Visualizing lidar datasets using QGIS on Research Desktop (RED)
We'll, go ahead and get started so, this. Is I think our sixths, in the series of the scientific visualization workshop. Series and we're. Glad to have Justin, Peters here to talk about Q, how do you pronounce that Q just yeah. All, right and running. That on the. Research. Desktop. The red research desktop, so go. Ahead thanks. Bill a. Couple, things I might, add in addition to my, research. Analytics. Staff. A full-time staff member I'm also a PhD. Student. Here in size information, science, department, and, a, muscle research affiliate, of the Indian geological, and water Survey so we'll be using some of their data today so I want, to make mention of that long. Title lidar. Elevation data, and aerial photography visualization. Using QGIS. On research. Desktop, so. Let's. Get started I really only have a few slides I'm gonna work through and then I'm going to try. Really hard for, some live. Demos because I love living life on the edge and nothing can ever go wrong on live demo so we're, going to try it so we've got a few objectives, for today I'm going, to cover what. Is light our data and then. What can I do with the PI point, cloud data that's. Acquired from a lidar data acquisition. Some. Resources. On where I can go grab some of this data and then. I'm gonna. Actually. Work through using, some tools for visualizing, elevation. Data I mentioned, on QGIS. On research desktops, so the. Slides would should go relatively, quickly and we'll be into the demo, phase of the. Presentation. Pretty, quickly so I won't be just, sitting here talking very, much we'll be actually. Working through some visualizations. So. Let's. Start, what does lidar data, I, love, Wikipedia, so I'm gonna go grab their answer. To what, is lidar, data. For. The sake of today and the. Workshop, today I'm gonna focus. Primarily on using, the data rather than diving. Into, the weeds as far as, what. All the technical, detail. Are behind a point cloud data set, but, it is worth mentioning that. The. Definition, so that we can I guess, determine, what uses light our data is useful for and then what. Data. Are what uses you can't really use it for but, it's used it's derivative, data is used for, visualizing. Visualizing. So, let's. Start with, what the definition, is a. Definition. Is the. Surveying. Measures, distance, laser lights and measuring, reflections, with a sensor, the, sensor can. Be I, guess, very technically. Advanced, and my. Internet connection is unstable, all right that. Makes two of us, all, right, so. Okay back. To the definition, and then the sensor as far as how advanced it's the sensor is it, can either classify, these points. Based on how long it took for the, reflection. To come, back to the sensor or what. The intensity of that return of that laser pulse is and kind, of classify, these points, so. We're, going to look at a couple that I pulled up already. We're going to look at a point cloud here. Of campus. And the. Definition, it really is are the yeah. It's, not really as high definition as it is on my screen so it. Really, doesn't look as nice, of a visualization as it is here but you have to take my word for it what we're looking at here this. Is the Welles, library, east tower. West. Tower. 10th. Street and Jordan as this rotates. Around we're, actually the, east, tower is back here the west tower is back here you can see it's, actually a series, of points, that are. Like. I said they're returned from a laser pulse and they're, they, capture the x y&z, so basically a last, file a light our file at point cloud is a series. Of XYZ. Coordinates, of XYZ points, it's basically, just a text file a rather, large text file as a matter of fact when we look at it we, are only rendering. 1 million of these points right now this point, cloud itself, has 41, million, points. In it so we're, only scratching. The surface only visualizing. A very small one out of every 40, points, that, are actually contained within this data set so what. We're viewing here is not really the full fidelity.
