Ontology type: schema:Chapter
2015-01-28
AUTHORSS. Sridhar , Tara Thiagarajan , Sitabhra Sinha
ABSTRACTWhy do some places evolve into large sprawling metropolitan settlements over time, while other initially similar sites decay into obscurity? Identifying the factors underlying the phenomenon of urban growth has sparked the curiosity of scientists ever since Walter Christaller proposed the Central Place Theory in order to explain the observed number, sizes and locations of settlements in southern Germany. However, lack of availability of sufficient empirical data has hampered progress in developing a quantitative understanding of this process. In order to initiate a data-driven approach to answer questions on the growth of settlements, we have undertaken the analysis of a large database of economic, demographic and infrastructural factors associated with different sites of habitation in India. Here we present preliminary results of our analysis for a few of the most populous states of the Indian Union, viz., Maharasthra, Tamil Nadu and Uttar Pradesh. As rapid urbanization taking place in many parts of the country provides a window into the fast-changing rural-urban landscape, we have investigated the growth/decay of population centers in these states using information gleaned from government census reports. In particular, we show that combining demographic data with geographical information allows the identification of specific locations as being either growth “hot-spots” and decay “cold-spots”. In addition, we compare the process of growth in different states (which have distinct trajectories for the evolution of the total population size) across multiple scales of settlement sizes. We also show that, for all the states considered here, the nature of the population distribution at different scales (of settlement sizes) appear to change from a sharply bounded to a long-tailed one as one considers larger settlement size scales, implying that distinct population growth processes are at work in different scales. More... »
PAGES225-234
Econophysics and Data Driven Modelling of Market Dynamics
ISBN
978-3-319-08472-5
978-3-319-08473-2
http://scigraph.springernature.com/pub.10.1007/978-3-319-08473-2_10
DOIhttp://dx.doi.org/10.1007/978-3-319-08473-2_10
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