Animations lecture (NCSU Geospatial Modeling and Analysis)

[0:00] So now we have looked at display of two-dimensional data, three-dimensional data, and then we can also have dynamic data that represent change over time. And to display those and visualize and analyze those, we can use animations. So When should we use animations? For example, if we are working with dynamic simulations, Simulations are, for example, used for prediction of ocean, surge, flooding, pollution, migration, urban growth. So outputs of dynamic simulations can be animated within GIS.

[0:44] Another big area of application are time series of data. For example, we can have measured temperature, precipitation, melting of ice cap, or urban growth from remote sensing data. And those can be animated again within GIS. Then there are some more unusual applications. For example, if you are trying to analyze certain method and how it changes by changing the parameter, That may be another application and we will show some examples of that as well.

[1:25] One important thing to remember about animations is that it requires data that change continuously. for the outputs of dynamic simulations that mean that you need to create the frames. from relatively small step. For monitoring data, sometimes it is not possible to gather the data over time with sufficiently small steps to capture the continuous change. So you may need to do interpolation over time.

[2:00] to add frames. Now, what are the most common applications of animations? And I'm just, there are so many, I'm just mentioning two. One is weather maps. Everybody knows them. Everybody has seen them on TV or on internet. And there is plenty of them and they represent both data and models. And another nice application that you can--you can--this is just one of the websites that has these animations. Then another one, another example is pollution@airnow.gov. There are some very nice air quality conditions maps animated that show how the air quality changes throughout the day. North Carolina has some quite interesting maps there.

[3:00] is flyby, where we are using a single static surface, and we are just flying over it. It's extensively used, for example, by Google Earth, but there are many, almost every three-dimensional visualization tool has flyby. fly-by-tool where you just work with mouse to fly over topography. It is most useful when you have larger datasets. and you want to explore it with greater detail to get really close.

[3:32] Then another type of animations is with dynamic surfaces, where you have series of changing surfaces. and the viewing position is static. And another one would be, for example, cutting planes, where you are using the animation to slice through stacked surfaces. And again, the most important thing to remember is that you need to have small step between frames so that the change is continuous.

[4:02] And we will look at some examples of these animations after I finish this lecture. Then just a final word about the newest popular way how to display GIS data, and that's using Web GIS display. Here is an example of a map done from GPS Visualizer that represents the visitors who visited Jockey's Ridge during the summer of, I think, 2006.

[4:36] and It had a small subset of these visitors and all that we had was zip codes. So just using the zip codes, we were able to map where all these visitors are coming from. And here it was very easy to do through web GIS. You can do much more sophisticated maps and visualization using, for example, Google Maps and Google Earth. So what I would say that Web GIS is the most dynamic, rapidly evolving component of geo information technology. And we are seeing WebGIs going way beyond the beyond just viewing the data, displaying the data, but more and more websites offer some tools for geospatial analysis.

[5:30] So let's now look at some dynamic GIS examples. In this first example you can see a simulation of healing of water reservoir and this was one of the first simulations that we have done at US Army Construction Engineering Research Laboratory in 1991. So here is first relatively simple example that shows use of animations to explain functioning of a method and how, for example, an interpolation surface changes when we change interpolation parameter.

[6:16] and we will be talking about splines, and we will be working with this method. Here is another example of method analysis where we are exploring how the parameter that controls the influence of topography on interpolated surface impacts the results. Here is dynamic model just for plane observations. And this is interpolated average monthly precipitation. And you can very nicely see the trends as a surf as a dynamic surface.

[6:59] as the precipitation changes throughout the year. Here is an output from simulation and this represents water flow over complex terrain. Here is water flow accumulation in valleys and you can also see how the crest rises and moves throughout the landscape and that it's certain point the crest reaches its maximum, where the maximum reaches the outlet, and then it doesn't change anymore.

[7:36] This is combination of water flow and slope map that represents sediment flow over complex terrain. And you can see that it's different from water, that it's really maximum somewhere in the middle slope where the slope is the the steepest And also that the sediment transport throughout the valleys is much bigger than on the hill slopes. And the sediment transport also decreases in those areas where we have concave.

[8:09] um topography. This is again output from a simulation that compares solar radiation during summer and winter solstice. This is summer. and you can see that the entire valley, entire area is illuminated. And you can also see that during the winter, there are parts of this landscape deep in the valley that never get direct solar radiation. So this is an important simulation, for example, for plant growth, for agriculture, forestry, but also for placing solar panels.

[8:54] Here is again an example of analysis of method that shows how increasing the number of samples reduces the error in the results of solution of continuity equation and how the how the noise that is in the solution just decreases as you increase number of particles. And we will be talking about this method and explain the example in a greater detail.

[9:25] And this is sediment flow, sediment flow map. and sediment flow map, and this is net erosion and deposition. Erosion is here, deposition is the blue. Here is another illustration of the path sampling method and On the left are the particles that move throughout the landscapes, and we use the density of these particles as a measure of water flow depth, which is shown on the right.

[10:05] And you can see that this area has more water, it's more surface runoff, and that's the area that is disturbed. Here is a multi-scale version of the same simulation where we have for certain area, we are, let's say, planning some developments, so we need higher resolution results. So essentially when the samples hit this high resolution area, they are split into the smaller, larger number of particles and the simulation continues at higher resolution.

[10:45] This is a cross, this is moving cutting plane through the cross section and you can see that you get the, you keep the size of this cross section the same. by moving the the multiple surfaces towards the viewer. Otherwise, because of the perspective, it would be getting smaller and smaller and harder to see. So this is just the three-dimensional map showing three-dimensional soil properties. It is distribution of pH and This is another three-dimensional Uh, three-dimensional representation here, now geological features. This is, for example, an ancient subsurface lava flow that is currently covered This is visualization of multi-attribute, multi-dimensional site data. We have already talked about the examples where we can display the three-dimensional, where we can display point data as three-dimensional symbols. Here the symbol allows us to show the proportion of

[12:06] Hmm. clay, silt and sand within each sample. and here is the animation that shows three-dimensional distribution of monthly nitrogen in Chesapeake Bay in one year cycle. So you can see that in the spring, there is an inflow of nitrogen, from the north and during the summer we have inflow of salt water and reduction of nitrogen concentrations.

[12:49] And here is again essentially a four-dimensional model that shows evolution of chemical concentrations in groundwater based on 10 years of well sample data. So you can see that the plume has evolved, it was very big, then it shrinked, and then somebody put some more pollutants there, so it increased a little bit again. And you need four dimensional interpolation to create models like this.

[13:29] And then finally, this is the ever popular fly-through. And this is actually through Fort Knox. and military installation along the river. So this is all about the animations and I hope that this was inspiring for you and that you will find an opportunity to do some animations as well for your project or sometimes in future.