Cited by 74Fire effects on ecosystemsFire Detection and Safety SystemsAtmospheric aerosols and clouds

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Investigation of Forest Fire Activity Changes Over the Central India Domain Using Satellite Observations During 2001–2020

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Abstract

Recurrent and large forest fires negatively impact ecosystem, air quality, and human health. Moderate Resolution Imaging Spectroradiometer fire product is used to identify forest fires over central India domain, an extremely fire prone region. The study finds that from 2001 to 2020, ∼70% of yearly forest fires over the region occurred during March (1,857.5 counts/month) and April (922.8 counts/month). Some years such as 2009, 2012, and 2017 show anomalously high forest fires. The role of persistent warmer temperatures and multiple climate extremes in increasing forest fire activity over central India is comprehensively investigated. Warmer period from 2006 to 2020 showed doubling and tripling of forest fire activity during forest fire (February–June; FMAMJ) and non‐fire (July–January; JASONDJ) seasons, respectively. From 2015 JASONDJ to 2018 FMAMJ, central India experienced a severe heatwave, a rare drought and an extremely strong El Niño, the combined effect of which is linked to increased forest fires. Further, the study assesses quinquennial spatiotemporal changes in forest fire characteristics such as fire count density and average fire intensity. Deciduous forests of Jagdalpur‐Gadchiroli Range and Indravati National Park in Chhattisgarh state are particularly fire prone (>61 fire counts/grid) during FMAMJ and many forest fires are of high intensity (>45 MW). Statistical associations link high near surface air temperature and low precipitation during FMAMJ to significantly high soil temperature, low soil moisture content, low evapotranspiration and low normalized difference vegetation index. This creates a significantly drier environment, conducive for high forest fire activity in the region.

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Figure 1 (a) Geographical location of central India domain (shaded in gray) within the Indian boundary and (b) an enlarged view of the study area showing Chhattisgarh, Maharashtra, and Telangana states.
Figure 1 (a) Geographical location of central India domain (shaded in gray) within the Indian boundary and (b) an enlarged view of the study area showing Chhattisgarh, Maharashtra, and Telangana states.CC BY-NC-ND · PubMed Central
Figure 2 ISRO forest fraction cover (%) data set at 5 km spatial resolution (Reddy et al., 2016) extracted over central India domain (latitude: 17.5°–21.5°N and longitude: 78.5°−82.5°E).
Figure 2 ISRO forest fraction cover (%) data set at 5 km spatial resolution (Reddy et al., 2016) extracted over central India domain (latitude: 17.5°–21.5°N and longitude: 78.5°−82.5°E).CC BY-NC-ND · PubMed Central
Figure 3 Flowchart showing methodology scheme adopted for the study. Confidence level of MODIS fire pixels is denoted by C in the flowchart.
Figure 3 Flowchart showing methodology scheme adopted for the study. Confidence level of MODIS fire pixels is denoted by C in the flowchart.CC BY-NC-ND · PubMed Central
Figure 4 (a) Forest fire counts and (b) fire counts anomaly observed during forest fire season (FMAMJ) and non‐fire season (JASONDJ) from 2001 to 2020.
Figure 4 (a) Forest fire counts and (b) fire counts anomaly observed during forest fire season (FMAMJ) and non‐fire season (JASONDJ) from 2001 to 2020.CC BY-NC-ND · PubMed Central
Figure 5 Spatiotemporal patterns of forest fire counts during forest fire season (FMAMJ) in central India domain in (a) 2001–2005, (b) 2006–2010, (c) 2011–2015, and (d) 2016–2020. Regions of high fire activity are highlighted in dark red boxes in the figure. Box 1 – Jagdalpur‐Gadchiroli Range, Mikabeli Range, and Indravati National Park in Chhattisgarh, Box 2 – Sundernagar Range in Maharashtra, Box 3 – Tadoba Andhari Tiger Reserve in Maharashtra, Box 4 – Medaram‐Thadvai Forest Range in Telangana, Box 5 – Forest patches at Odisha‐Telangana state border, and Box 6 – Alluri Sitarama Raju Forest area at the Odisha‐Andhra Pradesh state border.
Figure 5 Spatiotemporal patterns of forest fire counts during forest fire season (FMAMJ) in central India domain in (a) 2001–2005, (b) 2006–2010, (c) 2011–2015, and (d) 2016–2020. Regions of high fire activity are highlighted in dark red boxes in the figure. Box 1 – Jagdalpur‐Gadchiroli Range, Mikabeli Range, and Indravati National Park in Chhattisgarh, Box 2 – Sundernagar Range in Maharashtra, Box 3 – Tadoba Andhari Tiger Reserve in Maharashtra, Box 4 – Medaram‐Thadvai Forest Range in Telangana, Box 5 – Forest patches at Odisha‐Telangana state border, and Box 6 – Alluri Sitarama Raju Forest area at the Odisha‐Andhra Pradesh state border.CC BY-NC-ND · PubMed Central
Figure 6 Spatiotemporal patterns of average fire radiative power (in MW) during forest fire season (FMAMJ) in central India domain in (a) 2001–2005, (b) 2006–2010, (c) 2011–2015, and (d) 2016–2020.
Figure 6 Spatiotemporal patterns of average fire radiative power (in MW) during forest fire season (FMAMJ) in central India domain in (a) 2001–2005, (b) 2006–2010, (c) 2011–2015, and (d) 2016–2020.CC BY-NC-ND · PubMed Central

