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Over the last few weeks we have been looking at ESRI's CityEngine and how it can be used to create rapid urban scenes. As we noted it moves GIS visualisation a step forward while at the same time bringing procedural city modelling into the mainstream game engine world. Of course the heart of the CityEngine is the ability to import real world data but to get to grips with the interface it is sometimes easier to look at creating urban scenes from simple procedural rules.
As part of the MRes in Advanced in Spatial Analysis and Visualisation, here in CASA we have been looking at various techniques to visualise urban data. One such technique is the creation of a 3D exhibition space, allowing agent based models and urban data to be visualised within an architectural space.
The movie above combines the use of CityEngine in Lumion with SketchUp and 3DMax to insert an exhibition space into a city while burning the CASA logo into the street network. CityEngine is a notable step forward for ESRI, both in terms of visualisation and analysis, linking it with Lumion and SketchUp allows it to be taken even further, towards the ultimate city creation toolkit...
The best way to learn new modelling software is to step away from complex data and take a side look at its capabilities. We have used this approach to run through the various features of CityEngine, producing a series of movies based around the logo of the Centre for Advanced Spatial Analysis, here at University College London.
First up we integrated the CASA logo into the cityscape by manually tracing the logo and building a network around it. Via an import into iMovie the result is a playful fly around the logo:
Taking the concept further we built the city around the logo, using the nodes and hubs as interconnected cityscapes. With the city base rising out the sea it presents a different feel to the original movie:
Finally, we used an alpha channel on the logo, allowing us to lower the outline onto the cityscape:
The combination of Adobe Illustrator, ESRI CityEngine, AutoDesk 3DMax and finally Lumion make for a rapid way to create unique cityscapes. The next steps are to integrate actual data.....
This is very much a work in progress post, but we are interested in integrating text/patterns/logos into 3D models of the city. At the moment we are putting a work flow in place to take our CASA logo and burn it into the street patten of a procedural city.
Using the CityEngine, combined with vector files and Lumion/3DMax some interesting results can be obtained, especially if you also build in some physics/particle engine and agent based model capability.
We will have more on this in the coming days....
Update 14th March 2012 - Below is the first second draft movie:
Next stages are to build the city over time, we should have a work flow in place soon...
A quick weekend post - following on from our first look at CityEngine and Lumion we have expanded the visualisation to add in various standard items from the Lumion library along with a surrounding terrain and waterside setting:
Total development time: 15 minutes with rendering 1.5 hours, its getting quicker to make cities....
Yesterday a license for CityEngine landed on our desk from the nice people at ESRI and to be honest we were a little too excited for our own good, after all its only software. However, CityEngine and its integration with ESRI ArcGIS, while maintaining full export capabilities to load into 3DMax/Lumion/Unity etc, is a game changer.
It moves GIS visualisation a step forward while at the same time bringing procedural city modelling into the mainstream game engine world. Over the coming weeks we will be putting the software through its paces and exporting into Max/Lumion and Unity as part of introducing CityEngines onto our MRes in Advanced Spatial Analysis and Visualisation. The clip below details out first output direct from CityEngine into Lumion, adding in a general landscape, sample trees and transport objects:
Linking in our previous post on ArcGIS Twitter Visualisation in Lumion it seems that the worlds of GIS and architectural visualisation/game engines are finally starting to become accessible.
Over the past few weeks we have been exploring exploring new methods and techniques for visualising data. Developed as part ourMasters course in Advanced Spatial Analysis and Visualisation we are now looking into issues of scale, realtime rendering, rapid visualisation and 3D exhibition spaces.
Regular readers will know we have been exploring Unity due its interactive nature and ability to import various file types into its game engine (see Particles, Agents and Emergent Behaviour ). Unity is still an option but for rapid visualisation Lumion also offers distinct possibilities. The movie below details our first draft example of building an exhibition space (SketchUp), retexturing and adding various crowd/delegate models (3DMax) and the Twitter map (ArcGIS) using Lumion:
If Lumion offered a stand alone viewer rather than purely movie based output then it would be our engine of choice. As such it is currently a weigh up between Lumion and Unity, our Unity example is under development, we will post it soon as we can...
Readers will know that as part of the MRes in Advanced Spatial Analysis and Visualisation, here in CASA, we are exploring new methods and techniques for visualising data. As part of the course we are looking at collecting data from the Twitter API and using the resulting .csv file as an input into a variety of software, including Processing and ArcMap. Data so far has been focused on displaying the output from ArcGIS as a slightly more traditional map, albeit in 3D via Lumion:
Taking a step back it is possible to take a more abstract view of the data visualisation and use the Twitter data collected to create a digital elevation model for direct landscape visualisations.
As we have mentioned in previous posts there are of course many arguments on the pro's and con's of visualising data in such a way, indeed the visualisation is developed to open up the debate as part of the MRes course allowing various visualisation techniques to be compared from the same data set.
