Initial Steps Towards an Open Cadastre in the UK: A Case Study

1. The Meadows Community Cadastre

Take a closer look

2. Create your own Community Cadastre

Contents

• STEP 1: Download the Open Source Software
• STEP 2: Mapping with QGIS
• STEP 3: Machine Learning in Jupyter Notebooks
• STEP 4: Uploading Data to Felt

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STEP 1: Download the Open Source Software

• Download QGIS: Get the latest version from QGIS.org
• Download QGIS plugins: Get the latest version from MichaelMinn.com

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STEP 2: Using QGIS to Map the Geospatial Data

Getting Started

• Download files: Rename the downloaded files as a_boundary, b_land, etc. to be your new layers, and rearrange them as required.

Projection

• Ensure Correct Projection: Transform your local British data layers to British National Grid (BNG - 27700).

Data Cleaning

Wards

• From the Local Authority Ward Boundaries, select only the relevant ward(s) (i.e., Meadows)
• Remove any unnecessary columns from the attribute table, as this will slow down the processing and be unuseful to users viewing the map.

Land Polygons

Location

• Select land polygons that are in the area of interest.
• Use 'Select by Location' to choose polygons that intersect with a_boundary.

Size

• Find out the area of the largest single-dwelling piece of land.
• Filter polygons with Area > 1283 and remove them.
• Remove unnecessary columns from the attribute table.

Building Polygons

• Use the field expression calculator to filter house-related buildings "building" = 'detached' OR "building" = 'house' OR "building" = 'residential' OR "building" = 'semidetached_house' OR "building" = 'terrace' OR 'building' = 'yes'

Additional Steps

• Invert feature selection and delete non-residential features.
• Make the layer editable and delete extra large houses (Area > 244).
• Select garages by feature type and remove them.

Attribute Editing

• Add an attribute named Private.
  1. Open the attribute table
  2. Make the layer editable
  3. Open the attribute field calculator
  4. Create a boolean field with the expression overlay_intersects (ncc_owned_layer)

Spatial Join

• Use MMQGIS -> Combine -> Spatial Join
• Output as a new layer called cadastre

Final Steps

• Calculate the building-to-land ratio using the attribute table
• Save changes to the layer
• Export layer as .csv (save as cadastre_output)
• Manually label some data based on available archetype maps or visual survey

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STEP 3: Machine Learning in Jupyter Notebooks to Predict Building Age

• For full details run the code, and read the comments in the notebooks.
• But start off here by downloading the code and running locally:

Clone the directory

$ git clone [https://github.com/InfobyAdrienne/Test-React-Express.git](https://github.com/99ltaylor/community_cadastre.git)

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STEP 4: Using Felt to Upload the Data

• Register for a free account at Felt.com
• Use their drag-and-drop file system to upload your data.

See your community cadastre take shape!