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Putting Lipstick on a Pig

Marketing WhiteStar

Change can be tough - if your geotechs have already built a lot of land parcels on top of an underlying grid, the argument is sometimes made that switching to a new, more accurate basemap would not be cost effective.  Should land and exploration departments make a decision of this magnitude based on inertia, or should they look to constructing the most accurate lease and parcel basemap possible, supporting the highest quality business decisions?  The phrase "putting lipstick on a pig" comes to mind.

New polygon data layers are becoming available all the time, and should fit precisely on top of your land grid. They generally don't fit seamlessly on to your existing data layers because they come from different vendors and sources.  What should be done about this?  

Common sense and experience dictate that the most accurate data layer should be the control layer.  For example, if your enterprise invests in a parcel data layer for surface ownership - something commonly occurring in resource plays these days - then the surface ownership and the at-depth lease ownership need to be tied to the underlying, most accurate grid. 

Older land grids simply do not have the accuracy, precision, or level of detail that newer ones do.  You can easily demonstrate this to yourself by taking your elderly land grid from whatever source and attempting to overlay it onto the industry standard USGS topographic map series.  You'll often see the vectors wander quite a ways from their corresponding red source lines. 

What does this mean for your mapping program?  In the good old days, it was enough to show data on a paper map without much regard for positional quality or how the data were created and maintained. Obtaining a data set was the equivalent of ticking off a box.  But as spatial data finds more and more applications and uses, companies are paying much more attention to data accuracy and attribute completeness.  

The computer industry has forced investment in cleaning our data as new technologies become available and point out the flaws in that data.  For instance, it is quite easy now to bring in streaming topographic maps to compare the positional accuracy of a land grid.  At the same time, investment in clean up or reevaluation of an existing land grid is resisted more in corporations probably because it is hoped that the existing data is "good enough".  Would you stake a multi million dollar well on data this old - and potentially off by hundreds, if not thousands of feet?  Would you even want to chance it?  Would you want to base those same decisions on data that is not properly maintained, corrected, and supplemented with new information? 

If your data layers do not fit precisely together, then you can assume that your wobbly stack of questionably positioned data will eventually cause you problems, questions, critiques, perhaps even career limiting uncomfortable experiences.  We see Tier 2 and 3 petroleum companies beginning to more closely examine data quality and validation issues.  There is a dawning realization that GIS data needs to be based on the science of GIS.  

Land grids are changing these days.  At WhiteStar we are spending a considerable amount of energy adding government lot and tract data to fit precisely on top of our flagship WhiteStar Grid product. Lots and tracts are frequently referenced in land polygon legal descriptions.  Having a lot and tract database lets you create the most accurate representation of your land position - ever. 

Like many changes, making the decision to adopt a new, more accurate and trustworthy base for your mapping gets harder the longer you put it off. But the payoff in reduced data maintenance overhead and better business decisions makes it well worth the effort. We can help you get there - sooner than later.

Ask The Expert

Which layer ideally controls the accuracy of the stack of GIS parcel layers?

The land survey or cadastral layer.  If this data is imprecise or inaccurate, every parcel built on top of it will be inaccurate as well.  - RW