Chapter Capturing urban scaling laws via spatio-temporal correlated clusters 1
dc.contributor.author | Carbone, Anna | |
dc.contributor.author | Luiz da Silva, Sergio | |
dc.contributor.author | Kaniadakis, Giorgio | |
dc.date.accessioned | 2024-10-25T17:33:12Z | |
dc.date.available | 2024-10-25T17:33:12Z | |
dc.date.issued | 2024 | |
dc.identifier | ONIX_20241025_9781003288312_14 | |
dc.identifier.uri | https://library.oapen.org/handle/20.500.12657/94055 | |
dc.description.abstract | Urban allometry empirically describes how “things”, for example crime, GDP, emissions, energy use, area, street length, housing prices, etc. change in cities when their size, in terms of population, increases. Urban scaling is a relatively recent area of urban science, investigating how measurable characteristics of cities vary with their sizes. This book addresses this relatively novel but highly debated topic within urban studies and geography. It presents many results, techniques, methods, and reflections on urban scaling and allometry. The sections are organized into different sub- areas such as socio- economic, infrastructural or environmental outputs, so that there is a broad organization of the findings into recognizable sub- domains. The book is particularly timely as it is becoming increasingly urgent and necessary to understand the pro and cons of different city sizes and therefore to plan policies accordingly. The book is especially interesting from a theoretical perspective because it presents the latest developments and achievements in the field, which will help to highlight potential universal rules across cities and regions. This book will benefit researchers in urban science, and scholars entering the field from various disciplines, such as geography, sociology, economics, mathematics, physics, or urban and regional planning. It will also find an audience among practitioners and policymakers. Chapters 2, 13 and 31 of this book are freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license. | |
dc.language | English | |
dc.relation.ispartofseries | Routledge Advances in Regional Economics, Science and Policy | |
dc.subject.classification | thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management | |
dc.subject.classification | thema EDItEUR::K Economics, Finance, Business and Management::KC Economics::KCV Economics of specific sectors::KCVS Regional / urban economics | |
dc.subject.classification | thema EDItEUR::K Economics, Finance, Business and Management::KC Economics | |
dc.subject.other | Urban Scaling | |
dc.subject.other | Urban Science | |
dc.subject.other | Allometry | |
dc.subject.other | Urban Size | |
dc.subject.other | Power Law | |
dc.subject.other | Agglomeration Economies | |
dc.title | Chapter Capturing urban scaling laws via spatio-temporal correlated clusters 1 | |
dc.type | chapter | |
oapen.identifier.doi | 10.4324/9781003288312-35 | |
oapen.relation.isPublishedBy | 7b3c7b10-5b1e-40b3-860e-c6dd5197f0bb | |
oapen.relation.isPartOfBook | dafa8754-a4d7-40b9-9af4-beedf300d281 | * |
oapen.relation.isbn | 9781003288312 | |
oapen.relation.isbn | 9781032264400 | |
oapen.relation.isbn | 9781032264417 | |
oapen.imprint | Routledge | |
oapen.pages | 310 - 323 | |
oapen.place.publication | London |