Of The data set but it's an online. Cloud. Viewer that you could view and access point, cloud data directly. From your browser so. We're looking go ahead yeah you got a question. Okay. Yeah I can do it great yes. Perfect. Good idea. Alright, so this is a well just an example of what a point cloud looks. Like if you were to just render the point cloud itself so I mentioned. In the, onset, one of our objectives today is to identify what, you can do with point cloud data and what you really can't do with it, because. These files are so large also, this. Is a 1.1. Gigabyte, file. Size for this one small, geographic. Extent one small area it's a rather large in terms, of file size and in, terms of points. For, over 41, million in there so. Software. Or a web, browser to read through a 1.1. Gigabyte, file, and then, read all 41, million, of those record entries it's a pretty arduous. Task, for most software, of her browsers so. Using. The point cloud itself has. Limited, uses. You. Can and, there are several. Proprietary. And commercial, software, that. Will use the point cloud in its native format, but. Today we're primarily going to take this point, cloud and turn. It into a digital elevation model. And use those digital elevation models, for some visualizations. So. Let's, go back to the PowerPoint I'll work my way through these. Quickly. And then. We'll get to some of the live demos, of using, some of this elevation. Data derived, from lidar. Data. Ok. So I mentioned what, can I do with a point cloud you can do a. Lot. Of analysis, given the right software with. Point. Clouds however, I. Mentioned. It's very. Resource-intensive, so, today we're going to primarily look primarily, look at derived. Products, from the lidar, data namely, a digital, elevation model. Hillshade. Model, slope maps and an. Aspect, maps I've. Included on this again. A Wikipedia. Entry - a digital elevation model. But it's worth pointing out a digital. Elevation model, can mean many things depending, upon you, know what you're doing with it I. Wanted, to point out here that. No. Universal usage of the term de M digital. Terrain models, and digital. Surface models, are similar. But, terrain. Model could be anything on the earth whereas. A surface. Model is the. Most commonly. Used digital. Surface model is most commonly used. Name. For a digital elevation model, that we're going to be dealing with here it's primarily only dealing with the, last return, from, the. Laser. Pulse so the, very last return. Will be the the bare earth or the farthest away from if you're acquiring from aerial, photography, or if you're acquiring from a aerial. Vehicle, if you're acquiring aerial lidar. From an aerial vehicle the last return, will be the one that it takes longest, to get back to you, by. Specifying. That you only want to work with the last, return, of this point data you can determine. The. Digital, elevation model, or the surface model only the surface model and I'll show you that in, some of these tools I work as I work through here we'll we'll. Go ahead and and do one real quick this. Is just a random place in Bloomington, I went. Through and read the point cloud I want. To either, look. At it 3d. And. I. Want to renderer. Only. The. Ground, so. Each. One of these points that are in this point cloud have, a classification, you, know based on what they are some. Of the software and the vendors that collect this data we will go through and classify each of these points that come back and they'll. Give it a classification, so, that we can go through and look at I only. Want to look at buildings. Or, I only want to look at that ones that classified, for buildings but I only want to look at vegetation. Or, I, only want to look at the. Digital or the bare earth so. In. Addition to the X Y Z value. Obtained. By this lidar. Data and in this lidar point cloud there, are also a classification. And, at you of each one of these points. Alright, let's, go back to the PowerPoint real quick. Okay. So I. Can. Grab, only. Like I said only the. Ground. Elevation, and turn that into a digital elevation model, I can. Use that digital elevation model, to create. Additional. Products, like a hill shade a slope map or an aspect map let's. Look at what. A. Hill. Shade looks like real quick.
Will. Generate, some of these, but. This one in particular is hosted. At the indiana. Geological, water serve ages catty-corner back here this is a. Hill. Shade map that is hosted, on there and the indiana map and you'll, see as we get a little closer. The. Resolution, gets much better and we've, used that digital elevation model, along with an input. So. You know that never goes wrong on live demos, I, may. Be asking, too much of my laptop, here, anyway. You get the idea a. Hillshade. You. Specify. And azimuth, and a. An angle, to the Sun and you can see here that it looks like the. The. Angle I think that you used 45 with an azimuth of, what. 315. Just, 45, degrees, short of. 360. Where the the, shade the, hill shade is actually showing shades or. Yeah. It should it's showing, shade on, the. Exactly. 180, dr yeah 180, degrees. It's. Coming from the sun is coming from 315. So 180 degrees from, 315. Is where the actual. Shadow. Would show up so. Let's. Go back to the PowerPoint, you're. When, you're creating, a, hill. Shade it's a 3d representation representation. Of, its, surfaced. With, the sun's relative, position. Taken into account for shading an image so, you will actually specify, and this, was done by the India geological and water Survey. You'll. Actually specify, where you want the shading come from and what angled the Sun, is that to, you know make that hill, shade and depending. Upon what your inputs, are that can look totally different so if we gave it a an. Angle. Of the, Sun, coming from 45. Degrees the shadows, would be on the complete other side of the. Other. Side of well, of the image. Slope, map and aspect. Map we're going to create these I don't have any examples, to show you real quick so, I'll. Just, give. You the definitions, right there. Basically, slope map you. Have an option of specifying whether, you whether you would like degrees, or percent slope in it it gives a color for each value. Based. On what the. Slope. Is, we'll look at a couple of those also. Aspect. Similar it's the downward, sloping terrain from, 0 to 360. Or, 359. 9. Here. Are some, examples, of what each of those might look like depending. Upon the terrain. Elevation. Digital. Elevation model. So, what we're looking at first there the. Slope, the. Hill and in, the aspect and multi, multi-directional. Hillshade. Kind, of. Shows. You what I was talking about that the multi multi-directional, the, shadow can be coming from several different locations, instead, of just one angle and then. Some elevated, tinted. Hill shades there. Alright. And then as far as acquiring. Data so the, other objective is to let, you know that this data is out there and then, how to go about getting it, this G, is dot I you didi, you is the NES spatial data portal one of the. Resources. That we, manage that research technologies, to enable. Access to this, data it's. Public publicly, available so I'm. Just going to walk through quickly how you might go acquire some of this data some of this elevation data. So. If we download. Multi, file download, tool it takes me to a login screen my, credentials, are saved so I'm going to log in and. I'm, just going to say search by files. And. Use. My GPS, location. To determine where I'm at. And. Is. That even gonna work here no. All. Right. Let. Me Ken okay. So show, me some files, show, me ISD, Pyles files, for this extent.
