Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysis
India is home to 11 % of the global urban population and is ranks as the second-largest urban system in the world. This study introduces a Heat Health Risk Index (HHRI) rankings for 37 major Indian cities with more than one million residents, using geospatial and socio-ecological data to identify po...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-12-01
|
| Series: | World Development Sustainability |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772655X24000582 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846115641660014592 |
|---|---|
| author | Kaushik Mandvikar Nirmal Kumar Hitesh Supe Deepak Singh Ankita Gupta Pankaj Kumar Gowhar Meraj Inam Danish Khan Asma Kouser Santosh Kumar Pandey Ram Avtar |
| author_facet | Kaushik Mandvikar Nirmal Kumar Hitesh Supe Deepak Singh Ankita Gupta Pankaj Kumar Gowhar Meraj Inam Danish Khan Asma Kouser Santosh Kumar Pandey Ram Avtar |
| author_sort | Kaushik Mandvikar |
| collection | DOAJ |
| description | India is home to 11 % of the global urban population and is ranks as the second-largest urban system in the world. This study introduces a Heat Health Risk Index (HHRI) rankings for 37 major Indian cities with more than one million residents, using geospatial and socio-ecological data to identify potential heat health risk areas. In this study, the Otsu method was employed to determine the critical parameters in the heat health index, considering factors such as Land Surface Temperature (LST), solar radiation, population density, mean temperature, urban green cover, rainfall, specific humidity, and wind speed. All data values were standardized to a uniform scale (0–1) for comparability. The standardized values, integrated with the assigned weights, formed the HHRI. Results indicate that cities such as Chennai, Mumbai, Kolkata, and Ahmedabad, each with populations exceeding 10 million, are deemed less livable due to their high HHRI (>0.50). Both Chennai and Mumbai stand out with highest hazard index as 0.66, followed by Kolkata (0.62) and Ahmedabad (0.56). Cities that lack sufficient green spaces are often more vulnerable, display elevated risk levels, and have decreased adaptability. In contrast, cities such as Ludhiana, Theni, Amritsar, and Nabarangpur are perceived as the most livable, with a mean HHRI of 0.21, owing to their higher adaptive capacity and lower exposure. Overall, this study serves as a foundation for conceiving future perspective plans for existing urban and peri‑urban areas, compared to living standards within the realms of sustainability. |
| format | Article |
| id | doaj-art-fabc06e8d0f74954995e6d89bac7b06f |
| institution | Kabale University |
| issn | 2772-655X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | World Development Sustainability |
| spelling | doaj-art-fabc06e8d0f74954995e6d89bac7b06f2024-12-19T11:02:50ZengElsevierWorld Development Sustainability2772-655X2024-12-015100180Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysisKaushik Mandvikar0Nirmal Kumar1Hitesh Supe2Deepak Singh3Ankita Gupta4Pankaj Kumar5Gowhar Meraj6Inam Danish Khan7Asma Kouser8Santosh Kumar Pandey9Ram Avtar10Graduate School of Environmental Science, Hokkaido University, Sapporo, 060-0810, JapanFaculty of Environmental Earth Science, Hokkaido University, Sapporo 060-0810Graduate School of Environmental Science, Hokkaido University, Sapporo, 060-0810, JapanFaculty of Environmental Earth Science, Hokkaido University, Sapporo 060-0810Graduate School of Environmental Science, Hokkaido University, Sapporo, 060-0810, JapanInstitute for Global Environmental Strategies, Hayama 240-0115, JapanDepartment of Ecosystem Studies, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Tokyo 113-8654, JapanDepartment of Clinical Microbiology, Army Base Hospital, Delhi Cantonment, New Delhi 110010, IndiaCentre for Russian and Central Asian Studies (CRCAS), School of International Studies, Jawaharlal Nehru University, New Delhi 110067 IndiaGraduate School of Environmental Science, Hokkaido University, Sapporo, 060-0810, Japan; NTC International Co. Ltd. Koto-ku, Tokyo, 136-0071 JapanGraduate School of Environmental Science, Hokkaido University, Sapporo, 060-0810, Japan; Faculty of Environmental Earth Science, Hokkaido University, Sapporo 060-0810; Corresponding author.India is home to 11 % of the global urban population and is ranks as the second-largest urban system in the world. This study introduces a Heat Health Risk Index (HHRI) rankings for 37 major Indian cities with more than one million residents, using geospatial and socio-ecological data to identify potential heat health risk areas. In this study, the Otsu method was employed to determine the critical parameters in the heat health index, considering factors such as Land Surface Temperature (LST), solar radiation, population density, mean temperature, urban green cover, rainfall, specific humidity, and wind speed. All data values were standardized to a uniform scale (0–1) for comparability. The standardized values, integrated with the assigned weights, formed the HHRI. Results indicate that cities such as Chennai, Mumbai, Kolkata, and Ahmedabad, each with populations exceeding 10 million, are deemed less livable due to their high HHRI (>0.50). Both Chennai and Mumbai stand out with highest hazard index as 0.66, followed by Kolkata (0.62) and Ahmedabad (0.56). Cities that lack sufficient green spaces are often more vulnerable, display elevated risk levels, and have decreased adaptability. In contrast, cities such as Ludhiana, Theni, Amritsar, and Nabarangpur are perceived as the most livable, with a mean HHRI of 0.21, owing to their higher adaptive capacity and lower exposure. Overall, this study serves as a foundation for conceiving future perspective plans for existing urban and peri‑urban areas, compared to living standards within the realms of sustainability.http://www.sciencedirect.com/science/article/pii/S2772655X24000582Heat health risk index (HHRI)Geospatial dataLandsat |
| spellingShingle | Kaushik Mandvikar Nirmal Kumar Hitesh Supe Deepak Singh Ankita Gupta Pankaj Kumar Gowhar Meraj Inam Danish Khan Asma Kouser Santosh Kumar Pandey Ram Avtar Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysis World Development Sustainability Heat health risk index (HHRI) Geospatial data Landsat |
| title | Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysis |
| title_full | Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysis |
| title_fullStr | Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysis |
| title_full_unstemmed | Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysis |
| title_short | Evaluating heat health risk in Indian cities: Geospatial and socio-ecological analysis |
| title_sort | evaluating heat health risk in indian cities geospatial and socio ecological analysis |
| topic | Heat health risk index (HHRI) Geospatial data Landsat |
| url | http://www.sciencedirect.com/science/article/pii/S2772655X24000582 |
| work_keys_str_mv | AT kaushikmandvikar evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT nirmalkumar evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT hiteshsupe evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT deepaksingh evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT ankitagupta evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT pankajkumar evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT gowharmeraj evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT inamdanishkhan evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT asmakouser evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT santoshkumarpandey evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis AT ramavtar evaluatingheathealthriskinindiancitiesgeospatialandsocioecologicalanalysis |