Which methods and techniques are available to measure and diagnose the state of the city. There is rich variety available on the market: surveys and indexes, commercially non-profit driven, business, governmental or civil society oriented, policy or science-driven. The general impression of this variety is that the landscape of starting points is rich but at the same time segmented and fragmented. I had the feeling and wanting of going back to basics in natural ecosystems principles and build from there.
If the city is considered as an ecosystem, what methodes can we use for measuring the city? Those from the forest are the most advanced as developed by Oldeman (1990) for tropical rainforests. They are the most complex systems in the world. The methods from the forest, from the science of silvology, a tem professor Oldeman coined, are relatively unknown and hardly applied in the world of public governance and administration.
Assuming that the laws of nature rule everywhere – the opposite has not been scientifically proven – even in cities, it is therefore fair to consider that forest research methods and techniques could be interesting also for city diagnosis. In this article some measurement basics are explained and elaborated in examples.
If the organisations in the city are considered as the living components – compared with the organisms, in this case limited to the trees in a forest – we can count, weigh and measure their architecture and start the diagnosis of the state of the system. What comes forward from extensive and decennia long studies in forest ecosystems (Oldeman et al. (1990) is that “the basic criteria used in model building of all kinds seem to be only three.” The starting point in forest research is the measurement triangle. In essence, one can measure only three characteristics and continue with advanced (cross) ratios from there:
- Population: presence, numbers, quantity, population.
- Production: weight, dosage, biomass (literally) and importance, power and influence (figuratively).
- Architecture: structures, forms, shapes.
Eagle view by remote sensing and field view in forests have always been a good marriage, Combining both views have inspired many scientists for advanced accuracy and balanced diagnosis. The combination of top-down geographical and statistical measurement with more perceptional bottom-up findings from the street can be promising.
To explain the basic mapping, one topic – that of strategy and policy planning for regional economic development – has been selected, in relation to the four most involved organisations. The results come from personal insights. It is noted that the grids and transects need to be considered is an art impression and serve as an example for diagnosis.
- Population, 16*16 diagram in eagle view, representing actual involved number of organisations in regional economic development strategy. In this example 7 municipalities and 1 province are involved, 6 education institutes, 4 scientific departments of universities and 223 business related organisations. They were plotted geographically in this grid. The factual mapping of involved businesses in this yellow dominated grid makes the importance of a proper economic development strategy for the commercial sector in the region very clear.
- Production 8*8 diagram in eagle view, representing the actual mutual perceived influence on the strategy in regional economic development. The difference with the population diagram is that government relatively is of great importance, while most business are just following a view major leading companies. It was felt that the main city as well as the province had a relatively following role in the strategy, leading to holes in the overal plan (white fields). The influence of the university departments was only substantial for one science (here labor market) but relatively limited for other sciences as human resource management, technical innovation and public governance. The total of influence and involvement should be equally divided over 64 fields, for each type of organisation 16 fields. That was the starting point of this common strategy. The actual figure shows that only 57 fields were properly covered as a result of leaning back of some organisations in an uneven actual landscape of promised involvement and influence: goverment 23 fields, education 11 fields, science 9 fields and business 13 fields. The diagram was used to realign and reconfirm the cooperation. It lead to a more active role of science and education, a less dominating role of government and a stronger involvement of all companies in the region.
- Architecture, actual socionomic transects in street view in any dimension needed. Bases on interviews this is how the forest of the regions look like. The higher the tree, the more influence on and dominance in the strategy development. Interesting is to see that two main companies play a leading role, just one municipality and one education institute. It is noted that the province is somewhere active in the lower regions of the forest. It participates but is not leading. One major city in the region leaned back and played there role in the shadows of the forest. The geographical display makes it possible to mark the organisations by name. The transect makes very clear who is in the lead. Whether this is balanced and serves the strategy, is the question. This result contributed to an open discussion to improve the network.
Note: this experiment is focused to develop new methods of measurement, test them on quality and secureness and explore how results can contribute to a more focused governance and hereto related decisions. One relevant leading starting point here is that the components (organisations) are measured as how they actually feel and behave in a certain phase of strategy related to regional economic development. It s not how it should be, but how it is on a given moment. It is an instrument for socionomic diagnosis by counting, weighing and architectural measurement.
Oldeman, R.A.A. (1990), Forests: Elements of Silvology. Berlin Heidelberg: Springer-Verlag.
Oldeman, R., Schmidt, P. and Arnolds, E. (1990). Forest components. Wageningen: Wageningen Agricultural University Papers, ISSN0169-345X; 90-6, 111 pp. https://edepot.wur.nl/282842.