TY - JOUR
T1 - A model for simulating emergent patterns of cities and roads on real-world landscapes
AU - Aoki, Takaaki
AU - Fujiwara, Naoya
AU - Fricker, Mark
AU - Nakagaki, Toshiyuki
N1 - Funding Information:
We thank S. Murayama and M. Yamada for discussions. This work was supported by the Research Institute for Mathematical Sciences, a joint research centre at Kyoto University (TA); the joint research with CSIS, the University of Tokyo (No. 699) (TA); JSPS KAKENHI Grant Number 21H04357 (TA); the Human Frontier Science Program (RGP0053/2012, MDF); the Leverhulme Trust (RPG-2015-437, MDF); JSPS Fellowship to MDF; “Dynamic Alliance for Open Innovation Bridging Human, Environment and Materials” from the Ministry of Education, Culture, Sports, Science and Technology of Japan (TN); JST, PRESTO Grant Number JPMJPR21RA, Japan (NF); JSPS KAKENHI Grant Number JP18K11462 (NF).
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Emergence of cities and road networks have characterised human activity and movement over millennia. However, this anthropogenic infrastructure does not develop in isolation, but is deeply embedded in the natural landscape, which strongly influences the resultant spatial patterns. Nevertheless, the precise impact that landscape has on the location, size and connectivity of cities is a long-standing, unresolved problem. To address this issue, we incorporate high-resolution topographic maps into a Turing-like pattern forming system, in which local reinforcement rules result in co-evolving centres of population and transport networks. Using Italy as a case study, we show that the model constrained solely by topography results in an emergent spatial pattern that is consistent with Zipf’s Law and comparable to the census data. Thus, we infer the natural landscape may play a dominant role in establishing the baseline macro-scale population pattern, that is then modified by higher-level historical, socio-economic or cultural factors.
AB - Emergence of cities and road networks have characterised human activity and movement over millennia. However, this anthropogenic infrastructure does not develop in isolation, but is deeply embedded in the natural landscape, which strongly influences the resultant spatial patterns. Nevertheless, the precise impact that landscape has on the location, size and connectivity of cities is a long-standing, unresolved problem. To address this issue, we incorporate high-resolution topographic maps into a Turing-like pattern forming system, in which local reinforcement rules result in co-evolving centres of population and transport networks. Using Italy as a case study, we show that the model constrained solely by topography results in an emergent spatial pattern that is consistent with Zipf’s Law and comparable to the census data. Thus, we infer the natural landscape may play a dominant role in establishing the baseline macro-scale population pattern, that is then modified by higher-level historical, socio-economic or cultural factors.
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U2 - 10.1038/s41598-022-13758-1
DO - 10.1038/s41598-022-13758-1
M3 - Article
C2 - 35710781
AN - SCOPUS:85132282238
SN - 2045-2322
VL - 12
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 10093
ER -