ArticleScientific data2022
Geographical characterisation of British urban form and function using the spatial signatures framework.
Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Article
- Combining Spatial, Genetic, and Environmental Risk Data to Define and Prioritize In Situ Conservation Units.Ecology and evolution · 2025Article
- Inferring building height from footprint morphology data.Scientific reports · 2024Article
- ecolo-zip: A global, rich and granular characterization of biogeophysical ecology for 1.5 million postal codes.Scientific data · 2023Article
- Evaluating Spatial Identity Based on Climate Adaptation in Small Cities.International journal of environmental research and public health · 2022Article
- Geographical characterisation of British urban form and function using the spatial signatures framework.Scientific data · 2022Article
- Functional signatures in Great Britain: A dataset.Data in brief · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
Abstract
The spatial arrangement of the building blocks that make up cities matters to understand the rules directing their dynamics. Our study outlines the development of the national open-source classification of space according to its form and function into a single typology. We create a bespoke granular spatial unit, the enclosed tessellation, and measure characters capturing its form and function within a relevant spatial context. Using K-Means clustering of individual enclosed tessellation cells, we generate a classification of space for the whole of Great Britain. Contiguous enclosed tessellation cells belonging to the same class are merged forming spatial signature geometries and their typology. We identify 16 distinct types of spatial signatures stretching from wild countryside, through various kinds of suburbia to types denoting urban centres according to their regional importance. The open data product presented here has the potential to serve as boundary delineation for other researchers interested in urban environments and policymakers looking for a unique perspective on cities and their structure.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.