India’s sustained and rapid economic growth offers an opportunity to lift millions out of poverty. But this may come at a steep cost to its environment and natural resources. This insightful book analyses India’s growth from an economic perspective and assesses whether India can grow in a "green" and sustainable manner. Three key issues are addressed. The first is the physical and monetary costs and losses of environmental health and natural resources driven by economic growth. The authors undertake a monetary valuation and quantification of environmental damage, using techniques that have been developed to better understand and quantify preferences and values of individuals and communities in the context of environmental quality, conservation of natural resources, and environmental health risks. The second part estimates the value of ecosystem services from the major biomes in India using state-of-the art methods with a view to preserving them for the future. The third section provides a menu of policy instruments to explore trade-offs between economic growth and environmental sustainability using a Computable General Equilibrium approach with particular attention to air pollution. The conclusions focus on the way forward in terms of policies, measures and instruments as India has to balance the twin challenges of maintaining economic prosperity while managing its environmental resources.

The contributors looks at the transition and some of the factors underlying it, such as how Kerala differs from other Indian states, the role played by education, age at marriage and the use of contraception, and the impact of migration.

This book constitutes the refereed proceedings of the Third International Conference on Cognitive Computing and Information Processing, CCIP 2017, held in Bengaluru, India, in December 2017. The 43 revised full papers presented were carefully reviewed and selected from 130 submissions. The papers are organized in topical sections on cognitive computing in medical information processing; cognitive computing and its applications; cognitive computing in video analytics.