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It is well known that the urban systems, in particular cities, display scaling behaviour regarding socio-economic, infrastructural and individual basic services indicators. However, understanding urbanisation and the links between rural and urban areas is fundamental to making the most of the global transformations happening around the world. In this context, it is important to study the scaling laws based on both the urban and rural regions, going beyond cities. This paper explores the extension of the idea of allometric urban scaling law to study the scaling behaviour of Indian districts, with both the urban and rural population. To proceed, we have chosen districts (both rural and urban) of India, a relatively larger local administrative units, which are more or less independently functional within a country. This interdisciplinary work focus on the scaling analysis of various socio-economic indicators (SEIs) corresponding to the size (population) of four distinct urbanisation classes, namely rural, semi-rural, semi-urban and urban districts. The scaling exponents (β ) were estimated for each classes for the years 2001 and 2011 along with their goodness-of-fit measured by the R 2 values. Our rigorous statistical analysis indicates that the scaling laws indeed exist even at the district level for most of the SEIs considered, related to education, employment, housing, health, etc.; the R 2 values obtained for these SEIs are very high (often greater than 0.8 or 0.9) in both the years. Moreover, linearity of the scaling factors have been statistically tested and it has been found, at 95% level of confidence, that not all the SEIs behave linearly ( β = 1 ); some of them are characterised by super-linear ( β > 1 ) behaviour and some behave sub-linearly ( β < 1 ). Statistical hypothesis tests have also been performed to test the equality of two scaling factors corresponding to two distinct classes and two different years to understand the differences in scaling relationships amongst increasing urbanisation classes and their changes over time. [ABSTRACT FROM AUTHOR]

Impacts of global warming and local scale urbanization on precipitation are evident from observations; hence both must be considered in future projections of urban precipitation. Dynamic regional models at a fine spatial resolution can capture the signature of urbanization on precipitation, however simulations for multiple decades are computationally expensive. In contrast, statistical regional models are computationally inexpensive but incapable of assessing the impacts of urbanization due to the stationary relationship between predictors and predictand. This paper aims to develop a unique modelling framework with a demonstration for Mumbai, India, where future urbanization is projected using a Markov Chain Cellular Automata approach, long term projections with climate change impacts are performed using statistical downscaling and urban impacts are simulated with a dynamic regional model for limited number of years covering different precipitation characteristics. The evaluation of the statistical downscaling methodology over historical time period reveals large underestimation of the extreme rainfall, which is improved effectively by applying another regression model, for extreme days. The limited runs of dynamic downscaling models with different stages of urbanization for Mumbai, India, reveal spatially non uniform changes in precipitation, occurring primarily at the higher quantiles. The statistical and dynamical outputs are further integrated using quantile transformation for precipitation projection in Mumbai during 2050s. The projections show dominant impacts of urbanization compared to those from large scale changing patterns. The uniqueness of this computationally efficient framework lies in an integration of global and local factors for precipitation projections through a conjugal statistical–dynamical approach. [ABSTRACT FROM AUTHOR]

As cities throughout the developing world grow, they often expand more quickly than the infrastructure and service delivery networks that provide residents with basic necessities such as water and public safety. Why do some cities deliver more effective infrastructure and services in the face of rapid growth than others? Why do some households and communities secure better services than others? Answering these questions requires studying the large, politicized bureaucracies charged with providing urban services, especially the relationships between frontline workers, agency managers, and citizens in informal settlements. Researchers investigating public service delivery in cities of the Global South, however, have faced acute data scarcity when addressing these themes. The recent emergence of crowd-sourced data offers researchers new means of addressing such questions. In this paper, we draw on our own research on the politics of urban water delivery in India to highlight new types of analysis that are possible using crowd-sourced data and propose solutions to common pitfalls associated with analyzing it. These insights should be of use for researchers working on a broad range of topics in comparative politics where crowd-sourced data could provide leverage, such as protest politics, conflict processes, public opinion, and law and order. [ABSTRACT FROM AUTHOR]

Urban transport has serious problems that are symptoms of the general process of rapid urbanization and environmental degradation. Policymakers in general and urban economists in particular have paid little attention to public transport system pricing leading to the absence of a financially viable, self-supporting urban transport system. In this paper, we report a partial equilibrium model developed by us, which captures transport tax reforms in the presence of certain transport externalities. Our theoretical model shows that the question of public transport subsidies to reduce congestion and provide quality transport services depends on three factors: (a) the extent to which such subsidies induce people to switch from private transport to public transport; (b) if the price elasticity of current users of public transport is higher, there may be a sharp rise in public transport ridership as a reaction to increased subsidies, which will have an undesirable effect; and (c) there is the danger that subsidies will cause a loss in productive efficiency. The numerical model of our paper for Delhi shows that the cross price elasticity of public transport demand with respect to the price of private transport is significant (0.63) in the off-peak period whereas the same in the peak period is somewhat low (0.16) and the combined effect of these elasticities will result in a considerable modal shift in favour of bus transport demand (19%) if the price of public transport were to be subsidized and private transport were to be priced optimally. Even without subsidy, the modal shift will be significant (18%), if the under-priced private transport modes are optimally priced keeping the current bus prices constant. This paper shows that there will be significant welfare gains in both these scenarios. [ABSTRACT FROM AUTHOR]

This paper examines trends in three reproductive healthcare indicators- namely, antenatal care, medical assistance at delivery, and contraceptive use among the urban poor and non-poor in India using data from the National Family Health Surveys, 1992-1993 and 2005-2006. The urban poor and non-poor are derived from composite wealth indices based on a set of economic proxies. Results indicate that the estimates of poor and non-poor are reliable. During the last 14 years, the service coverage in all three indicators has increased in the country, among both the urban poor and non-poor. However, the utilization of reproductive health services is concentrated among the urban non-poor cutting across the states, with the exception of Kerala. While the non-poor/poor gap in antenatal care and medical assistance at delivery remained large over the years, the gap in contraceptive use has narrowed down cutting across states. After adjusting for other confounders, household poverty was found to be a significant barrier in the utilization of reproductive healthcare services across the states. It has been observed that the utilization of reproductive healthcare services followed a continuum of rural total, urban poor, and urban non-poor. [ABSTRACT FROM AUTHOR]

This paper describes the process of urbanization and land use change in the urban ecosystems of the National Capital Region (NCR) of Delhi, India. Two types of land use change are considered--from natural to urban and from agricultural to urban. Both types are explained in terms of economic variables known to be drivers of change. A panel data method was used, and economic variables were combined with GIS-based information on land use change during 1986-2004 for 11 administrative units of the NCR. The results suggest that investment in the construction sector plays a major role in converting the land from natural to urban areas, while differences in land productivity seems to be the major driver for change from agricultural to urban uses. [ABSTRACT FROM AUTHOR]

Measures of the effects of population pressure on the landscape using traditional methods for classifying urban territory are inadequate. The crude scale at which population densities are calculated and dependence on country-specific administration divisions hinder their ability to address such questions as the environmental impacts of cities and suburbs and make cross-national comparisons particularly difficult. This paper examines comparative urbanization measures among three case studies: the Pearl River Delta in Guangdong Province of China, the Indian state of Kerala, and the southern part of Florida in the United States. It proposes a measure based on the distribution of local population densities, taking advantage of the detailed data on small area populations and land area available in modern censuses and model-derived population databases such as LandScan, and the increasing potential of spatial analysis using geographic information systems (GIS). Examined with a similar set of thresholds, the resulting density distributions offer the potential to show better the ecological effects of population than do traditional measures. [ABSTRACT FROM AUTHOR]