Abstract
‘Graphical excellence is the well-designed presentation of interesting data—a matter of substance, of statistics, and of design’. This quote from Edward Tufte’s (1983: 51) principles of graphical excellence captures the ambition behind this next stage in the development of the Featured Graphics section. In urban analytics and city science, visualisations matter because they bring together empirical substance, analytical method and visual judgement. They are most valuable when they do more than display results and when they also clarify relationships, reveal patterns, expose uncertainty and make complex spatial processes interpretable. The move towards Visual Analytics therefore builds on the original spirit of the section while advancing its academic purpose which is to publish scientific knowledge in visual form.
When Featured Graphics moved to Environment and Planning B, Alvanides and Dorling (2022) reminded us that visualisation has long been integral to how planning, design, geography and urban analytics communicate knowledge. This is pertinent to computational methods, urban modelling, spatial analysis and city science, as they all depend on visual forms to make complex analytical processes intelligible. This visual dimension is also central to planning practice, where complex urban analytics must often be communicated across professional, political and public audiences. The move of Featured Graphics established the section presenting visual work as a central part of the intellectual life of the journal.
This editorial marks the next step towards establishing this section as a curated venue for visual scholarship in urban analytics and spatial sciences. From September 2026 onwards, the section will be published under the title Visual Analytics as we are looking to sharpen its academic purpose. We continue to welcome concise, visually compelling contributions that speak to a wide readership and that present innovative ways of seeing cities, metropolitan regions, urban infrastructures, built environments and spatial systems. At the same time, we wish to make the expectations of the section more explicit, with the visualisation becoming the primary scholarly contribution. This should not be simply a figure extracted from a longer paper, an adapted conference poster, or a decorative representation of already completed analysis. The visualisation should be designed as an independent scientific artefact; a carefully composed visualisation that reveals structure, pattern, relationship or process in ways that are best understood through visual form.
This emphasis follows from the traditions on which the section already draws. Bertin’s (1983) Semiology of Graphics established a language for diagrams, networks and maps through which visual variables can be understood as structured means of reasoning. Cleveland and McGill (1984) gave graphical perception an empirical foundation, reminding us that visual encodings vary in how accurately they support comparison and interpretation. Tufte (1983, 1990) argued for analytical clarity and visual integrity in the display of quantitative information. Wilkinson’s (2005) Grammar of Graphics provided a formal basis for thinking about how statistical graphics are constructed, while Munzner (2014) has more recently given visualisation design a systematic analytical framework. In cartography and geovisualisation, MacEachren (1995) and MacEachren et al. (2005) showed that maps and spatial displays are not passive illustrations, but tools for exploration, interpretation and the communication of uncertainty. These foundations remind us that scientific visualisation is a method of knowledge production in itself.
Urban analytics now engages with forms of data and modelling that were only in their infancy in Featured Graphics’ early days: high-resolution mobility traces, ever-growing remote sensing archives, volunteered geographic information, social media data, street-level imagery, digital twins, building information modelling, simulation outputs, spatial networks and increasingly AI-assisted analytical workflows. These developments create opportunities, yet they also place new demands on visual communication, as Cheshire and Batty (2012) argued in this journal already more than a decade ago. The rise of what was coined big data increased the need for methods that make complex spatial relations perceptible and allow us to see patterns that would otherwise remain hidden in the data (Hennig, 2013). Increasingly, this also extends to fine-scale, three-dimensional and building-related forms of urban analysis, where buildings, infrastructures and urban systems are modelled as dynamic and information-rich environments. A technically sophisticated model does not automatically produce a meaningful graphic, nor does a large dataset automatically become insight when mapped. A visualisation worthy of this section should be a deliberate composition which includes careful hierarchy, appropriate encoding, contextualisation, accessibility and scientific judgement.
For this reason, Visual Analytics will place considerable emphasis on the independence of the main visualisation. Submissions should be centred on a single comprehensive scientific visualisation, or on a coherent visual sequence where the sequence itself is necessary to communicate the analytical contribution. The visualisation should be able to stand on its own within the journal page. It should contain all key components required for a full interpretation and sufficient contextual cues for readers unfamiliar with the place, dataset or subject matter. The accompanying text should make the figure self-contained, rather than become a miniature paper compensating for missing visual explanation. The work of explanation should primarily be carried by the visualisation itself.
