Abstract
Utility companies must consider the following to arrive at the appropriate technical specifications for their GIS data and the corresponding implementation schedule:
- Impact of technology on the cost of data acquisition: All the technologies required for acquiring data of appropriate quality are already in place. Technology is unlikely to make any major contribution to reduce the cost of data acquisition in the foreseeable future. This will be more true for compilation of large scale maps (which we will call “Fine Mapping Product” in rest of this document).
- Impact of maturity of GIS data vending industry: In the next few years, maturity of the data vending industry will drive down the price of GIS data and simultaneously increase the data quality
- Impact of better and cheaper GIS software: Some of the upcoming GIS software are much more elegantly built and are so much cheaper. Hence, GIS computing will become much more commonplace and GIS database can afford to be more elaborate.
- Cost of upgrading the landbase at a
future date: Utility companies which presently start with less
sophisticated land base are likely to face high upgrade and
migration cost in the future.
When the above are taken into consideration, it shows that the optimal specification for the Geographical Information System and their implementation plan must be different from what is prevailing in the Indian industry.
Limitations
The discussions of this paper have two application limitations:
- The paper discusses the Utility GIS in the context of city based utility services only. Content of this paper will require substantial modifications to accommodate cross-country utility infrastructure like high tension power distribution
- The paper is tailor made for developing
countries like India. In most of the developed countries, GIS data
of high quality are readily available at a fraction of the data
acquisition cost.
Components of GIS Data
All GIS data are made of two components:
- Geometry of geographical features like locality boundary, street boundary, plot boundary, building features, etc. These type of data are called the “geometric data”. An illustration showing a typical geometric data for an Utility GIs is enclosed in the illustration overleaf.
- Information associated with the geometric
data like locality name, street name, nature of occupation of a
plot, elevations, etc. We will call this the “attribute data”
The typical “Geometric Data” are generally required in an Utility GIS are mentioned in Table 1.
The geometric data is usually acquired with one of the two accuracies (refer Table 2.)
Due to the inherent nature of the technologies deployed,
- “Fine Mapping” is much more capital intensive than “Coarse Mapping”.
- “Fine Mapping” is more labor intensive than “Coarse Mapping”.
- Hence, “Fine Mapping” is usually two to
three times as expensive as “Coarse Mapping”.
World over, it is the general practice to use “Coarse Mapping” specifications at the planning stage.
Whereas, India seem to stand divided in usage of “Fine Mapping” specifications. Even though labor cost is much higher in developed countries, which should make the “Fine” products much more expensive there (Developing countries have access to technologies like aerial photo interpretation, etc., which are not available in India. Hence, the cost equation in developing countries is further distorted from that it in India.), developed countries seem to go for the “Fine” product for utility maintenance and operations. However, in India, where utilities are just beginning to adopt to GIS, even though the “Fine” product is “only” about two times as expensive as “Coarse” product, there is a tendency to use the “Coarse” product for operations and maintenance as well.
Addressing this
anomaly adequately will create/save economic value running into tens
of crores of Rupees in the country within the next few of years.
Criteria for an Optimal Data Model
For arriving at an Optimal Data Model, we will be required to consider the following:
- Cost of Geometric Data, as varying over time
- Cost of GIS software and hardware of different capabilities
- Benefits derived from different Systems
- Cost of future upgrade, if any
