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Six tips on parcel mapping: Conversations with an expert

Forward thinking governments drive up economic prosperity by investing in GIS-based land management solutions, which improve operational efficiency, maintain accurate inventory records and deliver customer-oriented services.

We live in communities striving to be smart, a term now inclusive of a variety of or all definitions. Smart can mean citizen engagement in the decision-making process; it can mean online connectivity of services; it can be the replacement of legacy systems with innovative technology; it can even mean all of that.

In our rapid digital transformation societies, pressure is mounting on government agencies to modernize their land management systems to meet the escalating need for high quality land information and related services.

Forward thinking governments drive up economic prosperity by investing in GIS-based land management solutions, which improve operational efficiency, maintain accurate inventory records and deliver customer-oriented services.

The ArcGIS platform includes a robust suite of capabilities to support modern parcel mapping practices, including survey control planning and acquisition, digital survey plan integration, spatial accuracy improvements and cloud-based map services. Esri Canada’s Canadian Parcel Data Model (CPDM) provides Canadian governments with the capabilities to refine, edit, track and share land records.

A key component of a parcel mapping modernization initiative is the migration from legacy systems to the Canadian Parcel Data Model. This migration is a complex undertaking that requires advanced skills and experience to ensure success and minimize risk and downstream costs.

I spoke to Wendy Amy, GIS manager at MNC, an Esri silver-tier partner with expert consultants in cadastral and parcel mapping, about some of the key considerations MNC takes into account when assisting governments with their migration process. Wendy shared the top six.

1. Assess Topology: Does your source parcel data contain unintended gaps, slivers or overlaps? What level of effort will be required to resolve topology?

Why this is important – The parcel fabric relies on topological correctness when representing and storing parcel data. If your data has errors, you will most likely experience problems when adjusting or manipulating parcels. This will be frustrating, and the topological errors will be more time consuming to correct once inside the parcel fabric.

2. Assess Curve Data: Does your source parcel data contain densified line segments representing curves which will require curve generation? What level of effort will be required to re-create curves like cul-de-sacs?

Why this is important – Converting densified arcs/line segments into true curves prior to migration will improve the overall integrity of the fabric. For example, a cul-de-sac parcel surveyed with a true curve boundary is best represented as such in the fabric. Reducing or eliminating unintended densified arc geometries will improve performance during maintenance and adjustment operations.

3. Assess Connectivity: Does your source parcel data support connectivity with connection lines or road parcels? What level of effort will be required to create a connected fabric?

Why this is important – To successfully perform a spatial adjustment, all the parcels within the adjustment area must be well connected either by adjacency or by connection lines.

4. Assess Control:  Will your migrated source parcel data and control points support performing spatial adjustments in the fabric? What level of effort will be required to collect and activate adequate control?

Why this is important – Control points represent known locations on the ground (real world coordinates). The parcel fabric least squares adjustment engine utilizes control locations to statistically calculate the best spatial locations for the parcel corners. The variance between the unadjusted and adjusted parcel corner locations will dictate the number of control points required to perform a successful adjustment.

5. Assess Coordinate Geometry (COGO) Fields: – Does your source parcel data contain survey measurements for boundary lines or will the boundary line attributes be inversed?

Why this is important –  The “best” parcel fabric retains the original survey dimensions as attributes to the boundary and connection lines. These values are utilized in the least squares adjustment to continue to improve the absolute and relative spatial geometry of the fabric. Often budgets do not support the capture of this information; therefore, boundary line COGO attributes are inversed from source data. This will have impacts on adjustment and integration approaches that will require consideration.

6. Assess Attribution: Does your source parcel data attribution provide suitable information to populate the parcel fabric schema?

Why this is important – It is best practice to consider and create a data migration matrix for populating the fields provided in the Canadian Parcel Data Model (CPDM). Complete and correct data attribution will better support parcel maintenance functionality and workflows.

Have I managed to spark your curiosity to learn more? I hope I did. Check out Esri Canada Land and Property or read more about MNC in ArcNorth News.

About the Author

Alia Kotb is Esri Canada’s Community Maps Advocate. She steers communities to enrich their GIS offering with the Community Map of Canada to better serve their constituents and stakeholders. She prefers using an energized approach to challenges, exploring solutions with a curious disposition rather than simply applying routine processes. Alia has been in the GIS industry for more than 10 years. With an MBA in International Business and a BA in Journalism and Mass Communication, she is a journalist at heart who always likes to ask “why” and “what if” to uncover deeper insights to problems. Outside of work, Alia is an avid traveller and you’ll always find a book in her bag.

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