- Have you ever wondered how they decide where to put a road that
cuts through the mountains? Or where they decide to put a dam that makes a reservoir? Well, all this and more is covered on the subject of land surveying and today we're in Northern
Colorado at 7500 feet and we're gonna take you on an example of doing land surveying with an unmanned LiDAR system. So stay tuned and learn all about it and more on today's video. Let's go! (intense rock music) Alright, we're loading up the truck. We've got all the gear here. Today were going up to
the mountains in Colorado and we got a job where
we're doing a LiDAR survey of a local watershed in order to generate a digital elevation model and contours and we're delivering this
to a civil engineering firm whose gonna use this data
in order to make plans for work they're doing along the roadway. Let's continue to load up
the truck and get going. (intense rock music) Well, we just pulled up; it's starting to rain here. Before we start flying
today, I wanna tell you, basically, we have a whole system for doing these LiDAR land surveys and they consist of these
three basic big steps. The first step is we have to go out and get ground control points and set up aerial targets, and the second step we
plan and fly the mission. And then the third step, we take the data from the first and the second step back to the office where we process it together. But before we do any of that, we gotta get out of this rain and we're gonna use some of this time to go and inspect and scout out the area before we start flying. (intense guitar music) I'm walking the job site right now; you can see behind me
there's a lot of trees. The client wants no trees in the data set so it's just these topographical map of only the ground. And we also need to find a good place to go take off and land from. (intense guitar music) Alright, this looks like
an ideal place to fly from and what makes this a good place is that there's no overhead obstructions
like trees or power lines and we have a really good view of our whole flight plan. So let's go ahead and
jump into our first step and that's setting up the base station and starting to collect
some ground control points. (intense guitar music) So this right here,
this is our base station and it's going to be collecting data the entire time we're out here. And this is the GPS Rover. It's communicating with the
base station at all times and enables you to get
two centimeter precision in all the data it records. Now to tie this into the sky, we need to paint some aerial targets that'll be visible to the LiDAR data recorded from the drone. (intense guitar music) This aerial target will
show up very bright in that LiDAR data. Now let's record the accurate location of where this is located. (intense guitar music) Got it. (intense guitar music) So we just finished capturing our last ground control point. Now we can go back to the drone, plan the mission, and take off. (intense guitar music) So this right here, this is the LiDAR. Let's get it installed here. Now we can go ahead, start flying and getting data. (intense guitar music) We're in the sky right now, flying 100,000 laser pulses every second. (intense guitar music) Once it gets done with this flight line, we're gonna bring it home, land it, switch out the batteries, and pop it back up. (intense guitar music) Alright, we just finished
doing that drone flight, got all the LiDAR data, got everything packed up, and we're gonna head
back to the office now, process the data, and show you all what it looks like. Let's go back to the office. Welcome back to the office. We just got done flying the LiDAR drone and collecting the ground control points and now we're taking both those data sets, putting them together
to derive our results. So let's go ahead and jump right into that and take a look at that
raw point cloud data. [Indy] Here we're having a look at that first LiDAR data. It looks frickin awesome. So right now, what you're seeing, if you don't know, this is the raw point cloud data. The red is high, the blue is low, and color's depicting elevation. If we scroll around a little bit, you can see a lot of detail, a ton of detail in this data. This is what you're gonna get with unmanned aerial
LiDAR data collection. It's very high resolution, very high detail, and very high fidelity. Now let's go ahead and take a look at the accuracy of our LiDAR data. In order to do that, we're going to look at the intensity view of the LiDAR data, which will reveal the aerial targets and then we'll be able to compare those aerial targets
to the data we captured from the GPSRGK system. [Indy] I just imported
the ground control points into the data set, so now we're gonna be able to see them laid right on top of the intensity view of the LiDAR data. (light rock music) Here's our first aerial target. Now I'm gonna go ahead and look straight down
the plane of the data and just see where that target falls. It looks like it's right in the middle. Now in order to get an
even better perspective and view, we can do something
called a cross section, which is taking a little
