The Fabric of Jacksonville Beach

July 1, 2009
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Inaccurate documentation of property boundaries poses many problems for local governments in the United States. Spatial inaccuracies within a land base can lead to the inadvertent placing of utilities or other publicly owned facilities on private property when originally intended for placement in a right-of-way. Moreover, erroneous parcel information can often lead to disputes over property lines.

The City of Jacksonville Beach in northeast Florida experienced some of these challenges. Large numbers of parcel boundaries and right-of-way lines did not correspond to their known dimensions or locations, and these discrepancies prevented the city from providing a variety of public services with a high level of confidence and precision. “Without accurate parcel and right-of-way information, the city couldn’t move forward with its infrastructure projects on a timely basis,” explains Donald F. Terrell, senior network/GIS administrator for the City of Jacksonville Beach Information Technology Division. “A more-precise land base would allow us to leverage this information among multiple city departments and introduce new applications and improved services.”

A comparison of the old 2008 land base (shown in orange) to the rectified 2009 land base.

The city began exploring possible solutions. Typically, local governments reconcile boundary lines using enhanced aerial photography or orthophotography and other planimetric data to visually place the location of parcels. However, Reynolds, Smith and Hills Inc. (RS&H), a facilities and infrastructure consulting firm with an office nearby, had another idea for the city that would allow it to achieve a higher level of accuracy. RS&H proposed that the city improve its land base using the Cadastral Editor tools in ESRI’s ArcGIS Survey Analyst extension--an advanced tool set that facilitates the creation and maintenance of survey and cadastral data. The firm had spent the last several years gaining experience in geographic data management with ArcGIS and ArcInfo, and the GIS team was eager to expand its capabilities to encompass parcel management. The Jacksonville Beach project provided the ideal opportunity to begin working with the advanced cadastral data management tools.

A U.S. Army Corps of Engineers survey marker that was collected with the GPS receiver and incorporated into the fabric as a control point.

Data Cleanup and Field Collection

Prior to building the cadastral fabric, the team first performed a massive cleanup effort on the existing parcel data. The most common data issues involved pseudo nodes, overshoots, undershoots and densified arcs. Pseudo nodes are arbitrary nodes located along the parcel vertices, which split parcel lines into multiple segments. Without correcting pseudo nodes, the dimensions would be split between segments causing multidirectional distortions in the parcel shapes. Undershoots occur when the parcel line is too short, which leaves a gap, while overshoots occur when the parcel line is too long, which leaves a dangling node.

A closer look at two parcel dimensions after rectification. The black numbers represent what the dimensions should be; the red numbers are the dimensions after rectification. The blue triangles are the corner lot points provided by the surveyor.

These two errors became a major issue when building the polygon layer of the fabric since the Cadastral Editor workflow in ArcGIS Survey Analyst does not create polygons unless parcel line segments are all connected at nodes. Densified arcs are a sequence of many straight lines that are connected to make a curve. Since the fabric only supports true arcs, RS&H acquired one of ESRI’s developer samples called the CurveConversion command, which converts densified arcs into true arcs.

To ensure accuracy, the team relied on recent survey data gathered from a roadway project in Jacksonville Beach. Because the data sets--specifically the corner points--were stored in a centralized GIS database at RS&H, new surveys were not required for this project.

Concurrent to the data cleanup effort, the team collected GPS bench marks, monuments and known locations of points, such as manholes, fire hydrants and light poles, from high-resolution aerial photography provided by the city. Using this information, the team created a 14-section grid dividing the project at major roadways. The team collected points using a Trimble GeoXH GPS unit coupled with a Zepher antenna, which provided submeter horizontal accuracy. These points were then post-processed prior to incorporating them into the fabric to ensure subfoot horizontal accuracy.

One of the 14 grid sections after the parcels have been rectified. All blue lines represent parcels that now fall within the 5-foot tolerance. All green lines represent parcels that need more information before correction.

Parcel Rectification

Once the clean data and control points were built into the cadastral fabric, the team began parcel rectification. With nearly 15,000 parcels to rectify, RS&H designed a workflow that maintained the 14 grid sections and created a separate fabric for each one. This step streamlined the quality control and assurance process.

At the project’s onset, the team set a 5-foot tolerance on the parcels and also identified three status categories: in progress, review and historical. In-progress parcels were those that still needed to be edited, while review parcels were those that had been edited but did not fall within the 5-foot tolerance or were missing dimensions. The historical parcels were edited and were within the 5-foot tolerance. The initial analysis of the data involved identifying parcels that exhibited the correct dimensions and marking them as historical. Parcels in the review category were plotted on an aerial background and given to the city for final approval or direction for further correction.

While rectifying the parcels, the team used high-resolution aerial photography as the base layer to ensure proper placement of city blocks after they were disconnected and edited. It was extremely important to maintain and correct right-of-way information when reconnecting the parcel blocks. The accuracy of parcel corner points and dimensions was maintained within 5 feet.

One city block that has been disconnected from the fabric to correct the dimensions within the Cadastral Editor environment.

A Proven Success

The cadastral data management tools allowed the city and RS&H to create a topologically integrated geodatabase, or cadastral fabric, made up of lines, line points, points and polygons that represent each parcel layer. Once the existing parcel data sets were integrated into the cadastral fabric, new fields were generated by the software containing the dimensions of each parcel segment. These dimensions were then compared to known dimensions collected in the field and corrected using Cadastral Editor coordinate geometry (COGO)-based data entry capabilities.

The City of Jacksonville Beach’s land base upgrade is now benefiting the city’s public safety and planning initiatives in a variety of ways. For example, the police department is using the new information to create more-accurate maps for its emergency dispatch units and computerized Enhanced 911 emergency services system. These improvements are possible due to the more-accurate right-of-way data set, which allows the creation of a more-precise street center line shapefile used in the geocoding process. In addition, the improved land base is being used by the city’s planning and development, public works, and electric departments to make better decisions regarding the location and placement of utilities as well as to better manage the city’s assets.

“The new land base gives us more control over what infrastructure is out there and how it’s working,” Terrell explains. “Now our staff can make better decisions more quickly and with much more confidence.”

For RS&H, the project is expected to generate new opportunities in creating and maintaining cadastral data as other cities and counties seek ways to improve land base accuracy and infrastructure control.

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