cities_mapping

QGIS Grids Generator (hexagonal and square)

This Python module is designed for use in QGIS as a custom processing algorithm for generating hexagonal and square grids with aggregation of building data.

Features

• Automatically fetches city boundaries, buildings, and road networks using OSMnx.
• Generates H3 hexagonal grids or regular square grids over the city area.
• Aggregates values from a specified attribute column (e.g., r_floors) per grid cell.
• Computes normalized metrics (e.g., buildings per km², building density index).
• Applies graduated styling to output layers for effective visualization.

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Installation and Usage

1. Place the provided Python file into your QGIS Python scripts directory or load it manually.
2. Open QGIS.
3. Ensure the following Python libraries are installed in your environment:
   • osmnx
   • geopandas
   • shapely
   • numpy
   • h3
4. Run the register_algorithm() function or restart QGIS to auto-load the tool.
5. Open the Processing Toolbox and locate "Create Grid" under the Custom Tools section.

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Parameters

Parameter	Description
City Name	Name of the city for fetching OSM data
Grid Type	Select between Hexagonal, Square, or Both
Resolution	H3 resolution (integer from 1 to 15)
Cell Size	Cell size in meters for square grids (optional, calculated automatically)
Buildings Layer	(Optional) Custom building layer to override OSM data
Aggregation Column	Column name for aggregation (e.g., r_floors)

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Output Layers

• Hexagonal Grid Output: H3-based grid layer with aggregated values.
• Square Grid Output: Regular square mesh with the same computed attributes.

Each output contains the normalized_count field, representing:

• Object count (if no aggregation column is specified),
• Average value of the specified attribute (if provided),
• Building density index (when using r_floors).

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How It Works

1. The algorithm loads urban geodata using OSMnx.
2. It creates the grid over the city's bounding box.
3. Buildings are spatially assigned to grid cells using their centroids.
4. Aggregated statistics and density metrics are computed.
5. Results are visualized in QGIS with automatic styling.

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QGIS Urban Block Generator

This plugin provides a custom QGIS Processing algorithm for generating urban blocks based on roads, buildings, waterways, natural objects and railroads infrastructure.

Features

• Uses road geometry to define urban blocks via polygonization of road networks.
• Integrates railways and waterways into block segmentation.
• Automatically removes dead-end street segments and internal artifacts.
• Performs area-based filtering of blocks (e.g., excludes blocks without buildings).
• Aggregates building data by block (e.g., counts, average floors, FAR).
• Outputs styled block polygons.

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Installation and Usage

1. Copy the Python file into your QGIS Python script folder.
2. Launch QGIS.
3. Ensure the following Python libraries are installed:
   • geopandas
   • shapely
   • pandas
   • osmnx
   • networkx
4. Call register_algorithm() or restart QGIS to auto-load the tool.
5. In the Processing Toolbox, find the algorithm under Custom Tools as "Create Blocks".

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Parameters

Parameter	Description
Boundary Layer	Polygon layer defining city or district boundaries
Roads Layer	Line layer containing road geometry
Railroads Layer	Line layer with rail infrastructure
Buildings Layer	Polygon layer with building footprints
Waterway Layer	Line layer of rivers, canals, etc.
Aggregation Column	Optional: building attribute to aggregate (e.g., r_floors)
Target CRS	Coordinate system for processing geometry (default: EPSG:4326)

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Output

• A polygon layer representing urban blocks.
• Each block includes calculated values:
  • normalized_count: buildings per square kilometer or normalized attribute
  • far: Floor Area Ratio (if r_floors provided)

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How It Works

1. Roads and rails are merged and split at intersections.
2. Dead-end road segments are extended to improve connectivity.
3. Polygons are formed by polygonizing road networks.
4. Polygons without buildings or too large/small are removed.
5. Waterways are buffered and subtracted from block geometry.
6. Metrics are calculated per block (building count, average, FAR).
7. Result layer is styled with graduated color ramp.