Posts Tagged ‘temporal’

Possibility of a Time Toolbox?

Thursday, March 22nd, 2012

Temporal GIS is a topic that encompasses almost all studies. Last year I did a study on pesticide use in California. Unfortunately, the data was only available on a year to year basis, so in order for me to graphically show the drastic increase in pesticide-related injuries I had to use multiple maps. On each map, cases were visualized with a red dot. At the end of the project, I resorted to using three maps from three different years in order to show the growth of pesticides. This however, was somewhat taxing. I had to create and prepare three different sets of data to visualize. At the time I accepted this as the way temporal GIS could be dealt with, but now I ask the question if there are better ways to visualize, rather than overlaying or using side by side map comparison.

I wonder if a simple sliding time bar could be incorporated into arcMap (or something similar) as a toolbox. Existing objects would simply need an additional time attribute that the slider would select. As a user slides the bar, a different series of shapes and polygons would appear or disappear. This could also offer analysis tools. If the program is aware that two polygons are the same, but change in size and shape over time, it could possibly calculate this change.

I realize though, that this would be data intensive, especially when dealing with time scales that are very small. A year to year basis could be feasible, but on a smaller scale, such as second to second, dealing with hours of data could become unrealistic.

Google Earth has several features that allow the user to play sequences through time, but as PPGIS and HIC has proven, sometimes Google apps are not the best for data analysis.

Andrew

Time and GIS

Wednesday, March 21st, 2012

We’ve heard how the cyberinfrastructure handles temporal and spatial data separately, but must be developed in such a manner that allows for users/researchers to utilize both sets of variables when interacting with a GISystem. Now Gail Langran and Nicholas Chrisman provide an interesting overview of the topological similarities between time and space, and how best to design a GIS system which can accurately display temporal elements.

I find the authors’ notions of time and its important elements to be a overly simple in a way that helps to lend credence to their subject. In particular, they characterize cartographic time as “punctuated by ‘events,’ or changes” (4). Furthermore, they do a nice job contrasting GIS algorithms based on questions concerning space (what are its neighbors? what are its boundaries? what encloses it? what does it enclose?) with the similar questions one might ask for time (what was the previous state or version? what has changed? what is the periodicity of change? what trends are evident) (7). Such examples help to define this paper not just as a discussion of temporal data, but also of temporal data based closely to its application in geographic space. Such an added dimension can be incredibly important when we begin to think about all of the geographic phenomenon that occur over differing timelines. It’s also an element we should try to remember more in our own research efforts.

I do wonder about the distinction the authors draw between real world time and database time. Since many GIS databases are headed toward real time, streaming data – as was pointed out in previous lectures – why make this distinction? Perhaps I’m not technically inclined enough to understand the importance of the difference in programming or maybe it’s just a matter of how the system might store information. Anyone have thoughts on why real time data can’t be used in a manner that equates it to database time?
–ClimateNYC