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Show all 2 references

Research works printed but not linked: 74

  1. 10.1007/s00704-010-0396-2 · DOI
  2. 10.1007/s41324-018-0175-1 · DOI
  3. Andreae M. O., 1991, Global biomass burning‐atmospheric, climatic, and biospheric implications, 3, 10.7551/mitpress/3286.003.0003 · DOI
  4. 10.1007/978-1-4615-2524-0_6 · DOI
  5. 10.5721/EuJRS20164921 · DOI
  6. 10.1080/02827581.2021.1918239 · DOI
  7. 10.1016/j.jastp.2017.03.017 · DOI
  8. 10.1029/2003JD003697 · DOI · Paper page
  9. 10.1016/j.tree.2005.04.025 · DOI · Paper page
  10. 10.1111/geb.13058 · DOI
  11. 10.3329/jesnr.v5i2.14840 · DOI
  12. 10.1007/3-540-27468-5_86 · DOI
  13. 10.1038/s41558-017-0014-8 · DOI
  14. 10.1007/978-3-540-77381-8_1 · DOI
  15. 10.1126/science.250.4988.1669 · DOI
  16. 10.1029/2004JD004924 · DOI
  17. FAO., 2007, Fire management global assessment 2006, i
  18. 10.1007/s10584-005-5935-y · DOI
  19. 10.1016/S0048-9697(00)00524-6 · DOI
  20. 10.1007/s10584-015-1521-0 · DOI · Paper page
  21. Forest Survey of India (FSI), 2019, India State of Forest Report 2019, i
  22. Forest Survey of India (FSI), 2020, FSI Technical Information Series, 1
  23. 10.1038/s41598-017-07956-5 · DOI
  24. 10.1016/j.rse.2008.10.006 · DOI
  25. Giglio L., 2018, MODIS collection 6 active fire product user’s guide revision B
  26. 10.1016/j.rse.2016.02.054 · DOI
  27. 10.4209/aaqr.200460 · DOI
  28. 10.1023/A:1005371923658 · DOI
  29. 10.1007/s12040-020-1381-5 · DOI
  30. 10.1289/ehp.1002288 · DOI
  31. 10.3390/f11030286 · DOI
  32. India Meteorological Department (IMD), 2021, Statement on climate of India during 2020, 1
  33. Intergovernmental Panel on Climate Change (IPCC), 2018, Global Warming of 1.5°C, An IPCC Special Report on the impacts of global warming of 1.5°C above pre‐industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty
  34. Jain M., 2021, Extremes in atmospheric processes and phenomenas: Assessment, impacts and mitigation
  35. 10.1088/1748-9326/aa9853 · DOI
  36. 10.1007/s40010-017-0452-8 · DOI
  37. 10.1126/science.1131152 · DOI
  38. 10.1016/j.wace.2013.07.006 · DOI
  39. Kumar M., 2013, Effect of fire on soil nutrients and under storey vegetation in Chir pine forest in Garhwal Himalaya, India, ActaEcologicaSinica, 33, 59
  40. 10.1007/s42452-021-04391-0 · DOI
  41. 10.1029/2005GL022860 · DOI
  42. 10.5194/acp-20-8827-2020 · DOI
  43. 10.1111/gcb.13275 · DOI · Paper page
  44. 10.1177/0309133307079365 · DOI · Paper page
  45. 10.1002/asl.959 · DOI
  46. 10.1016/j.foreco.2013.12.003 · DOI
