Planning sustainable urban-industrial configurations: relations among industrial complexes and the centralities of a regional continuum

ABSTRACT

Production models’ flexibilization in capitalist economies continues to transform industrial activities’ spatial organization in a regional continuum. Placed in planned complexes located on cities’ fringes, firms often stand inaccessible from regional circulation routes, which hinder activities’ long-term economic sustainability. Further changes are impending, as forthcoming Smart Manufacturing logistics require efficient linkages between local and regional transportation models. Such issues compel urban planners, economists and policymakers to re-evaluate industrial territories’ imprint on metropolitan dynamics and enact proper strategies towards the industry. In this paper, the role of road-circulation network centralities on industrial complexes’ placement in a regional continuum is analysed, refining the existent methods to assess industry spatial configuration and agglomeration logics. Empirical cases comprise five Brazilian industrial complexes in Porto Alegre’s Metropolitan Region. Hypothesis is that road-circulation network centralities’ hierarchies (closeness and betweenness) have positive correlations to industrial placement patterns at regional and inner-complex scale, informing regional contiguity dynamics amid discontinuous industrial spaces.

KEYWORDS:

• Urban planning
• regional planning
• industrial complexes
• network analysis

Acknowledgements

This research is equally sponsored by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brazil (CAPES) – Finance Code 001 and by Università di Pisa (IT).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Sustainability in this case is defined as the local-regional capabilities of maintaining a long-term economic dynamism (economic sustainability), as well as assuring the efficient use of space and infrastructure (morphological sustainability).

2 Hoffman and Rüsch (2017) discuss logistics as being a major bottleneck in the diffusion of Industry 4.0 production models.

3 Morceiro and Guilhoto (2019) refer that Brazil exhibited the third highest retraction in industrial sector gross added value (GVA) among 30 countries, on a data series starting from 1970, after only Australia and the UK. The authors (2019) consider this a premature deindustrialization, since the productive structures weight on GDP began to decrease before the GDP per-capta could grow, an antithesis, when compared to other industrialized countries’ process.

4 According to Proulx (2008) and Lévesque (2008), the industrial complex concept provides an interesting frame for modelling territorial phenomena like clustering, since it singles out the economic specialization of loose institutionalized zoning parameters.

5 Porto Alegre’s Metropolitan Region is composed of currently (2019) by 34 municipalities; however, these analyses use a road-centre line map comprising only the 14 municipalities that constitute the first PMAR iteration (1970). These cities were chosen because they exhibit higher conurbation indexes (Rigatti 2009), forming a more cohesive road-circulation network; and because they concentrate on most of the Metropolitan Region industrial-dedicated areas. From these 14 municipalities, only five cities, which have industrial complexes possessing continuous planned territories, were analysed: Alvorada, Cachoeirinha, Gravataí, Porto Alegre and Viamão.

6 Brandão (2007): centralized economic decisions during the Brazilian Military Government (1964–1985) established a clear pattern regarding urban development and industrial policies, where workforce expansion (rural–urban migrations) and total integration of national industrial production were targets. Even though the States were responsible for enacting these policies regionally, they were part of a national development plan. In this sense, municipalities had limited autonomy regarding their industrial district planning and implementation.

7 Porto Alegre’s Master Plan (2010a) classifies these areas as mixed-use zones, a more flexible zoning tool than the State Industrial Districts. Still, most of the residential incorporations (social housing), retail and service activities in the area are industrial-oriented.

8 Angular Analyses provide a better depiction of movement potentials and flow probabilities in orthogonal and regular grids, as it can identify slight changes in topology direction, interpreting them as weighted angular changes (Turner 2007). Orthogonal grids are the morphology typologies deemed to be prevalent in industrial zones.

9 The sphere of influence radius (Kernel Buffer Radius) for each structure is limited to 500 m, stipulated as a maximum acceptable distance that a vehicle must travel to access a public road from the industrial structure.

10 If the industrial site sphere of influence determined by KDE (500 m) is intersected by at least one segment within the established centrality value of threshold (top 20%), there will be a spatial correlation.

11 4 km is the most commonly stipulated influence distance for regional facilities and services, industrial complexes akin.

12 Described organization of metropolitan road-circulation networks possesses similitudes with Granovetter’s (1983) concepts of strong ties – that would be the interconnected road-circulation network inside settlements; and weak ties that would be characterized by the continuous highways that connect the different settlements in the metropolitan system.

13 Metropolitan settlement urbanization, mustered by residential incorporations especially in Cachoeirinha and Gravataí, has encompassed the areas where the Industrial Complexes were placed (Altafini 2018). Hence, the complexes are now more integrated to the regional road-circulation network than when they originally conceived during the mid-1970s.

14 Since the industrial complexes are small in comparison to the regional area, only when assessed in higher resolutions (local scale analysis), that KDE heatmaps become discernible.

15 These inner-complex road-circulation networks are clipped from the main regional network and remodelled using Space Syntax measures (NAIN and NACH) and represented here by the 20% of the road-elements with highest centrality values.

16 It is opportune to remark that the regional modelling for NACH (Figure 2 – B1 and B2) have a very high ‘visual similitude’ degree when compared to the sphere of influence restricted modelling for NACH (Figure 9 – A and B).

Additional information

Funding

This work was funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brazil (CAPES) – Finance Code 001 and by Università di Pisa (IT).