Error prone GIS

In any data related field great efforts are put into ensuring the quality and integrity of the data being used. It has long been recognized that the quality of results can only be as good as the data itself, moreover, the quality of data is no better than the worst apple in the lot. Hence, for any data intensive field great efforts are put into data pre-processing to understand and improve the quality of the data. GIS is no exception when it comes to being cautious about the data.

The various kinds of data being handled in GIS makes the problem of errors more profound. Not only does GIS work with vector and raster data, it also needs to handle data in forms of tables. Moreover, the way the data is procured and converted is also a concern. Many a times data is obtained from external sources in the form of tables of incidences that have some filed(s) containing the location of the event. Usually this data was not collected with the specific purpose of being analysed for spatial patterns, hence, the location accuracy of the events are greatly varied. Thus, when these files are converted into shapefiles, it inherits the inaccuracy inbuilt in the data-set.

One of the things to remember however is, that the aim of GIS is to abstract reality to a form which can be understood and analysed efficiently. Thus it is important not to lay too much emphasis on how accurately the data fits the real world. The emphasis on the other hand should be to find out the level of abstraction that is ideal for the application scenario and then understand the errors that can be accepted at that level of abstraction.

-Dipto Sarkar

Comments are closed.