Title and Parcel Mapping

Connecting Ownership to Cadastral Fabrics

Title mapping represents the extent of ownership as defined by a certificate of title. This information is of critical importance to municipalities as well as development, resource and utility companies. Typical uses include:

  • Assessment
  • Municipal and infrastructure planning
  • Landowner consultations
  • Operational activities that occur on the land

The foundation for title data is the cadastral base, or survey fabric, which depicts registered plans of survey. Title mapping needs to be kept in-sync with this cadastral base as new plans are added and spatial adjustments and improvements are made. Once the title data has been paired with a survey from the cadastral data, this “parcel” offers great value to government and industry alike.

Challenges in Title Mapping

The challenge many governments face with the collection, management and compilation of titles data is:

  • Complexity of magnitude: Provincial or state scale issues associated with complexity, update frequency and volume of these legal deeds for a district.
  • Labour-intensive, manual interpretations: In addition to the enormous amount of titles typically found in a region, often descriptions use metes and bounds which can only be interpreted and mapped manually.
  • Data formats: Data is often in multiple sources and formats, making it difficult to compile and maintain.
  • Costs: Inefficiencies leading to higher costs to compile and maintain the data.
  • Sustainment: Building and maintaining a current database can be challenging with government budgets.

Typically there is no linkage or spatial referencing that reconciles the line work contained within the cadastral datasets with the description of property ownership contained within Land Title certificates. Yet what governments need most is a GIS-ready “parcel” dataset for every ownership title in their district; a common, authoritative source of accessible, accurate, up-to-date title mapping information to provide a base for improved collaboration at all stages between the various levels of government, individuals and the private sector companies active on the land.

Streamlining Title Data

Recognizing that governments maintain data in different ways that have served their needs in the past, MNC uses a unique approach with clients to provide a seamless fit with their organization. Always focussed on providing cost effective solutions and quickly delivering business value, with minimal capital cost, we analyze and propose the most efficient ways to aggregate and build a title mapping database.

Building the title mapping database involves:

  • Designing a spatial database containing the special number connecting it to the cadastral database, and a legal description for each title.
  • Converting historical textual metes and bounds descriptions into a graphical format.
  • Integrating the title information into the cadastral map fabric.
  • Constructing title polygons based on the “extent” of the title.

We can receive data in any standard format and the processed data can be returned in any format – providing unparalleled flexibility. Data conversion and data quality are initially addressed on an as-needed basis allowing real business value to be delivered quickly.

The benefits of our approach to creating a title mapping dataset include:

  • Considerable cost savings through the reduction of redundant, repeated activities required to synchronize and update many systems.
  • Standard title mapping directly linked to the Alberta Land Titles Office Certificate of Title.
  • Access to title information through a single provincial cadastral base.
  • A cost effective, affordable, province-wide title mapping product available to the public, which provides consistency between municipalities and registry offices.
  • An accurate and reliable tool, which allows Land Title offices and all other stakeholders to view potential title conflicts.

MNC also offers experience in creating sustainment models which enables industry, the public and governments access to up-to-date datasets, under a recoverable cost model that fits budgets (such as affordable user-pay systems).