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Urban Infrastructure Projects

 

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An area of growing interest around the world is the integration of geomatics and infomatics in the management of urban infrastructure. This ranges from the use of laser scanners to provide highly detailed 3D digital "as built" data sets, to using water flow analyses to develop sophisticated storm water runoff, to new tools to manage the electrical, water and sewer systems using network data models - and many, many others.


From the perspective of historic applications in geomatics, the urban data have the properties of being very large scale (that is highly detailed and requiring highly precise control), truly 3D (not 2.5D like much terrain data) and having complex interrelationships between elements in a single data sets (e.g. valves and pipes in a water system) and between data sets in space (e.g. water supply elements are located beneath building elements) and operational relationships (the water line connects to the plumbing within room 1 in building x).  These issues raise interesting new questions and opportunities for research.
 Historic Old Main - 3D Scan  

 

A second major area of interest in the application of geomatics to urban infrastructure is in the potential to reduce the "stove-piping" that is prevalent in many areas. It is not uncommon for different data to be in widely different data formats and for different professions to have different semantics and ontologies applied to the same phenomena. At the Center we are following closely the development in such areas as CityGML and the National Building Information Model initiative and other semantic and ontological studies in the urban infrastructure arena. There are great opportunities for intermediation in this arena through interoperable systems and data.

Among other efforts, urban infrastructure research (e.g. the development of new methods to create 3D visualizations of the urban fabric), the Center is working closely with the University of Arkansas'  Facilities Management to simultaneously assist them in the development of new approaches while using the massive and complex university infrastructure data sets as a valuable "sand box" for the Center to develop new methods and techniques.