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GIS Visualization of Climate Change and Prediction of Human Responses

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Computational Intelligence Techniques in Earth and Environmental Sciences

Abstract

Estimation of heat stress based on WBGT (wet bulb globe temperature) index is widely accepted as international standard. The purpose of the present study was to provide tolerance limit for people and interventions required to protect individuals from the dangerous consequences of heat. The meteorological data collected from Indian Meteorological Department of Ahmedabad (2001–2011) was used for estimating the WBGT. Multiple regression analysis was used to explore relationship between variables dry bulb temperature (T a), wet bulb temperature (T wb), and globe temperature (T g) across the districts varied widely in two different seasons, i.e., summer and winter months. The linear regression analysis was applied for the purpose of future prediction, with respect to the WBGT index, and heat tolerance limit and visualized using GIS tool. The average tolerance time for 2001–2011 arrived at 82 ± 16 and 159 ± 36 min for the months of summer and winter, respectively. Thus, the WBGT and tolerance limit maps might prevail working population from heat stress fury.

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Authors and Affiliations

  1. National Institute of Occupational Health, Ahmedabad, 380 016, India

    P. K. Nag, Varsha Chorsiya & Anjali Nag

  2. Indian Institute of Public Health Gandhinagar, Public Health Foundation of India, Sardar Patel Institute Campus, Drive In Road, Thaltej, Ahmedabad, 380 054, India

    Priya Dutta

Authors
  1. P. K. Nag
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  2. Priya Dutta
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  3. Varsha Chorsiya
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  4. Anjali Nag
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Corresponding author

Correspondence to Priya Dutta .

Editor information

Editors and Affiliations

  1. Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA, NOAA/NESDIS Center for Satellite Applications and Research, College Park, MD, USA, Fort Collins, CO, USA

    Tanvir Islam

  2. NASA Goddard Space Flight Center, Greenbelt & ESSIC, University of Maryland College Park, MD, USA, Greenbelt, Maryland, USA

    Prashant K. Srivastava

  3. Department of Civil Engineering, IIT Delhi, Delhi, India

    Manika Gupta

  4. School of Geog. and Env. Sciences, Monash University, Melbourne, Australia

    Xuan Zhu

  5. School of Environmental Sciences Remote Sensing, Jawaharlal Nehru University, New Delhi, India

    Saumitra Mukherjee

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Nag, P.K., Dutta, P., Chorsiya, V., Nag, A. (2014). GIS Visualization of Climate Change and Prediction of Human Responses. In: Islam, T., Srivastava, P., Gupta, M., Zhu, X., Mukherjee, S. (eds) Computational Intelligence Techniques in Earth and Environmental Sciences. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8642-3_5

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