  47. 10.1007/s12040-009-0040-7 · DOI
  48. 10.1007/s00703-016-0469-6 · DOI
  49. 10.1016/j.worlddev.2020.105120 · DOI
  50. 10.1016/j.jenvman.2006.11.017 · DOI
  51. 10.1007/s11676-011-0206-4 · DOI
  52. 10.1007/s10531-015-1033-2 · DOI
  53. 10.1007/s10661-015-4990-8 · DOI
  54. 10.18520/cs/v112/i07/1521-1532 · DOI
  55. 10.5194/acp-5-799-2005 · DOI
  56. 10.1016/j.rse.2005.04.007 · DOI
  57. 10.1016/j.ejrh.2020.100727 · DOI
  58. 10.1029/2018JD028428 · DOI
  59. Satendra, 2014, Forest fire disaster management, i
  60. Saxena P., 2019, Criteria air pollutants and their impact on environmental health, 157, 10.1007/978-981-13-9992-3 · DOI
  61. 10.1016/j.heliyon.2021.e06973 · DOI
  62. 10.1016/j.foreco.2019.117723 · DOI
  63. Sonwani S., 2016, Proceedings of Indian aerosol science and technology association conference on aerosol and climate change: Insight and challenges. IASTA Bulletin, 269
  64. 10.1007/s10874-019-09396-z · DOI
  65. Sonwani S., 2021, Water‐insoluble carbonaceous components in rainwater over an urban background location in Northern India during pre‐monsoon and monsoon seasons, Environmental Science and Pollution Research, 1
  66. 10.1029/2008JD010717 · DOI
  67. 10.5194/acp-13-5227-2013 · DOI
  68. 10.1146/annurev.es.20.110189.001131 · DOI
  69. 10.1007/s10661-005-9122-4 · DOI
  70. 10.1175/BAMS-D-16-0145.1 · DOI · Paper page
  71. 10.1038/s41598-019-55036-7 · DOI
  72. 10.1071/WF09002 · DOI · Paper page
  73. 10.5194/acp-21-3833-2021 · DOI
  74. 10.5194/bg-16-1629-2019 · DOI

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Metadata

Authors
Jain, M., Saxena, P., Sharma, S., & Sonwani, S.
Affiliations
  • Jawaharlal Nehru University (IN)
  • University of Delhi (IN)
  • Physical Research Laboratory (IN)
Corresponding author
Sonwani, Saurabh
Venue
GeoHealth
Published
2021-12
Volume
5
Issue
12
Pages
e2021GH000528-e2021GH000528
ISSN
2471-1403 (ISSN-L)
OpenAlex
W4200432480
Cited by
74
References
2
Citations by year
2026: 6 · 2025: 23 · 2024: 20 · 2023: 12 · 2022: 12 · 2021: 1
FWCI
4.61
Type
journal article
Language
en
Open access
Locations
  • GeoHealth (publishedVersion, cc-by-nc-nd)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Fire Detection and Safety Systems
  • Physical Sciences › Environmental Science › Global and Planetary Change › Atmospheric aerosols and clouds
Keywords
Central India, fire seasonality, fire intensity, heat waves, El Niño, drought, climate extremes, soil moisture, evapotranspiration, NDVI, Chhattisgarh, fire-prone forests, satellite fire detection

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