momepy

momepy is a powerful Urban Morphology Measuring Toolkit designed for the quantitative analysis of urban form. It provides a comprehensive suite of functionalities to measure various dimensions, shapes, and spatial distributions of urban elements, transforming raw spatial data into actionable insights for scientific research. This tool extends beyond basic GIS operations, enabling deep, systematic investigations into the intricate patterns and structures that define our cities.

This toolkit finds extensive application across various scientific and computational domains. In urban climate and environmental modeling, momepy is crucial for generating urban form metrics essential for parameterizing Urban Canopy Models (UCMs). Researchers can use it to derive detailed geometric properties of urban landscapes, improving the accuracy of simulations for urban energy balance, heat island effects, and air quality. For instance, it can help map urban form metrics to UCM parameter sets, ensuring physical consistency and interpretability in advanced climate models.

In the realm of public health and social sciences​, momepy facilitates the analysis of built environment determinants that influence health outcomes. Researchers can quantify urban design features such as walkability, street connectivity, and green space distribution, which are directly linked to physical activity levels, obesity, and cardiovascular health. By providing measurable indicators of the built environment, the tool supports the construction of causal pathways between urban design and health, enabling evidence-based interventions. It also aids in understanding the spatial context of social phenomena, such as analyzing historical urban layouts and their impact on societal structures or understanding the optimal siting for community resources.

Furthermore, momepy is invaluable for urban planning and design​, allowing for the objective assessment and comparison of urban forms. It can be used to analyze land use mix, street network patterns, and density variations, providing data-driven foundations for sustainable urban development strategies. Its capabilities are essential for researchers seeking to define and differentiate various built environment determinants from social environment features, contributing to a holistic understanding of urban systems.