved about the room to represent the change in perspective.  



Having spatially sound, 3D information allows for an infinite number of perspectives - includes the position of the observer, target and a field of view.  This ability provides the framework for a number of applications including line of sight analysis, obstructions, glide slopes, transportation/infrastructure design and 4D modeling.

Measuring Systems Part 2 - Lasers and Cameras

Background

Continuing with our series on Baker's Mobile LiDAR system (See Part 1), we introduce you to the lasers and cameras.  We will discuss the basic overview and specifications of the sensors.  After all, the information captured with these four sensors is what you really want to see and utilize.

The images below depict an image captured with one of the onboard cameras and a colorized point cloud derived from the laser data and the picture (See our Bedford Springs post)

Lasers

Frequency & Returns
Our vehicle utilizes two Optech lasers - their LYNX Mobile Mapper™ system. The system allows us to collect at different rates (50kHz, 100 kHz or 200kHz) depending upon specific project requirements.

Building upon the technology developed for aerial systems and the need to penetrate tree canopies, the system is also capable of measuring multiple returns of the laser (up to 4). This ability allows for the capture of information behind hedges and through other brush. From the multiple returns, we're able to derive more complete "bare earth" elevation models.

Accuracy & Precision
Basically, precision is a measure of repeatability of a measurement. The lasers have a defined precision of 7 mm.  Surveying total stations, by comparison, vary from 2 to 7mm depending on manufacturer, type and target (reflectorless total stations are generally less precise when used as such).

Often times, that term "accuracy" is thrown around indiscriminately, misinterpreted, misrepresented and, quite truthfully, over exaggerated.  There are a number of ways to measure accuracy and a number of processes that either improve or reduce accuracy.  In the most basic sense, we are realizing raw accuracies from the system itself of between 3 and 8 cm.  Using ground control and point cloud constraint measures, we are realizing accuracies in the neighborhood of 1.5 - 4 cm. *There are a number of dependencies and each project is designed and performed to specifications to meet accuracy requirements.

Accuracy will be greatly expanded upon in a future blog.  We will review what dilutes accuracy, what procedures we employ and how we establish ground control.

Safety
The light produced by the lasers is not visible and is eye safe at nadir.  Therefore, drivers in surrounding vehicles and bystanders are safe from injury by the laser and distraction.

Cameras

We have two 5 mega-pixel cameras on our platform.  They can measure up to 3 frames per second depending, again, on project specifications and requirements.  We can position them forward or behind the lasers.  They are also mounted in brackets that allow for a full range of orientation.  If interested in a sign inventory, the passenger side camera may be positioned forward of the laser facing in the direction of travel while the driver side camera may be positioned behind the laser facing backward.  For assessing pavement, the cameras would be located in the rear and pointing down.

From the images, we're able to develop a range of products from colorized point clouds to movies and attributes.

The rapid reconfiguration of the sensors (both laser and cameras) allows our operators to tailor a collection to a specific set of goals and products.

Mississippi River Levee

Recently, we surveyed a few miles of the Mississippi River Levee south of Baton Rouge, LA using the Mobile LiDAR vehicle.  At first, there were two things we wanted to learn from the collection.  Our primary concern was the ability to capture the toe of slope of the levee with the system - the reasoning behind raising the sensor platform higher than the luggage rack.  As you can see from the screen captures below, we didn't have any trouble with that test.

The second phase of testing dealt with camera settings. Since the sun angle changes rapidly with the vehicle in constant motion, our crew tested different collection techniques and settings in an attempt to have consistant brightness.  Our goal is to limit the patchwork affect that is slightly visible in the roadway of the image above.  With new software we've employed, we're able to then perform basic color matching to smooth out those regions.

Now that we have this information, we have elected to perform an assessment of "soft targets".  We are performing field surveying in support this assessment - the results of which will be shared upon completion. 

Measuring Systems Part 1 - Positioning

Background
In traditional Surveying & Mapping, points are determined by measuring an angle and distance to an object from an instrument over a known point (X, Y, Z or elevation).  We have all seen, at one point or another, a person at a total station locating a rod held by another field crew member - often while we zoom past at highway speeds. 

Now, with Mobile LiDAR, we are Surveying & Mapping at highway speeds.

In order to better understand how accurate measurements are collected from our vehicle, it is important to know the instruments onboard and the function of each.  As individual sensors, they do not provide an adequate solution.  But, when used as part of a system, they provide the foundation for accurate information. 

The purpose of this post is to provide a basic overview of our system.  Additional parts will cover the lasers, cameras and other components and processes which provide a complete solution.  If you have questions, please leave a comment.

Global Positioning System (GPS)
The primary method of location for the vehicle is GPS.  We utilize 2 onboard units to provide the position of the vehicle as well as the heading (having a known baseline, distance and direction, between antennas provides a measure of direction of the vehicle).  The fundamental issue with GPS as a sole (hence I used primary) source of positioning is that we measure a position one time per second.  For those of you breaking out your calculator, that equates to 88 feet per second when traveling at 60 mph.  In that second, our lasers could have measured 400,000 points (covered in part 2, stay tuned).  Therefore, we rely on our second measurement instrument.

Inertial Measurement Unit (IMU)
The IMU measures the attitude (roll, pitch and yaw) of the vehicle, much like an aircraft, at a rate of 200 times per second.  By measuring those changes in direction about the X, Y and Z axis, we are able to calculate the vehicle position at those increments.  Using interpolation, we are able to further refine intermediate positions.

Distance Measurement Instrument (DMI)
The often overlooked member of the measurement family is the DMI.  Barely noticeable and not mounted on the "LiDAR Wing", the DMI has two distinct purposes: determine the distance traveled by measuring the revolutions of the wheel 1,024 times per second and tell the system when the vehicle is stopped.  Since there is drift in GPS and the IMU, the DMI basically determines when the wheel stops revolving.  By measuring the diameter of the wheel and calculating circumference, we also know the distance traveled per partial revolution.

For NASCAR fans:  since we measure the diameter of the wheel at rest, the circumference of the wheel is calibrated while we're driving and GPS provides a good solution.

For non-NASCAR fans: as we drive, the tire will begin to heat and will build pressure thereby increasing tire circumference and impact the distances measured by the DMI.

In a nutshell... one system helps calibrate another system.  In a later post I'll cover what happens when we lose GPS!!! 

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