slice out of the data and then we can actually see the point laying in the data. It's a little big right now, let's shrink that down. (light rock music) Okay, so it's basically
inside the data set. I'm gonna go ahead and calculate. So even to this middle point, we're at .036 feet off. So .036 feet, this is about 1.1 centimeters. We're spot on. Let's go ahead and take a look at one more ground control point and then for the rest of them, I'm gonna go ahead and
just calculate them all off the video. [Indy] Here's the aerial target that you saw me paint on the ground. And again, the point is basically right in the center. So it's good on the X and Y axis. Let's look at the Z axis. (light guitar music) Alright, the closest neighbor here is about .04 feet away. Now, .04 feet is 1.2 centimeters. I went ahead and calculated the area from all the other ground control points throughout the whole data set and they were all about
one to two centimeters. So this looks really great for the global accuracy of the data and the precision is about
two to three centimeters. So I'd report this to be about two to three centimeters precise and accurate across the whole data set. Okay, now you've seen the data, you've seen the accuracy of the data, let's go ahead and look at the ground classified portion of the LiDAR data set. [Indy] This is stripping
off all the trees, all the vehicles, everything that's not ground. And you can see, there's an incredible
amount of density of data outlining all of the ground throughout the entire data set. This is actually what's
unique about LiDAR data. You don't get this doing photogrammetry because when you do photogrammetry, which is photos and you
stitch those together to make a 3D model, you have all the trees and the trees are just
blocking the ground, and you're not seeing
the ground really well. But with the LiDAR data, we're able to actually
get points to the ground underneath the canopy of the trees, then from this is what we're gonna derive the digital elevation model. So let's go ahead and just jump right into the digital elevation model for this data set. [Indy] This is the digital elevation model for the data set. It has no trees, just the ground, and it's a TIF representation
of the LiDAR data. This is very easy to
import into other software cause it's only an image, it's not the raw point cloud data, it's just an image of the heights associated with the ground. And for this I did a one foot spacing and interval for the DEM. We actually have something really unique with this software. We can turn the DEM into a three-dimensional model as well, and it looks really cool. I'm gonna go ahead and just take that 3D view of this data and put it in right now so you guys can see exactly what that looks like. [Indy] It looks really awesome. I mean, you can see some- I mean, I don't even know what this is, some sort of road but there was no road that was over there. I walked over there. So this is maybe some
sort of drainage feature. And over here, underneath all these trees, there's a couple more
drainage features, as well. Very important information here. Now the final piece of
information we wanna derive from this data here is a one foot contour model. I'm gonna go ahead and show you what that looks like now. [Indy] The yellow lines
are one foot intervals, then every five feet you see a blue line, and every 25 feet, I have a red line. It looks very detailed, very accurate, and we're also able to
import all this data into CAD as well as GIS software and so I think it's
actually an important thing to show you right now. I'm gonna go ahead and
import these contours into QGIS, which is an open source, free GIS software. [Indy] And you can see right now that lines up perfectly. If we go ahead and turn on the Google Hybrid base map, you can see all of the contours line up with the area that we were surveying in. Now our ground control points are definitely way more accurate than the base map from Google Maps, but it still does a good sanity check for you to see your data overlapped, overlayed on something else like Google Earth and Google Hybrid. (light guitar music) Alright, well that was the unmanned LiDAR land surveying video. Hope you guys enjoyed it and you know what, I did something really
special for this video. I went ahead and hosted
that data set online. So if you look into the notes in the description below, you're gonna see a link right there and that will lead you to seeing that data set for yourself. So feel free to play with it and if you have any questions or comments or ideas for videos you wanna see next, just leave them in the comments below; I'd love to read them. And as always, please like, subscribe, share the video with your friends and I'll see you on the next one here on Indian Drones. (intense rock music)
Thank you for the video! I will be reaching out to chat. Iām the Remote Sensing manager of a survey firm in Portland, OR.
Woulda been cool to see you process the trajectory too, have you tried Riprocess and found it lacking or do you just prefer this other software?