buildingregulariser 0.1.3

A Python library for regularizing building footprints in geospatial data. This library helps clean up and standardize building polygon geometries by aligning edges to principal directions.

Building Footprint Regularization

A Python library for regularizing building footprints in geospatial data. This library helps clean up and standardize building polygon geometries by aligning edges to principal directions.

Example Results

Before and after regularization:

Overview

Building footprints extracted from remote sensing imagery often contain noise, irregular edges, and geometric inconsistencies. This library provides tools to regularize these footprints by:

• Aligning edges to principal directions
• Converting near-rectangular buildings to perfect rectangles
• Simplifying complex polygons while maintaining their essential shape

Inspired by RS-building-regularization, this library takes a geometric approach to building regularization with improvements for usability and integration with the GeoPandas ecosystem.

Installation

pip install buildingregulariser

Quick Start

import geopandas as gpd
from buildingregulariser import regularize_geodataframe

# Load your building footprints
buildings = gpd.read_file("buildings.gpkg")

# Regularize the building footprints
regularized_buildings = regularize_geodataframe(
    buildings, 
)

# Save the results
regularized_buildings.to_file("regularized_buildings.gpkg")

Features

• GeoDataFrame Integration: Works seamlessly with GeoPandas GeoDataFrames
• CRS Handling: Intelligently handles coordinate reference systems
• Polygon Regularization: Aligns edges to principal directions
• Edge Simplification: Reduces the number of vertices while preserving shape
• Geometry Cleanup: Fixes invalid geometries and removes artifacts

Usage Examples

Basic Regularization

from buildingregulariser import regularize_geodataframe
import geopandas as gpd

buildings = gpd.read_file("buildings.gpkg")
regularized = regularize_geodataframe(buildings)

Working with Different Coordinate Systems

regularized = regularize_geodataframe(
    buildings,
    target_crs="EPSG:3857"  # Web Mercator projection
)

Fine-tuning Regularization Parameters

regularized = regularize_geodataframe(
    buildings,
    parallel_threshold=2.0,   # Higher values allow more edge alignment
    simplify=True,
    simplify_tolerance=0.5    # Controls simplification level
)

Parameters:

• geodataframe: Input GeoDataFrame with polygon geometries
• parallel_threshold: Distance threshold for handling parallel lines (default: 1.0)
• target_crs: Target CRS for reprojection. If None, uses the input CRS
• simplify: If True, applies simplification to the geometry (default: True)
• simplify_tolerance: Tolerance for simplification (default: 0.5)

Returns:

• A new GeoDataFrame with regularized polygon geometries

How It Works

1. Edge Analysis: Analyzes each polygon to identify principal directions
2. Edge Orientation: Aligns edges to be either parallel or perpendicular to the main direction
3. Edge Connection: Ensures proper connectivity between oriented edges

License

This project is licensed under the MIT License

Acknowledgments

This library was inspired by the RS-building-regularization project, with improvements for integration with the GeoPandas ecosystem and enhanced regularization algorithms.