New Paper- Online Interactive Mapping: Applications and Techniques for Socio-Economic Research

I have a new paper published in Computers Environment and Urban Systems- Online interactive thematic mapping: applications and techniques for socio-economic research. The paper reviews workflows for creating online thematic maps, and describes how several leading interactive mapping sites were created. The paper is open access so you can download the pdf for free.

Figure_04
Global Metro Monitor by Brookings- http://www.brookings.edu/research/reports2/2015/01/22-global-metro-monitor

The paper features web mapping sites by Oliver O’Brien (http://www.datashine.org.uk), Kiln (http://www.carbonmap.org) and Alec Friedoff at Brookings (http://www.brookings.edu/research/reports2/2015/01/22-global-metro-monitor). Many thanks to these cartographers for agreeing for their work to be included in the paper, particularly Ollie O’Brien who also kindly provided comments on the paper draft. Also many thanks to Steven Gray at CASA who set up the hosting for the LuminoCity3D site.

Here’s the paper abstract-

Recent advances in public sector open data and online mapping software are opening up new possibilities for interactive mapping in research applications. Increasingly there are opportunities to develop advanced interactive platforms with exploratory and analytical functionality. This paper reviews tools and workflows for the production of online research mapping platforms, alongside a classification of the interactive functionality that can be achieved. A series of mapping case studies from government, academia and research institutes are reviewed.

The conclusions are that online cartography’s technical hurdles are falling due to open data releases, open source software and cloud services innovations. The data exploration functionality of these new tools is powerful and complements the emerging fields of big data and open GIS. International data perspectives are also increasingly feasible. Analytical functionality for web mapping is currently less developed, but promising examples can be seen in areas such as urban analytics. For more presentational research communication applications, there has been progress in story-driven mapping drawing on data journalism approaches that are capable of connecting with very large audiences.

And here are some example images from the mapping sites reviewed in the paper-

Datashine
Datashine by Oliver O’Brien and James Cheshire- http://www.datashine.org.uk
Luminocity
LuminoCity3D by Duncan Smith- http://luminocity3d.org
Figure_06
The Carbon Map by Kiln- http://www.carbonmap.org

Mapping the Global Urban Transformation

One of the best datasets for understanding the explosive growth of cities across the world in the last 65 years in the UN World Urbanisation Prospects research, which records individual city populations from 1950 to 2014, and includes predicted populations up to 2030. I have been meaning to create an interactive map of this fascinating data for a while, and have now completed this at- luminocity3d.org/WorldCity/

UNWCP_global

The map uses proportional circles representing city populations in the years 1950, 1990, 2015 and 2030, highlighting the regions in the globe with the most spectacular urban growth, and the time period when this growth occurred (I first saw this technique used in a static map at LSE Cities Urban Age). Naturally China, India, Africa and Latin America jump out in the map, while Europe is largely static (except for Turkey). You can also explore time-series graphs and statistics for individual cities by moving your cursor over each city.

UNWCP_shanghai

The site also includes queries of the city statistics, for example highlighting the world’s largest cities in different years. It’s amazing to see the dramatic changes between 1950 and 2015. London was the 3rd largest city in the world in 1950, and is now the 36th. In 1950 there were no African cities and only one Indian city in the world’s top 12, but by 2030 this list is dominated by South Asian, East Asian and African cities.

UNWCP_largest2030

Mapping Tools Used
This map is the first time I’ve tried out CartoDB for interactive mapping, and I’m impressed with this tool. The main advantage of CartoDB for thematic mapping is the ability to perform SQL queries on the client-side, allowing map features to be highlighted interactively (this is used for the map queries on the World City site). There is also the ability to comprehensively restyle map symbology from the client using CartoCSS (this feature requires a full map refresh). Certainly sophisticated interactive mapping functionality is possible using CartoDB. It’s also Leaflet.js based, which is what I’m used to from the previous LuminoCity3D project.

Cities and Mega-City Regions
Measurements of city populations inevitably depend on where regional boundaries are defined, and the UN database is by no means perfect. The job of trying to integrate the hundreds of different city definitions used by each individual nation-state is no easy task. The UN tries to apply the concept of metropolitan agglomerations across the globe, but data is not always available and some cities are measured using administrative boundaries, which leads to population underestimation (full details on the UN methodology).