When. I get to this screen it. Passes the coordinates. Of where. I was on that map and it says these. Are the files we have available in the Indiana spatial data portal, we, have on Indiana, map data. 2011. We have the lidar files the individual, last files so for, that area for that map area that we were just looking at that, individual, file is your. Light our file that last file you, could use that map navigation, screen to go determine, another location, and get the exact file you're looking for. In. Addition to that the. Raw last, file we have some, other, datasets, available. The. Digital. Elevation models, are right here and imagine format or, we have. A mosaic. Of the whole county noticed, that you can go get a small little section a small little tile for two. Megabytes, or you can get the whole county, for, 1.47. Or 1.4. Gigabytes so. It's, really up to, you as far as. What. You would like to gather or what you would like to download from. Here the. Reason I'm showcasing. Our using research, desktop, today is because some of these elevation, datasets can get really large and as. We get to the research desktop, I'll show you how, you can actually download these, directly, to. The. Research technologies, infrastructure. So, that you don't have to worry about saving. Gigabytes. Of data on your personal, machine you can save this on a data capacitor, and use, tools like QGIS. On research, desktop, to. Do your processing, and not, really tax your local machine. So. Just, an example on some of the data that we have there there's also ortho, photography, data. Various. Sets, of aerial, photography. Various. Sets of lidar data we. Have some Monroe County, local data sets so, it's. A good resource if you're not aware of the Indiana, spatial data portal, to, keep in mind, get. Together or, to get data, as. You work through some of these projects. All. Right I don't, think I have many slides left so we'll get to thee. Okay. Last. Slide so some of the tools we'll be using today I mentioned, research desktop, if you. Do. Not have a carbonate, account. You'll have to set up a carbonate account to get a research desktops a research, desktop, account. QGIS. Is the GIS, software going to we're going to be using today and quick. Note QGIS. Is an open source. Software. That, runs, on Linux, Mac and Windows which, makes it very versatile, so. It's. Kind, of up and coming and not really old. And it's highly being worked on so. You'll. See some of it today a couple. Plug-ins, for, QGIS. One. We're going to you to create a 3d, visualization. Near, the end is this QGIS, 2/3 j/s plugin. And then, a plugin we're going to use to. Bring. Data right in directly from the Indiana map, and. Then. Last. Tools this last tools viewer is what we were looking at earlier last tools is also a free and open source software for. Using. Lidar, point clouds. All. Right, yeah. Go ahead. Yeah. Rotations. And translations. Yeah. As. You're flying okay. Yeah so okay school, Scott asked. As I'm flying along collecting, this data how, do I relate. That data to a point on the earth is that what you're asking yeah how do way yeah. Okay, yeah. You ever been, on an airplane that has a little, monitor. In the back of the. Chair. In front of these it shows you where your airplane is at yeah. Well it knows where it's at it knows where that airplane is that from high from. From, GPS. Yeah. So as you. You, know the exact time of where you're at what GPS says you're at at that time you. Know where that point is right you've also got a bearing, a distance or an azimuth from where that's. Lidar. Is coming back. Yeah. So. We. Can we can sidebar, on this a little later it doesn't really have much to do with the visualizations, but if you want to get into the weeds of light, our data, point cloud so I'll be happy to another, setting yeah. That. Satisfactory, yeah okay great. Yeah. I want to get to some of those visualizations.
I Guess today being. A visualization. Workshop. All. Right so let's, start, with. Research. Desktop, I should, probably start from scratch. Discard. And. I should probably start, from scratch as far as. Research. Desktop, also, show, show you how to launch it and what you'll start with and some of the things we'll. Get to some of these visualizations, so, let. Me. Get. Out of there. All. Right blank slate when you log into. Thinlinc. This, is what you'll log into and. It, that knowledge based document, that I shared the, link to the knowledge base document about research desktop, will. Actually walk you through how to get this client how to install it and how to log in but essentially. This turns your machine. Into, a similar. To a. They. Called like a. Remote. Desktop session, for. Windows. It's, basically, like a. Thin, client well it is a thin link thin client so. When. You log in type your username, password and say connect it'll. Pull. Up the cast duo authentication. Then you'll be launched into a screen just, like this so this, is what. You'll get by default as. Soon as you launch research. Desktop. The. Great thing about research desktop, is I've worked, in research technologies, for many, years now and the. Research, infrastructure, that research technologies, provides is great. But. Coming, from a Windows background, a GUI. Background, you actually had to know how to get into some of these resources. Like, scholarly. Data archive like the data capacitor, and. Like. The supercomputing, systems like carbonate, what we're doing with right now when. Well. Car step stop came on board and then this assess the successor, to that research, desktop, what we're looking at here it. Provides a GUI to all of these resources one, graphical, user interface, that will allow you to use all these resources, and, software. On those resources. In, a fashion, that's similar to. What you may be used, to or what I was certainly used to using, windows so. Like. The the. Data capacitor, there. Is no, limit. On what you can throw as far as data in the data capacitor, I've got all kinds of data in here and they're 396. Point 2 terabytes. A file, storage. Space left available but. It essentially turns it, into a right click copy, right. Click paste. You know copying. Files from either the scholarly data archive, to the data capacitor, or to your home directory. On, one. Of these supercomputers like, my home directory right, here on, carbonate, I can say paste and you know copy that rectly from the, data capacitor, and put it on my home drive or vice. Versa. I've. Also got, on this research desktop, thin drives so. That, the. Chip with me. You. This. Thin drives application. Will allow you to actually. Also, mount, local. Disks, so I've also got in the same user interface a D, Drive mapped, that. I that is on my actual local hard drive here that I can go grab data from so it's, like bringing all these resources, together and one user interface, really makes it a, really. Powerful system. So. Let's. Let's. Start using. Some of this data we got. We're. Looking at QGIS, today so from the applications, menu and.