We interpret visualisation broadly. In this sense, visualisation is not simply a way of presenting geographic data, but a means of translating complex spatial relations into forms through which new questions and interpretations can emerge (Hennig, 2013). It may include maps, diagrams, plots, networks, model outputs, visual composites, cartograms, image-based analysis, spatial narratives, comparative panels, annotated visual sequences, or hybrid forms that do not fit easily into existing categories. The core aim of the section is to publish scientific knowledge in visual form. The visualisation should translate complex data, models or research findings into a comprehensive representation that enables interpretation, comparison or discovery. We are especially interested in work that advances how urban and spatial research is seen.
As has long been the case in the Featured Graphics section, visualisations that are submitted should be largely self-explanatory, interesting to a wide audience and ideally novel in design, while properly acknowledging visual inspirations, publications, websites and code repositories. Authors should consider accessibility issues, including colour-vision deficiency and the careful selection of colour schemes (Harrower and Brewer, 2003), an international readership, and the value of combining elements into a single coherent figure. These principles remain central and are part of the scientific quality of the visualisation. Colour, contrast, typography, symbolisation and layout shape what can be read and what may be misunderstood. Principles of graphical excellence as described by Tufte (1983: 51), consisting of ‘complex ideas communicated with clarity, precision, and efficiency’ remain the key criterion for this section.
A further development concerns interactive and animated work. Many innovative visualisations in urban analytics are produced for digital environments. They may involve interaction, animation, filtering, zooming or linked views. Shneiderman’s (1996) information-seeking mantra and the later taxonomy of interactive dynamics by Heer and Shneiderman (2012) remain highly relevant to such work. However, a journal section must still publish a visual artefact that survives in static form. Interactive or animated projects are therefore welcome, but they must be accompanied by a dedicated static visualisation developed specifically for publication. A screenshot of an interface will rarely be sufficient. The static version should be meaningful on its own, making considered choices about which states, comparisons, sequences or annotations best communicate the underlying analytical contribution.
The accompanying text will also evolve. For Visual Analytics, we expect a more substantive commentary of approximately up to 1500 words. This text should still be concise, while allowing authors to explain and justify the scientific visualisation workflow. It should briefly establish the scientific background and relevance of the topic; explain why the visualisation was produced; document the data sources and analytical steps; describe the design rationale; identify software, tools and scripts used; and situate the visual approach in relation to relevant academic or design precedents. Open access to data and code is strongly encouraged wherever ethical, legal and practical conditions allow. Where original tools or scripts were developed, authors should make them accessible where possible, or explain clearly why they cannot be shared. This requirement is intended to strengthen the visual focus of the section. The text is not a substitute for the visualisation but a transparent account of how the visualisation came into being and why its design choices matter. In this respect, the section also aligns with the broader move towards reproducible and transparent computational urban science, including this journal’s own interest in urban data and code (Arribas-Bel et al., 2021). Reproducibility in visualisation means that readers should be able to understand the workflow, assess the relationship between data, method and visual form and, where possible, inspect or recreate the analytical process.
We are aware that changing the name of a section is not merely a matter of labelling. Featured Graphics carried a generous and open invitation: submit something striking, unusual and visually engaging. Visual Analytics keeps this invitation, while placing greater emphasis on scientific independence, methodological transparency and visual innovation. Conventional maps and graphics produced through standard software settings will continue to struggle unless they are transformed through an original analytical and visual contribution. Conversely, work that treats the journal page as a space for scientific visual reasoning, and that has clearly been designed for this purpose, will be strongly encouraged. Back when the concept of Featured Graphics was introduced in Environment and Planning A, Thrift (2009) wrote that the journal was trying to blaze a trail. Alvanides and Dorling (2022) showed why Environment and Planning B was the right place for that trail to continue. With Visual Analytics, we seek to carry the section forward by making its intellectual ambition more explicit. The section will publish visualisations that do not merely accompany urban analytics, but advance it in their own right. We look forward to submissions that show us, with clarity and imagination, how cities and spatial systems can be analysed, interpreted and communicated through visual form.