ESRI UC: Exhibit Hall, Wisdom of the Cloud
Below are three booths I visited in the Exhibit hall and a use case describing how Cloud based GIS would allow them to collaborate.
Surface Area and Ratio
I visited with Jeff Jenness, who showed me tools he’s developed to compute Surface Area and Ratio. An acre in a hilly location has a lot more surface area (and wildlife habitat) than an acre in a flat location. Cool stuff.
During lunch, Michael F. from Santa Barbara described all the fires they’ve had near his home. I wonder if reports of the number of acres burned for that region reflects the surface area.
I watched an in depth presentation on of HAZUS – MH. This is a free tool available from FEMA for performing risk assessment. While lots of free data is provided with the tool, users often like to plug in their own data. It runs on the desktop.
WeoGeo showed me how their marketplace allows data vendors to present their wares on a site where buyers can comparison shop and purchase the best data for their needs. While their marketplace focuses on data, they see a potential for using a marketplace for tools.
A Cloud Use Case
Let’s suppose FEMA ported HAZUS MH to the cloud. Right now HAZUS supports Hurricane, Flooding and Earthquake. It does not support Fire risk modeling. Imagine a cloud based tool, perhaps looking like modelbuilder, that would a allow GeoDesigner to author a template wildfire risk assessment model, and publish it for others to use.
A user would log in and create a model of specific area (Santa Barbara) using the template. They would augment the free data with data purchased from some site like WeoGeo. Maybe they could purchase a DEM and some color infrared imagery to indicate how much fuel is available for a fire. Likewise they might decide to pay extra to have WeoGeo pre-process the data using a tool like Jeff’s before shipping it.
The guy at lunch told me there was one fire that moved 20 mph down a valley. He said shifting winds can quickly change which areas are deemed to be at risk. With such rapidly changing conditions it seems like it would be easier to re-run models with updated parameters and serve the results out to appropriate agencies if the model is in the cloud.