Sometimes however an abstract route to visualising data can quite liberating in a world of visualisation dominated by more traditional and academic output, the screenshot above illustrates Kingston Peak with Soho Mountain dominating the background. The movie below details the landscape as a fly-through:
In future posts we will explore issues of scale as we take the landscape and move it into an online exhibition space.
As part of the MRes in Advanced Spatial Analysis and Visualisation, here in CASA at The Bartlett, University College London, we are exploring new methods and techniques for visualising data. As part of the course we are looking at collecting data from the Twitter API and using the resulting .csv file as an input into a variety of software, including Processing and ArcMap.
One such known example is the London Twitter map by UrbanTick, developed using the data collector created by Steven Gray and imported by Fabian into ArcMap, it developed a style of its own as the 'NewCity Landscape' collection. From a digital urban point of view the next stage of the map is a 3D extension, a transformation that proved surprisingly difficult due to the nature of combining the worlds of traditional GIS and game engines such as Lumion.
We are still in the early stages of development but the movie below illustrates the NewCity Landscape Map of London visualisation in Lumion as a 'Twitter Island':
Music by Pigeman over at MP3 Unsigned. There are of course many arguments on the pro's and con's of visualising data in such a way, indeed the visualisation is developed to open up the debate as part of the MRes course allowing various visualisation techniques to be compared from the same data set.
We will have more updates as the visualisation develops, along with a walk through of how to build it. If your interested in such output our MRes is now open for applications, entry 2012-2013...
Crowd, transport and urban simulations are at their roots down to 'Agents' or 'Objects' that are assigned a set of rules as to how to moves in relation to both the environment and other agents around them. 3D Studio Max has a built in 'Crowd and Delegate' system which can be used to assign behaviour and therefore create realistic traffic of pedestrian systems in 3D space.
The movie below displays our first tentative steps to explore emergent behaviour via the introduction of simple rules. The movie starts out with a basic 'wander' behaviour where the agents only knowledge is the shape of the surface. Moving on we assign each of our 'cubes' (of which we have become quite fond of...) a level of vision so they can see ahead and therefore avoid each other and objects in their environment.
Thirdly, the agents seek a 'sphere' which could be viewed as a source of food. While being aware of each other and tweaking the way the cubes move a swarm behaviour emerges. Finally, we introduce competing groups with two priorities, firstly to eat and secondly to stay as a group. The majority choose the group over the food but a couple stray off in search of sustenance and lose the other members. Previous steps in our visualisation of agent based models are based around a simple flocking examples. This model is an attempt to mimic the flocking of birds, while the resulting motion also resembles schools of fish. The flocks that appear in this model are not created or led in any way by special leader rather, each bird is following exactly the same set of rules, from which flocks emerge.
We have exported the model into 3D Max providing the visualisation below, as ever these are early days but the results seem to run well with 300 'birds' over 1000 frames. The birds are rendered as cubes at the moment for proof of concept:
The birds follow three rules: "alignment", "separation", and "cohesion". "Alignment" means that a bird tends to turn so that it is moving in the same direction that nearby birds are moving. "Separation" means that a bird will turn to avoid another bird which gets too close. "Cohesion" means that a bird will move towards other nearby birds (unless another bird is too close). When two birds are too close, the "separation" rule overrides the other two, which are deactivated until the minimum separation is achieved.
The three rules affect only the bird's heading. Each bird always moves forward at the same constant speed.
If we were using the built in Crowd and Delegate system a true 3D flocking system would be possible, but it would be pure visualisation, by importing via NetLogo you gain access to the raw data and thus spatial analysis is possible. It is also quick to model and provides the best of both worlds - 3d visualisation and complex modelling.
While 3D Max is of use for crowd and particle simulation when it comes to modelling complex systems an external package is required, such as NetLogo. The movie below details our first steps at CASA (home of digital urban) to export a basic traffic model from NetLogo into 3D Studio Max. The import script was written by our new PhD student, Ateen Patel and opens up a vast array of opportunities to both visualise and model the city.
NetLogo is a cross-platform multi-agent programmable modeling environment that is widely. It is particularly well suited for modeling complex systems developing over time. Modelers can give instructions to hundreds or thousands of independent "agents" all operating concurrently. This makes it possible to explore the connection between the micro-level behavior of individuals and the macro-level patterns that emerge from the interaction of many individuals.(Nation Master Encyclopedia).
How does this relate to the city? The next part is to put in real geographical data and to get the agents movies and reacting to each other on a spatial network, more on that to come. Perhaps using a particle system as per the movie below:
All of these models are going into our exhibition space to allow a step by step guide to the principles of agent based modelling. At the moment we are weighing up two options - Unity and Lumion. Our previous trials in Unity are below:
Unity is great, it is a fully featured game engine, however we are also looking at Lumion. Lumion, aimed more at direct visualization, is remarkably easy to learn, the movie below is the result of our first 20 minutes working with Lumion from first load to final output. It is merely proof of concept, but taking the output from Max and dragging into Lumion is refreshingly simply:
