Post Covid-19 Urban Planning Strategies: Lesson from Hong Kong Spatial Analytical Approach (SAR) and Suggestions for Lagos

Oluwole Soyinka is a postdoctoral researcher at the Department of Urban Planning and Design, Faculty of Architecture, The University of Hong Kong.

The global environment and economy are currently faced with the dilemma of (novel) coronavirus disease 2019 (COVID-19) and cities around the world are affected differently. Debates are on-going on the causes, effects and solutions, with questions being asked whether we would be completely free from the impact of the COVID-19 pandemic. African cities already affected with critical urban challenges such as housing, transport and governance are further confronted with another kind of environmental health challenge. COVID-19 is associated with density and space, thus requires an urban planning response which must be spatial and consider density. Although, it is evident that there is no single silver bullet to resolve the COVID-19 pandemic and no one urban planning strategy can solve it, a holistic multi-sectoral strategy with significant integrated spatial and density analytical approach is essential for post-COVID-19 urban planning strategies.

Even though several efforts have been identified and adopted in response to the pandemic, most seem to be promoting wide-spread or low-density (sprawl) development approach, a far departure from the compact smart city development approach which was promoted in pre-COVID19 times. I disagree with the current common discourse against smart, compact high-density city planning approach based on evidence from many cities. For example, Hong Kong, which is a high-density city has never had a COVID19 induced lockdown and had managed to contain the virus better than some low-density cities of the United States and United Kingdom (World Health Organisation, National Health Commission, & Health Bureau of Macao, 2020).

I believe that for post-COVID-19 planning in African cities, adequate integrated space density measurement strategies for would be more effective. I therefore outline the Hong Kong Special Administrative Region (SAR) experience and suggest how Lagos can adapt to it

Network-based Analytical approach for Lagos metropolis: Lesson from Hong Kong

Hong Kong SAR of China with 1,106.81km² land area and approximately 7,507.400 resident is a high-density city with smart compact city characteristics. Similarly, Lagos metropolis with over 17million resident and 1,171km² land area is growing towards a high-density city, especially with the redesign and transition of development areas such as Victoria Island and Ikoyi and the new Eko Atlantic city. Thus, it is essential to project the post-COVID-19 planning approach of Lagos metropolis to adopt spatial density analytical approach for smart high-density city development. This strategy will ensure real-time precise morphological, and geometric re-ordering of land uses and subsequently promote sustainable urban development that is resilient as  exemplified in the case of Hong Kong.

Figure 1: Hong Kong as a smart, compact high-density city

Photo credit: https://pixabay.com/photos/hong-kong-china-asia-tsim-sha-tsui-5249670/

Hong Kong adopted several spatial and density analytical measuring approaches (Sun, Webster, & Zhang, 2019) to develop COVID-19 related reponse strategies such as spatial separation, testing and tracing. As at the time of this article, Hong Kong COVID-19 had been able to contain the virus effectively with 1,108 total confirmed cases, and only four deaths. This result is remarkable considering Hong Kong as a high-risk area based on it high population density, and her several busy boundary points with mainland China, as well as the high rate of everyday work and home cross border commuting relationship with Shenzhen. Shenzhen is a closely related province to Wuhan and the origin of the COVID-19.

The example of Hong Kong’s urban planning density and spatial analytical approach can be contextualised for post COVID19 urban planning in Lagos.  For example, the introduction of geometric parameter referencing (digitised) and configurational parametric measurements to influence the required urban planning outcomes are key. These strategies include Real-time GIS mapping and digitisation; Machine learning and big data spatial analytics; Metric space and mathematical computation mechanic and Space syntax and network analysis, such as ‘Spatial Design Network Analysis (sDNA)’.

These proposed approaches are not totally new, however, their application with contemporary information technology communication (ICT) software’s in COVID-19 clinical treatment simulation approach will inevitably produce an innovative planning approach. Thus, I suggest the above four spatial analytical approach as a response to Post-COVID-19 urban planning strategies, and I also propose the adoption of sDNA to achieve this efficiently.

Figure 2: Application sDNA in Hong Kong for connecting the city pedestrian network in three-dimensional urban analytics.

Source: Sun et al. (2019)

Cooper and Chiaradia (2020) described sDNA as a “toolbox for 3-d spatial network analysis, especially street/path/urban network analysis, motivated by a need to use network links as the principal unit of analysis to analyse existing network data. sDNA software can be used with QGIS or Arch GIS, Rhinoceros, AutoCAD or AutoCAD Map and the command line includes Python API. sDNA is suitable for urban planning spatial analytical response to post-COVID-19 urban planning because “it computes and measures accessibility (reach, mean distance/closeness, centrality and gravity), flows (bidirectional betweenness centrality) and efficiency (circuit) as well as convex hull properties, localised within lower and upper bounded radial bands (Cooper & Chiaradia, 2020, p. 1).

I believe that a post COVID19 Lagos should leverage on technology for spatial and density related development, and recommend further study and adoption of sDNA for spatial analytics and urban planning response in post-COVID-19 urban planning for Lagos .

References

Cooper, C. H., & Chiaradia, A. J. (2020). sDNA: 3-d spatial network analysis for GIS, CAD, Command Line & Python. SoftwareX, 12, 100525.

Sun, G., Webster, C., & Zhang, X. (2019). Connecting the city: a three-dimensional pedestrian network of Hong Kong. Environment and Planning B: Urban Analytics and City Science, 2399808319847204.

World Health Organisation, National Health Commission, & Health Bureau of Macao, S. A. R. (2020). Countries/area with reported cases of Coronavirus Diseases-2019 (COVID-19). Retrieved from https://www.chp.gov.hk/files/pdf/statistics_of_the_cases_novel_coronavirus_infection_en.pdf

The views expressed in this article are those of the author(s) and not necessarily those of the Centre for Housing and Sustainable Development or the University of Lagos, Nigeria.