But There's some slow, lag time I think it may be my internet, connection. From. The applications. Menu, geographic. Information systems. Folder there's an option for QGIS. It's. Going to say ok it may take a minute or two to start up that's fine we'll let it do its thing. Okay. And there we have QGIS. All. Right you, got a blank, slate. First. Thing we want to do is, remember. We're not going to be working directly with the last class the, last point cloud' we're going to be working with derivative, data so. I mentioned, the, data. Capacitor. I. May. Minimize this real quick. That's. Where I have, much, of my data that we're going to use today or that I've already downloaded and, staged and here's the actual file path in, data. Capacitor, to scratch, space and then my username I'm, just going to copy that real quick and then I'm going to. Bring. Up QGIS, again. Bear. With me here I'm going to move that task bar out of my way let's. Put it over to the left okay. Back. To QGIS, okay. Now I'm going to add that data so I've got data staged, in the data. Capacitor. I'm. Going to add a raster, datasets raster. Datasets that's, just this button right over here and then I'm going to go. To that scratch space and, I've, got a. De. M for. Orange County, Indiana, in here, I'm going to open. And. We're going to take a look at it this, is again the de M was derived from it, took an input, of that, lidar data and. It's. Create. And we created a de M from the last point cloud yeah go ahead. PTX. Know. It was dot la s the, actual tool that was used or, in. This case for the DM that we're going to be looking at was a, last. De, M is the actual, tool. And that's last tools that was created, so. Last. Tools there we go last tdem, so this. I mentioned. Last tools this tool itself, takes. A last, LasR, l AZ file, which is the native format of the lidar point cloud, it's. Just ASCII text XYZ. It takes that goes, through a 10, methodology. Triangle. Triangulated. A regular. Network, is what ten stands for and creates, a basically. A mesh of all the points and then. From, the points it creates this continuous. Raster. Image. So it's not a series, of points it's a continuous. Raster. Image I. Don't. Think you lose accuracy, but. If there's no data, so you've got a point here and a point here it, will, interpolate. In between those points you know what an actual elevation will be if it's you know one point of four, hundred and one point of 401 in, between that it's going to interpolate, that value, so not, losing any data but. It's using only the data you do have in that point cloud to kind.
Of Create data create. A continuous, data set instead of a point here point here point here does. That answer your question okay. All. Right the. EEM came in so this is what we're looking at as far as a digital elevation model, the actual values, that you see down here and your panel. Those are feet so in Orange. County, the. Elevation, ranges, from 494. Feet or. It's very dark, to. The higher light, area, an. Elevation, of 851. Feet. This. Digital elevation model, will enable us to create some of those other products, I showed you like the hill shade so let's. Go ahead and quickly walk, through how, to create a hill, shade since we're on that so, from the raster, menu up, top we're, going to say analysis, and. Diem. Terrain. Models, touch. Up with me. I'm. Gonna launch that tool. And. I'm not sure if this is slow because the internet, connection, or what but that. Would make sense so. You specify, your, input. De. M and then, I mentioned. You. Specify, the azimuth, and the altitude of where the lights coming from I also want to give this some vertical exaggeration in. The Indiana we don't have a lot of relief. So, in, order to make this an actual 3d. Hillshade. That has that, show some relief I'm going to say exaggerate. This Z, three. Times and, I'm. Going to run this. Oops. I did select an output file, but that's okay it should run. Okay. I need, to specify the output. And. Again, I think this is the, Wi-Fi. That's so slow not the actual machine I think I have yes I do have my scratch, space in there and. I'm. Just going to call it. Out. HS. Alt, hillshade. And. Give. It the TIF extension. And. Save. That file and. Run. It and. This time it's actually running I've. Tried this before it's, a whole counties. Worth it, we're creating, about. A gig a bit our one gig file a file of a gig size so, it takes a little bit but not too long so, I'm hoping I can just sit here and talk for a moment. Or two and it'll pop, up but. It's. Running on carbonate, yes. Research. Desktop runs on company yes good. So. Okay so good point digital, elevation model. Only. Uses, the last return, we're only using bare, earth so we've stripped, out all those from that point cloud that had the trees and had the buildings those.
