2021/07/15 by Martin Fleischmann, Alessandra Feliciotti, William Kerr +1 · 68 citations
Earth and Planetary Sciences · Engineering · Environmental Science · Mathematics · #Civil engineering #Computer science #Data science #Database #Engineering #Land Use and Ecosystem Services #Mathematics #Open science #Python (programming language) #Remote Sensing and Land Use #Scope (computer science) #Software #Statistics #Transparency (behavior) #Urban Design and Spatial Analysis #Urban morphology #Urban planning #Workflow
paper · pdf · doi:10.1111/gean.12302
published in Geographical Analysis 54(3), 536-558 (Wiley)
openalex publication_date 2021/07/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30
The recent growth of geographic data science (GDS) fuelled by increasingly available open data and open source tools has influenced urban sciences across a multitude of fields. Yet there is limited application in urban morphology—a science of urban form. Although quantitative approaches to morphological research are finding momentum, existing tools for such analyses have limited scope and are predominantly implemented as plug‐ins for standalone geographic information system software. This inherently restricts transparency and reproducibility of research. Simultaneously, the Python ecosystem for GDS is maturing to the point of fully supporting highly specialized morphological analysis. In this paper, we use the open source Python ecosystem in a workflow to illustrate its capabilities in a case study assessing the evolution of urban patterns over six historical periods on a sample of 42 locations. Results show a trajectory of change in the scale and structure of urban form from pre‐industrial development to contemporary neighborhoods, with a peak of highest deviation during the post‐World War II era of modernism, confirming previous findings. The wholly reproducible method is encapsulated in computational notebooks, illustrating how modern GDS can be applied to urban morphology research to promote open, collaborative, and transparent science, independent of proprietary or otherwise limited software.