Visualizations may shape smarter city development
- 30 October, 2014 12:23
David McConville, president of the Buckminster Fuller Institute, spoke on Tuesday at the GreenBiz Verge conference in San Francisco
There's more to making cities smart than the Internet of Things and the collection of big data.
The move to address urban problems like pollution and traffic congestion has shone a spotlight on instrumenting things like roads, light poles and mobile devices, and seizing insights from the information they generate. But how that data is presented can affect the impact it has and the types of questions that get asked, panelists at the GreenBiz Verge conference said Tuesday.
Just as smaller sensors have expanded data collection and big-data tools have made it possible to better analyze information, visualization software is also evolving. That could help to give ordinary citizens a say in how cities are built and run.
Decisions about transportation, housing, pollution and other issues have long been made using models based on urban planning theories, said Paul Waddell, a UC Berkeley professor and founder and president of planning software company Synthicity. Now planners who build those models can use them to put structure around big data, he said. What that data can accomplish is determined partly by what visualization software can do, and its capabilities keep growing.
Synthicity's Urban Canvas software lets users quickly visualize large amounts of data to find out how different decisions could affect things like the environment and the character of neighborhoods, Waddell said. Software like Urban Canvas can mean planners aren't locked in to drafting one or two possible solutions and asking residents to accept or reject them, he said.
"We can do interactive design, we can do interactive visualization, and we can start to engage communities more directly in evaluating the outcomes that matter to them," Waddell said.
Design software vendor Autodesk has developed a way to estimate the environmental effects of proposed projects along with the straight financial costs of building and operating them. It's part of a broader effort by the company to make environmental factors visible to designers using all its products, said Emma Stewart, Autodesk's head of sustainability solutions.
The company's AutoCase product, becoming generally available next month, can integrate findings from multiple sources, including articles from academic journals in a variety of disciplines, and combine them with other data in a visual simulation of the project under discussion, Stewart said. Regulatory factors such as environmental laws and credits offered for green features are also built in. Those values can be modified as needed but are there for quick visualization.
Los Angeles has used some of these technologies to design and win approval for a project to restore the cement-lined Los Angeles River to a more natural state. Within a 3-D model, designers can add new elements such as pathways and trees and see the effects on other elements of the area. Using licensed data about the local climate, Autodesk software can simulate the environmental effects of giving a building a roof with a built-in garden, Stewart said.
Visualizations that showed environmental as well as financial costs have already shaped policy decisions in Phoenix and Fort Worth, Texas, where those decisions were surprises given the political culture in those cities, Stewart said.
Talking about environmental effects may also require visualizations at an even higher level, according to David McConville, president of the Buckminster Fuller Institute. He is also cofounder of The Elumenati, an engineering firm that creates tools for immersive visualizations such as planetarium shows.
For example, to discuss local decisions that could affect bird migrations, words may not be enough to describe those migrations and how they work with global flows of water and energy, McConville said. Visual depictions are required.
Data can be collected about anything, so the key to making good use of data is to decide that data is needed and why, McConville said.
"The solutions that we develop are really going to be based on the questions that we ask, so we have to be asking much more intelligent questions," he said.