Points, Had classifications. We said only use. The. Points that had a classic, hit classification. Of grounds. To, create, this digital elevation model, so those, were removed beforehand. Okay. A process, completed, and we've created a hill, shade here, and. Okay. And close we're. Going to zoom in and take a look at some of these or, look look at this real quick as. Far as visualization. You. You. Yeah. Just random spots. Concede. You know driveways. Let's. Go back a couple I want, to look. At. Excuse. Me. And. It's, paying around till. We find something interesting I guess. But. You get the idea so we specified. Again, an angle, of the shade. Coming. From or the angle of the light coming from 315. We, could go through and create the, exact opposite, instead of the shadows. Being on the what's, southeast, of all the hills or all the elevation, the, shadows would show up on the other side that's a that's a hill shade Jim, this is a kale shade generated. From a digital elevation model, the, digital elevation model, was generated, from the, lidar point cloud so we're looking at derivative, data from that light our point cloud. This. Digital. Elevation model, are this hill shade that we're looking at right now and the supporting. Digital elevation model, is. Really. High definition compared, to digital. Elevation models, that were created. Without. Using, lidar data so prior, to light, our data prior, to going out and getting a point cloud for the whole state of Indiana, we. Had generated digital. Elevation models, for the state of Indiana, using only contours. And I. Can, we can look at that hill. Shade and the, difference between that hill shade as a matter of fact let's do that. The. Difference between the, hill shades generated, using a, elevation. Model that was derived, from the point, clouds versus, one an elevation, model that was derived from contours, night. And day you, don't get near the definition, that you get here as far as these. Little gullies washing. Into so. I'm, going to go ahead and and show you that. I'm, gonna add in our chance. And. Bear. With me I'm gonna go grab a URL, from right here. Another. Great thing being able to copy and paste directly, from, your. Workstation. To, research, desktop, so, name, I'm gonna call this this. Is world hillshade. And. I'm gonna paste that URL in, there and say okay. And. Then. When. I add that real quick we'll. Be able to see well, night and day isn't it, I'm, gonna turn it on and off so this is, a world this is a hillshade that was derived, only using contour. And point elevation data not. The lidar. Derived. Digital. Elevation model, and hillshade it's, just night and day the the. The. Resolution, and the precision of this data is just so much better. All. Right. Okay. Plenty, of time all right I'm going to. Walk. Through, this. Data, that we're looking at right here that we created as a locally, created. Hillshade. We we, created this locally, and I stored it on the, this. Out hill shade if I'll go look at the properties I stored.
This On. The. Dc2, we, created this it's a local file it's only one County and. It's a rather large data set as uh let's, say a gigabyte, for this one hill shade for one county. Luckily. We have. Organizations. Like the, Indiana geological, and water Survey that go through and create these and then, we'll allow. They'll, host them so that you do not have to go through and create each one of these County, Hill, shades or and. Host it locally on and, store, it locally so. One, of the. Move. This guy again. Okay. So one of the tools I showed you are, included, in the PowerPoint, is this Indiana, map plugin, for QGIS, this. Will. Allow you to pull, in, services. Hosted, directly, at the Indiana map to, your QGIS. Session I mentioned. The lidar. Hillshade, that, they had let's go ahead and pull, that in and it's down here and write reference. Lidar. Hillshade. Iris. And. I add that real quick and it adds it to our map, session, you can see that uses, basically the same data a little bit different, settings to generate that but, if I go look at this again this is, statewide. This is a statewide layer. That's hosted on the Indiana, map so you're we're connecting, to a map service and streaming this data in rather than hosting it locally like, that one we just created if, I. If. I turn that off you'll see the one we created, the hill, Shay we created locally, it, just uses different colors, but. You could see same data and. Again. Our local, copy is only for Orange County that's all we did whereas this one that we're streaming in from the Indiana map from the Indiana geological, and water Survey is for. The whole state so you, can go create your own or you can connect directly to a service, like Indiana map and bring that data in directly from there I'm. Gonna bring in while we have that tool up I'm also going to bring in some aerial. Photography, just so we can get. A sense of where, we're at. You. All. Right so that aerial photography, if, we. Go. Through and adjust its. Transparency. So. That we can see through it and then we can see that underlying, hillshade, in the background, it'll create. A nice, visualization. They'll. Kind of you know make. The elevation, kind of pop out in the background you can kind of see right through that and see those elevation, areas. Right there. Okay. Anything. Else we want to bring in from the Indiana map this tool. Will allow you to do so if you wanted to bring in some contours, just so you can see you know actually, where you are you could do that or any of the other layers you could do that I'm, going to leave it as. Is right now we've got enough in there. Okay. So. Another one of the. Products. That we talked about. Was. A slope. And aspect let's. Create, a slope, quickly. Same process. Through. The roster. Menu, I, want. Some analysis. Again. We're going to use de m as our input. Data and, we're going to do some train models. This. Time the model we're going to do is. Sloped. So, rather. Than the mode of hillshade we're just going to change, that to. Slope. You have the option of using oh. No, that's for aspect you. Have usually option. Of using, degrees. Or. Angle. For. This it does not look like you have that we're using the. Band. One for, that there's only one band and, then. We're going to output, to the same spot and, I'm going to call this out. Slope. And it's also going to be a TIF image. And. Again it takes. A, few. Moments to run but, not that long. Go. Ahead perfect time for one day but yeah. Okay. So, what. Elevation. Data you have outside. Of lidar data okay, this is done and we're gonna see the slope return before. We had lidar data we. Had contours, and we had you know benchmarks, you know point elevations.
You Know here's an actual benchmark that we know the actual height. Of that those. Were our inputs, so that's, all we really had so the contours. Were the. Know. So. Yeah, the, where. Did elevation, contours, come from is that what you're asking yeah from the USGS. USGS. Topo quads, and, those, what, I, don't. Know the exact origin of, the, contours, as far as how they're created but I know that they were created, from those, USGS. Topo maps and they're on there it's the same data set they, were digitized, from that but, I think those were actually created. Using that, stereoscopic. Overlapping. Heads-up. Digitizing, using that stereoscopic. Process. I'll, have to dig further into that if you want more. Details but. Yeah. But. The the magnitude difference is just, glaring. Okay. So. There is our slope image in the background as soon as I get rid of this okay. And. Close. You. Can see the actual slope, and the, out slope these, are what. Angles. From zero, so downward. Up to 23, degrees. The. Very light, areas. Or where those slopes, are very high. If. I were to like. I did the other ones if I were to select that layer and give it some transparency. Options. Kind. Of make it see-through. Does. It add any value to the visual visualization. We'll see. Maybe. Maybe. If I just add a little bit. And, made. It more. Yeah, it might help a little bit, all. Right and, then the final one same, process, with, a SPECT we're. Going to use. The raster menu. Analysis. And. Digital. Elevation. Model, terrain models and, this. Time. Aspect. Okay so rather than running that this time I've already generated. An aspect I think so I'll just load. It in. Yeah. So there's aspect if you want to see what it looks like. So. That's aspect, and again if we want to go back to the actual. Definitions. Of these. Aspect. Represents, the orientation. Of downward sloping terrain in degrees. Clockwise. From, north so where that's actually down sloping, and then, the slope. Yeah. You can read there. All. Right so those were the, types. Of datasets I wanted to cover I want, to go. Back to. This. And remove some. Layers. And then we're going to create a, 3d. Visualization. Using that digital, elevation model. So. I'm. Going to remove some, of these that I don't necessarily want to use like the aspect, and the. Slope. You. All. Right. You. That's. A good question. I. Don't know uh I guess. Geology. Geologist, may use it for. Flying. Outcrops or like. Minded, slopes, I don't know like. Well. Not. Necessarily. Well. I mean it goes downhill yes obviously but I don't, think that says that's, not, necessarily, here.
Hydrological. Model doesn't. Matter actually follow aspect. Everywhere. Right, especially. If it it backs up. Let's. Look into that Eric I don't know what it would be used for, other. Than visualizing. No. I know I do here, it's. It's actually right here in this right. Let's. Say open, up really it. Actually tells you what each of these are used for for. Me. Might as well take a break inland okay. All. Right aspect. There. We go provides aspect is he's gonna float what's. It used for. You. You. It. Doesn't even say what it's. All. Right we'll have to look into that and get to it moving, on hmm. I. Wanted. To use. Just. The aerial photography, some. Hillshade and then, the de m in the background, to create a, 3d. Interactive. Interactive. Application. Using a plug-in. That, is this I mentioned, earlier the QGIS. -. 3j, s we'll, just do one right here, with what we have on there right now I don't. Know where we're at I wanted. To look at maybe. Paoli. Peaks but yeah we'll. We'll. Come back to it if dB, all. Right so that, looks okay I'm comfortable, with that I want to make a visualization, out of that and I say a QGIS, - 3j, s it's going to take this and again I'm going, to specify that I would like a, vertical. Exaggeration of. About let's, do 3.5. And. Then my de mi have to tell it that my de M is this file. The, 2011. Count EDM and. I'm going to leave the. Defaults. For the rest of it and I'm gonna click run and, we. Generate. Quickly. A. 3d. Elevation. Using, that 3d. Digital. Elevation, model, we've got a. Well. A. An. Interactive. 3d. Visualization. Based. Off that digital, elevation model, and I can zoom in and take my look around whatever. Lay airs I have in, my map are kind of draped over top, of that digital, elevation model, so. If I had up, there layers in here and we can I can add a couple just to show you. Scoot. Over. And, the. Lag from the internet and the. Difference. Between definition, of what I'm looking at here and what I'm looking at there is a little different but you get the idea you can.
