Overview of Survey Data


The geometry of land survey data assumes three separate incarnations, each with their own audiences, usages and behaviors. The incarnations are 1) field measurements taken from survey instruments, 2) record boundary data from survey plats describing the relative positions along boundaries and other items affecting boundary location, and 3) seamless parcel coverages in GIS representing the best guess on the positions of parcel corners based on a unification of all pertinent survey data.

The one common factor applying to all measurement data is that it is inexact. It has slop (error) and mistakes (blunders). It is important to quantify and track the reliability of each piece of survey data so its suitability can be determined for various purposes. This reliability is also crucial for decisions toward responsible maintenance of data.

Traditional surveying applications help transform field measurements into record boundary data, (1 into 2) often assuming the survey occurs on a plane surface. Measurements within the survey are adjusted to accomplish geometric closure, thereby providing Cartesian coordinates. The error is discarded as well as the ability to determine the positional tolerance of the coordinates. Note: The BLM-sponsored field software, CMM, improves on the traditional COTS software by tracking error throughout the process and providing error ellipses of the derived coordinates which are always geographically based.

GMM provides for input of control coordinates and record data from various surveys. It essentially stitches together these survey data into a single fabric, providing analysis of the error as well as polygon attribute data to serve up to a GIS environment, (2 into 3). GMM also provides for the subdivision of sections in the PLSS using standard rules. Exceptions to the rules, as determined through interpretation of the survey plats, are stored as processes that deal with each exception. These "constructions" can be replayed at any future time, always after any readjustment of the survey measurement data. This is a critical feature that will have application outside its current implementation.

Traditional GIS software has stitched together a base of record boundary data and incorporated vectorized raster data. Since the reliability of the survey data is unknown and most adjustment processes cannot take data reliability into the equation, the resulting positional tolerances are unknown. Today, it is absolutely critical to provide a basis for GIS accuracy commensurate with current measurement and computer technologies. This is the basic underlying concept behind recent articles in many professional journals on the need to involve surveyors in GIS efforts. Merely involving surveyors will not solve the problem if we do not provide the tools for them.

Yet even providing a set of tools is not sufficient. We must also provide a cohesive system of standard data structures to move survey data through its incarnations from field instruments into GIS coverages.


The Ultimate System

The concept of NSDI requires a single, seamless parcel coverage that will meet the needs of all users. The implications are that each agency will insist on maintaining and publishing the parcels that it has jurisdiction over. This solution, however, places pressure on targeted agency data custodians to rapidly incorporate new survey data and in many cases to jointly share maintenance of common data with data custodians of agencies having adjacent or overlapping jurisdiction. There exists the need to streamline the flow of survey data from the field and into an office environment where it will be finally be reviewed by the data stewards prior to integration of the new data into the seamless coverages.

The easiest and most obvious action to take in streamlining this data is to enhance existing survey software, including GPS software, to be aware of the official parcel coverage. Collection of survey data is very decentralized compared to the heavy centralization of the process to merge new survey data into the fabric that is the official current parcel coverage. If current parcel coverages were available from a website, then the new field positioning and traversing applications would be able to utilize existing point and parcel identifiers, greatly facilitating the eventual incorporation of new data into the main fabric.

One of the problems that will have to be overcome is that the best geometric analysis/adjustment solution will often require data from other agencies and will often affect those agencies’ boundaries. To achieve edgematching and cohesiveness, these agencies will share in the maintenance of the measurement data. Processes should be institutionalized at the application level to assure that data custodians have appropriate access to neighbor agency data and to assure that updates can be entered, reviewed, accepted and put online as quickly as possible.


About the PLSS

The requirements of PLSS come into play during section subdivision and uniquely identifying parcels. While the geometric analysis and adjustment of surveyed lines are unaffected by PLSS rules, subdivision of sections represents quite a challenge due to the peculiarities of subdivisional rules. The BLM has profited from a rule-based point identification scheme for PLSS corners, a system used both by humans and machine to organize and manipulate the data.



We can do best if we get to a common vision with survey data. The BLM’s GCDB Technical Advisory Group (GTAG) is willing to participate in any dialogue that clarifies where we all should be heading in this venture. - Dennis McKay and GTAG