 So, thank you for having us. I know some of you were here earlier with my colleague Samuel, but we're going to be discussing a little bit different on the drone and geospatial data. We try to be as more educational as possible, and what are the use cases and best practices. My name is Gord Katherhout, and I'm here with Jaume Katherla. We can do this in Spanish, if you prefer. No, sorry, not Dutch, no German, but anyway. So, real quick, who we are, we're part of MD Group. As Samuel mentioned, for those of you who are not here, MD Group is a French family owned association, three associates who own it, and we have different production centers in the US, in Germany, and in France. And here's where we are. For those of you who are here before, you saw it already. Same thing. This is where we are. We produce drones in Siegen. We produce electronic devices in Paderborn, and payloads in Hansville, Alabama, in the US. And finally, we do R&D for LP360, our software. These are our products, so drones, ventilators, both in Germany, and payloads like this one. I'm going to show you real quick later as well. As Sam mentioned earlier, this is a LiDAR product with cameras, which allows you to do LiDAR, photogrammetry, point clouds, and all those cool stuff. And LP360, the software, which is what we're going to talk a little bit, not only the software, but what are the best practices for obtaining clear data and data that actually you can process, analyze, and be useful for decision making. These are our products, obviously. We need to do some publicity advertising. Different products that we have, mostly for UAV payloads, but also for mobility. Depending on what you want, LiDAR only, photogrammetry, or both, we're pretty sure we have the solution for you. And as Sam mentioned, and I'm going to do real quick as well, software is key. We see more and more that people will rely on software for everyone in our lives, obviously. And for data, it's obviously the same case. And we try to be as diagnostic as possible. So as long as you bring a LIS file into the software, LP360, you can do pretty much whatever you want. You can analyze data, you can do volumetrics, you can do measurements, you can do classification of buildings, grounds, ground floor. You can do classification of vegetation. You also can do MDEs, DMs, DTMs. You can do crossing sections, a bunch of different things. With all that, let's get into it, into the geospatial use cases. And I'm going to give the word to Jami. We try to wrap up the presentation around what are the typical use cases of geospatial, mostly lighter and photogrammetry. And the first one is cartography and topography. Jami. Hello. Do you hear me? Yes. Okay. Then we can go. My name is Jami. I'm mainly the technical guy, especially I give support here in Europe. This means that if you ever have an issue, highly possible, welcome to me. As my colleague mentioned, the software was developed like 15 years ago in U.S. And the main focus of the software was to process airborne LiDAR. Through the years, we started to add more and more support for other platforms or other sources of LiDAR. And now you can process and analyze different sources, either if it's airborne LiDAR, if it's static laser scanner, mobile mapping, and the most recent that would be the UAV LiDAR acquisition. Now, I'm going to go through the software and the different use cases. I will go a little bit quick because we don't have much time. But if you have any questions in the end, I will be able to answer all. Now, what I'm going to show here is what you can do with our payloads and the software. But most of these cases you can do it with just the software. Like if you have the data acquired from any different source, you can add it to the software and process it there. Now, the first case would be a typical topo mapping or a classic one where the client would want to see the background, would want the ground classify, extract maybe digital elevation models, contour lines, et cetera. And here we have, for example, in this case, it's a typical case of the client wants to acquire the data for an area, extract the ground, extract the buildings, this means some classification on from there generates some deliverables. In this case, the project, the aim is to get the contour lines for this area, the digital terrain model and the ortho photo. Okay. And the first thing would be the ground classification. You can do it inside the software. After you get your data into the software, you process, you do some geometrical corrections to your point plot and you can perform the ground classification. This could be the result, mainly the ground classify only. Like you can see the whole with the building. Okay. The next thing would be the DTM generation. In this case, would be digital terrain model that would be a surface only with the background. And again, there is a tool to do it. I'm just showing the tool from the software. And this could be the result. The surface, again, without trees, without buildings, without any other feature that is not the background. Later, the contour lines more of the same. There is the tool there and you can extract it. This would be a classic use case of the software. The next thing and the last thing for this use case could be the ortho photo. The software has a model for photogrammetry. And if you use one of our pilots, it's totally integrated. You can go process the LiDAR point cloud and at the same time create the ortho photo. And this is how it looks. And this could be the final result. Next use case could be power lines. This is a very common use of our pilots and also the software. The idea in this case is like the user want to get the power lines, classify the cables and see if there is any, usually it's vegetation, but any feature that is moving next or near the power lines. In this case, we surveyed 220 kilometers of power lines in Brazil next to the Amazonas and we did 128 flights. What you will see here is a cross section where we can see the power lines classified and the cables. And actually what the final client care is not about the point cloud or the classification or the extraction of the power line. What he care really is what we are seeing here. That is we classify the point cloud across the cables in different colors in this case with radius of 10 meters, seven meters and five meters. And if there is any vegetation growing closer than five meters, we will point it. We send a list of points to the client where he needs to send the team to chop the trees. Mainly. Could be this one. And here are the tools that were used. Finally, I will talk about the railway extraction. This is also a very common use. You can use the software to extract the tracks of the railway and the center line. Now, then in this case, I have a use case of 25 kilometers of railway survey in Denmark. It was 16 flights and what the user wanted actually is only 100 profiles of the railway. Then you can see the project here. And the first thing that we did is to extract the profiles. Actually, this is what the user care. Save files with the profile every X amount of meters and later to extract the railway. In this case, we extracted the top part of the railway and the center line. And it looks like this. This is a cross section. One side of the railway and the other. One track and the other. Finally, the last use case and this is the most recent is like the idea to find what is below the canopy. In this case, what we tested is cards below the canopy. This means that you can fly about an area with trees. And in real time, you can stream the data to a workstation. In this case, it would be a computer in the field. And at the same time, analyze if there is any object below the trees. In this case, the object was these cards, but you could use your imagination for what kind of things you can detect under the canopy. This can be used for defense or can be used for search and rescue. Finally, what you can do with LP360 is if you have a streamlined production of an extraction of features, we have a QAQC model that what it does is like if you have several or different members in the team processing at the same time, you can have one of the team members analyze all the data produced, put comments and share back these comments with the team. And finally, I'm going to talk a little bit about the workflow of the processing for our sensors. Everything is done in LP360 and I divided in three steps that you can do. The first one would be a basic processing. In this case, what the client just wants is they already have many softwares. They already have everything and they just want the LAS and they want to get out of the software. Then they just need to input inside the software all the raw data that comes from the drone and they will get their point cloud. A second one would be a user that wants to work a little bit more inside the software. Then they get the point cloud that they produce in the first step. They will apply some geometric corrections like for example, strip adjustment or they would compare with some control points and see if there is any bias. And they will just get an improved point cloud geometrically and also a report of the quality of their project. And finally, for a user that likes the software and likes to work on the software, they can get this point cloud and extract different features, classify the data, create orthod like deliverables, create the ortho photo, and get the final products that the client might need. Again, and this I insist, if you are a user that could be interested just to get the LAS or the point cloud, you could do it in the very first step. And finally, these are some key points about the data processing. It's a little bit of a bit of a challenge to do the processing. It's a little bit tricky to do the processing and talking like this, but it's important to have clean data, precise information, hand definition, detection to analyze the data that you acquired. Again, if the input data is bad, the output, you don't do miracles and processing. And of course, from there you can extract the ground, get areas that are dangerous, identify and visualize. And that's pretty much. I hope that it was short and sweet. You learned something today. If you want to learn a little bit more, you could come to our booth and we could have a session or I can show you our different products. Thank you.