I'll. Get a sense of the elevation, for any area using, these digital elevation models, if, I were to let's. Go back to QGIS and, do the same thing but this time I want to add some contours, and I think they're under reference. Elevation. Contours, yeah the 24k so back. To the elevation, contours. They were digitized. From USGS. Topo, maps that one to 24k, topo maps the. You, can actually go get the metadata about that layer if you want to determine how the contours. Were created. So. Now we've got contours, on there and if. I do that exact, same, export. And I want to make another. 3d. Object. Of this it's. Going to keep my vertical, exaggeration keep, all the settings this, time I just have a layer draped over top of that so. It should be the same visualization but. With you, know that layer of contours added on top of it so now I can zoom. In and. Work. Around and actually, see you, know where those, crowns. And points how. Those contours, actually. Work with that. You. Okay. So, yeah this is an actual HTML page by the way that you can take this this. Browser, page take it posted, online and, host. It and it's a regular web page that anybody can come visit rename. It add whatever you need to to. Make it on a regular. Web page that works, within your website. Go ahead. Yeah. It would be what you would let's, go do it would it be what you would look like what, it would look like in, real world scaled, um let's let's go ahead and do that but it doesn't make for a good visualization. But, let's do it for. Illustration. Purposes, so. Exactly. I'm going to go ahead and remove those elevation, contours. Before. We do that okay. And. This. Time we. Say vertical exaggeration of. Wine. Just, playing. And. Let's see what it looks like. You, know I chose, Orange County and southern Indiana because it is one that has some, of the most relief southern Indiana has the most relief and without. Exaggerating. Relief you know this area right here is you. Know pretty. Rolling. If. You were to you. Know go look at one of the counties in northern Indiana yeah it this, would look just. Nothing. There. Oh. Yeah I mean sure. Yes. But yeah you may have to get up into the eighth or Ken area to make that happen yeah, yeah. So. Yeah. That was it that that, visualization right, there the ones we're looking at right there are basically the grand finale we. Looked at the types, of datasets that I wanted to cover and how to use them in how, to bring them in to QGIS and, how to. Export. A web. Page a. Interactive. Web. Page with, this data so, that you can host it locally or do. Whatever you want with it I. Mean. For what. Five till five. Questions. Can I go, ahead David yeah oh.
Yeah. You want to yeah, let's look at the, help me in here oh. Yeah. Good, point innocent okay David, asked what kind of controls are available in this QGIS, to 3GS. Here. We're looking at them right now all the actual. What you can do with it how to use it. If. You, know how to use three Jas and three Jas by the way. Similar. To the talk you're going to be doing later it's a it's kind of like the d3. JavaScript. Library that you can create. Well. Interact with web pages with, so, if you know how to use to a 3GS. You can use this as your starting. Template. And then go ahead and add whatever customized. Code or customized. Controls you wanted yeah. Yes. So plugins a good point I should I should have made that plugins, are. What make QGIS. Run so the, base package is, of QGIS, is awesome we looked at a couple plugins, the Indiana map plug-in that that, I had created but there are so many other plugins, so let me say manage, and install plugins and. And. If I look. 3d. So de m2 3d will create obj, you know objects, that I can actually 3d. Print these elevation. Models if I wanted there. Are several other ones in here view, 3d clients, or you, know but plugins, is where that it's not, actually. In the base, package itself, those, were Python plugins that the user community creates, and, yeah. We've actually looked, at a few of these. What. Was some of the other formats. The obj, was, one of the 3d, printing, formats, there was another popular one that I can't, yeah. Yeah and that does that one even mentioned here but, let. Me what, was STL. Yeah. So. This one else this one will support it this one else born it so. Yeah it's a matter of just, finding the right plugin. And if the plug-in doesn't exist and if you know Python you can just create your own plugin and do that it's, QGIS. Is highly integrated but with. Python. And any, of the other statistical. Or software packages, or some, other packages, so over here in my toolbox. I have you. Know I can bring in our scripts if I want to chain a methodology. Together suppose you have an R script or something that does, some analysis, and outputs a file somewhere you can chain that together so that after, that output is done you can feed that input into QGIS, and kind of chain, a workflow, so that you, don't have to stick with QGIS. But you can put, together a model that'll take, some Python code do, something in QGIS, take the output use R and any, of these other packages. I mentioned, last tools there's a lot of the tools that tools. For lidar over, here. So. You can take these last so we mentioned last to de M but you can take two to last files a last, difference, my, input laughs and my new last and say what, changed, in between these two data, collections was there a building that was created did, somebody you, know remove a forest and actually get some, quantifiable. Metrics as far as change, between two data sets a lot, of other geo. Algorithms, and tools over here that are included that just, not going to have time to have covered today yeah.
