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| Compactness Index× | Street Network Analysis× | |
|---|---|---|
| Field | Urban Studies | Urban Studies |
| Family | Process / pipeline | Process / pipeline |
| Year of origin≠ | 2010 | 2017 |
| Originator≠ | Geographic shape-analysis tradition (Richardson, Cole; codified by Angel, Parent & Civco) | Geoff Boeing (OSMnx); graph-theoretic street analysis tradition |
| Type≠ | Geometric/morphological index of how compact a settlement footprint is | Graph-theoretic measurement of street-network structure and connectivity |
| Seminal source≠ | Angel, S., Parent, J., & Civco, D. L. (2010). Ten compactness properties of circles: Measuring shape in geography. The Canadian Geographer, 54(4), 441–461. DOI ↗ | Boeing, G. (2017). OSMnx: New methods for acquiring, constructing, analyzing, and visualizing complex street networks. Computers, Environment and Urban Systems, 65, 126–139. DOI ↗ |
| Aliases | Shape Compactness Measure, Polsby-Popper Index, Richardson Compactness, Perimeter-Area Compactness | Street Pattern Analysis, Road Network Metrics, Urban Street Connectivity Analysis, Configurational Street Analysis |
| Related | 4 | 4 |
| Summary≠ | A compactness index measures how compact the shape of a settlement, district, or built-up area is, almost always by comparing it to the circle — the most compact shape enclosing a given area. Classic indices such as the Polsby–Popper or Richardson ratio compare a polygon's area to its perimeter, while more elaborate measures compare interpoint distances or fitted circles, all returning a value of one for a perfect circle and falling toward zero as the shape becomes elongated, indented, or fragmented. Angel, Parent and Civco systematized these into a coherent family by showing that the circle is optimal on ten distinct geometric properties, clarifying which index answers which question. | Street network analysis treats a city's streets as a mathematical graph — intersections as nodes, street segments as edges — and measures its structure with graph-theoretic indicators of connectivity, density, centrality, and efficiency. From this representation come the metrics that distinguish a permeable grid from a tree-like cul-de-sac suburb: intersection density, average node degree, the share of dead-ends, betweenness centrality, and circuity (how much longer network routes are than straight lines). Tools such as Geoff Boeing's OSMnx made it routine to download, model, and analyse the street network of any place on Earth from OpenStreetMap, turning street-pattern analysis into a reproducible, comparative science of urban form. |
| ScholarGateDataset ↗ |
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