Evaluating the Environmental Sustainability of Smart Cities in India: The Design and Application of the Indian Smart City Environmental Sustainability Index

Abstract

There is a growing consensus that the initiatives taken under the Smart Cities Mission (SCM) in India should be used as an opportunity to prepare models for Environmentally Sustainable Smart Cities (ESSC). While developed countries have earlier worked towards Sustainable Cities and now are moving towards Smart Sustainable Cities, the conditions in developing countries are different. In their current form, SCM guidelines appear to emphasize more on social and economic development along with governance issues using modern tools of information and communication technology (ICT). To ensure environmental sustainability of such large-scale development planning, after a two-stage screening process, 24 environmental indicators have been finalized (including 11 from the existing guidelines), which can be used to monitor various environmentally sustainable elements of smart cities. Accordingly, in the present study; a tentative framework has been developed using these indicators to arrive at a Smart City Environmental Sustainability Index (SCESI) on a 0–100 increasing scale, and the city’s environmental sustainability has been classified under five categories: Excellent; Good; Fair; Poor or Critically Low; based on decreasing SCESI. Using this framework, five Indian cities, which are currently being developed under SCM (Delhi; Patna; Allahabad; Varanasi; and Bhubaneswar), have been examined. The analyses indicate that while three of them (Delhi, Allahabad, and Bhubaneswar) are found in the Fair (SCESI = 40–60) category of environmental sustainability, two (Varanasi and Patna) are in the Poor (SCESI = 20–40) category. The SCESI developed may be used as a monitoring and diagnostic tool for planning and managing services connected with the environment surrounding human life.

An overview of the consumer‐centric disruptive technology research: Insights from topic modelling and literature review

“…and promoting efficient resource allocation and energy management (Shruti et al, 2020). However, the successful adoption of innovative technologies depends on consumer trust (A 12 ) and acceptance (A 2 ) (Papoutsi & Sodhi, 2020).…”

“…Sustainability aims to balance economic growth (A 18 ), environmental protection (A 20 ), and social well‐being (A 7 )—all essential components of human progress—without jeopardising prospects (Govindan et al, 2021). Disruptive technologies like smart cities (A 5 , A 3 ) exemplify the essence of sustainability by reducing risks (A 17 ) and promoting efficient resource allocation and energy management (Shruti et al, 2020). However, the successful adoption of innovative technologies depends on consumer trust (A 12 ) and acceptance (A 2 ) (Papoutsi & Sodhi, 2020).…”

Co-Creating Smart Cities – Design Thinking for 21st Century Urban Planning

“…Said approach is often led by partnerships between public entities and large technology companies, and may substantially aid in the promotion of energy efficiency of social infrastructure. Sustainability constitutes a cornerstone of smart city development, with there being a growing academic consensus that it is crucial to reduce the consumption of nonrenewable energy sources, as well as safeguard natural heritages (Silva, Khan, and Han, 2018;Shruti, Singh, and Ohri, 2021). Silva, Khan, and Han (2018) outline an interdependence between sustainability and the other attributes of a smart city, visualized in Figure 1.…”

Developing a method for assessing environmental sustainability based on the Google Earth Engine platform

“…Similarly, Xu (2013a) developed the remote sensing ecological index (RSEI) using Landsat images to assess urban environmental sustainability in Fuzhou, China, from 2001 to 2009. More recently, Shruti (2021) developed the smart city environmental sustainability index based on 24 environmental indicators to assess environmental sustainability in the construction of new smart cities. Although remote sensing-based means provide effective methods for monitoring and assessing environmental sustainability, limitations such as large data volume, heavy preprocessing work, and low efficiency of exponential calculation still exist, making them difficult to implement at large spatial scales or over a long-term scale.…”