Yes. Yeah. Okay yeah, let, me repeat the question so, he. Asked whether or not QGIS will, handle, other types of lidar, collected. Data and I think what you are getting out there is the difference between terrestrial. Lidar. Data data that's collected maybe, indoors, and as a. Just. A laser scan, of a place. Horizontally. Rather than vertically, and the answer is yes the file formats are going to be the same but remember QGIS, does not work with the point. Clouds directly, it. Normally. Takes a. And. GIS, packages in general, well. You can use some, of the raw lidar files in some GIS, packages you, will primarily work, with derived. Data from. That last point, cloud but, as far as last point clouds are concerned. Yes. The viewing. That 3d, point cloud whether it was collected. Dressed orally or through. Aerial. Collection. The, same process. In the same file formats. Yeah. So. If you were trying to compare. Forestation. That wall so for example. Over. Time, what. Would be the level, like. You wouldn't want the ground level what does it mean. Yeah. So um here. This is last, tools a last, viewer and what. We're looking at right there is only vegetation. So I'm saying render, only draw only. Vegetation. But I'm gonna say draw. Only ground okay so, and now I'm gonna go back and say render. Only. Vegetation. So. What we're looking at right there is vegetation, I have, I can create a digital surface, model of. Just, the vegetation, and you. Would do, that last difference, the difference between two last files using. Only those points, that are classified as vegetation, and you, can do a last diff and determine, you know what's the volume difference or you know how much difference, is is there between these two files. Does. That answer your question I did, not repeat the question I'm sorry I should, have, for. Those listening at home. She. Asked how, would you. Compare. Vegetation. Among two different. Lidar. Files, to different last files and I. Think the answer was pull. Out only those vegetation. Point clouds or vegetation. Points and compare. Those to only the vegetation, points of the other datasets. Sure. Yeah. So, you're. Okay. So the question is I think comparing. Digital, elevation models, an older digital, elevation model, that was created from. Input. Data of contour, lines versus. Comparing. That, to a digital, elevation model, that was created using, lidar, data as the input, and yeah.
You Can compare to DMS, a similar, to the last. Difference, compared. To what. You would notice are what you'll notice. Is. Well. What we what we looked at there and I can I highlight it that again but, the the. The definition, are, the high definition of, those little stream channels, that, just don't show up in that older, digital elevation model, just because, of the. Limitations. Of the data that was used to create it but you can compare those digital elevations, and get a difference, how. Valuable, that, would be because of the limitations, of the older data I don't, know does. That answer your questions. Okay. The question is on these lidar. Point clouds points. Are classified, as either, vegetation. Or ground how does that classification, take, place is that your question okay yeah so. Sometimes. It's, done automatically. Based on the intensity, and the time that it takes for that return to come back so your. Your very last return, that's. Going to be your ground that. Can be automatically. You can automatically, classify, a lot of those there, is. Cleanup. That takes place from the vendor that collects this data before. They deliver it to whoever. Purchased. The data, there. Is classification. That takes place they will go back to the. Office look, at the point cloud and start, classifying these select, a bunch of points at once and classify, those based on what, they see what. They are they'll, also have that area of photography and they'll make that decision and classify. That in many, cases the data we're looking at. It. Gets, very. Manpower. It's. Very difficult to classify, every, one of those and very expensive so some, of the data sets we're looking at like I said if I'd go to and say render only. What. Buildings. There, there none there so they in this data set they did not take the time to say all these, points are, buildings. If I go back and say render. All returns, you'll see there are buildings here but, they did not take that time to actually go classify, all those points that constitute, a building, as a classification. Of building they only classified, a few so. To answer, your question it's a manual, process but, there is some automation, taking place based on you know how, what. The intensity, of that reflection of that reflection. Coming back and how long it took for that reflection. To come back a lot, of that is automated and cleaned up in the office answer. Your question great. All right. Yeah. I don't, really know these. Hmm. Not. Really familiar with these controls either you'd have to guess. Worked with the controls to zoom in or actually. Go. Look at the errata, or, the digital elevation model, that came out of that data I don't. Think there's a zoom in here so this yeah. While I'd say just. A little last year it says it's a free and open-source tool not, a lot of advanced functionality, those, that are classifying. This data when I go back to the office they've, got commercial, or proprietary, software that allows them to do. Much more. What. I used today when I tried to use today was all free and open source software so no license, is needed and same. With the research, desktop, no. No. A special accounts needed other than your carbonate accounts. So. That was the goal anyway. Any. Additional questions go. Ahead isn't yeah. Yes. This, PowerPoint. Will be made available on, the Encore. Or on the campus site and, then, the. Zoom recording is also going, to be recorded available, there but I can also make it available to anybody. Pretty. Easy to find. Thank. You all for the interest in for coming yeah.
2018-10-14 19:20