One of the interesting definitional issues that arises is around how very large polycentric regions have emerged in parts of the globe and beginning to look more like a single giant city. One of the most famous is the Pearl River Delta Megacity Region-

UNWCP_shenzhen

There are so many giant cities in close proximity that the map symbology struggles. Hong Kong, Guangzhou, Shenzhen, Foshan and Dongguan are all huge cities. Shenzhen in particular has experienced the most rapid growth of any city in history, growing from small town in 1980 to 10.7 million people in 2015. The combined population of these cities would make the Pearl River Delta the largest city in the world if a wider regional definition was employed.

ESRI Urban Observatory- the right model for city crowdsourcing?

This month ESRI made an interesting move into the field of global city data with the launch of Urban Observatory (TM). The site has some great interactive visualisation ideas with simultaneous mapping of three interchangeable cities, linked navigation and indicator selection. It provides an intuitive interface to explore the diverse forms of world cities-

UrbanObservatory

Furthermore this ambitious project is intended to be an extensible platform. Jack Dangermond (billionaire founder of ESRI) and Richard Saul Wurman (founder of TED with a long-standing interest in city cartography) discuss in the introductory video how they want many more cities to join in, to crowdsource city data from around the world, using the ArcGIS online platform.

So is this project going to be the answer for all our global urban and smart city data needs? Well I think despite the great interface, as a city crowdsourcing model ESRI’s urban observatory is not going to work. But it’s interesting to explore why, particularly in relation to the bigger questions of whether the open city data revolution is going to be truly global and inspire a new era of urban analysis and comparative urban research.

ESRI’s site states that “information about urbanization does not exist in comparative form”. In reality comparative urban analysis is a growing trend across many sectors, from international organisations like OECD, EU and UN (including the original UN Habitat Urban Observatory); to environmental organisations like ICLEI and C40; to economically focussed organisations like the World Bank and Brookings; to global remote sensing providers like the USGS; to major commercial data producers in transport and telecoms; to the many urban academic research centres around the world (including the two London based centres I’ve worked for, CASA and LSE Cities).

Global cities data example- GaWC Network at Loughborough
Global cities data example- GaWC Network at Loughborough
CASA- deprivation in UK cities example.
CASA- deprivation in UK cities example.
Brookings MetroMonitor- comparison of US cities' economic performance
Brookings MetroMonitor- comparison of US cities’ economic performance

 

LSE Cities- over a decade exploring comparative urbanism
LSE Cities- over a decade exploring comparative urbanism

There’s a rich and growing field of data providers and analysis techniques to draw on for comparative urban analysis. Indeed the ability to gather and analyse urban data is absolutely central to the whole Smart City agenda. But there are clearly many challenges. What do cities gain by opening up their data? Who then owns the data and controls how it is presented? Who selects what data is included and excluded?

I believe the natural platform for civic data (and subsequently for the international comparison of urban data) will be an open platform with wiki features to encourage civic engagement. This provides the answers to the above questions- citizens gain from better access to data and institutional transparency; citizens own the data and have a say in what is included and how it’s presented. This is the model for current successful open data sites like the London Datastore, where anyone can access the data, and Londoners can request new datasets (backed by freedom of information legislation). Unfortunately the governance situation is of course much more complicated for the international comparison of cities, and this has limited progress.

As the world’s leading provider of GIS software, ESRI are in a strong position to integrate global datasets, and have clear commercial interests in amassing urban data for their clients. But it’s much harder to answer questions about who owns and controls data in their urban observatory project. Arguably this will limit the number of cities volunteering to take part, and limits the project’s ability to respond to the diverse demands of global cities and their citizens.

A further huge challenge in comparative urbanism is in developing the right analytical techniques and indicators to answer key urban questions. This will inevitably require more sophisticated analysis tools than a set of thematic maps, and needs to draw on the many research strands developing the most relevant analytical tools.

Overall there will be some exciting competition in the coming months and years in the expanding market of international urban data integration and visualisation, with different models from commercial, government and academic contexts. ESRI’s urban observatory is an innovative project, and should stimulate further advances.