Enhancement of Fire Early Warning System in Vietnam Using Spatial Data and Assimilation

  • Ba Tung Nguyen
  • Khac Phong Do
  • Nguyen Le Tran
  • Quang Hung Bui
  • Thi Nhat Thanh Nguyen
  • Van Quynh Vuong
  • Thanh Ha Le
Part of the Springer Remote Sensing/Photogrammetry book series (SPRINGERREMO)


Accurate and timely information on vegetation fires is crucial for mitigation and rehabilitation measures. With the advent of spatial technologies, fire risk can be mapped at varied spatial scales integrating multiple datasets. In Vietnam, forest protection department (FPD) leads the forest and fire management activities. FPD routinely generates fire early warning maps at a district level that depict fire risk varying from level I to level V with increasing severity. The FPD fire risk maps are based on an algorithm that only uses ground-based meteorological inputs. In this study, we improve the fire risk assessment through assimilating meteorological as well as satellite data and map the fire risk at 0.1 × 0.1° grid cells. We use MODIS active fires to test the relative accuracy of FPD-generated fire risk map and our approach. Results suggest a significant enhancement in fire risk using our approach. Our results outperformed the FPD results in terms of both spatial details and fire risk information, i.e., we found a much higher fire density at level IV and level V at 0.1 × 0.1° grid scale than the FPD district-level maps. Our results highlight the potential of data assimilation for an improved fire early warning in Vietnam.


Fire early warning system Meteorological variables Kriging interpolation Data assimilation 



The authors would like to thank Vietnam National University, Hanoi for financial support.


  1. Ager AA, Nicole MV, Finney MA (2011) Integrating fire behavior models and geospatial analysis for wildland fire risk assessment and fuel management planning. J Combust.
  2. Andreae MO, Merlet P (2001) Emission of trace gases and aerosols from biomass burning. Global Biogeochem Cycles 15(4):955–966CrossRefGoogle Scholar
  3. Badarinath KVS, Kharol SK, Madhavi Latha K, Chand TR, Prasad VK, Nirmala J. A, Samatha K (2007) Multiyear ground-based and satellite observations of aerosol properties over a tropical urban area in India. Atmos Sci Lett 8(1):7–13CrossRefGoogle Scholar
  4. Badarinath KVS, Kharol SK, Prasad VK, Sharma AR, Reddi EUB, Kambezidis HD, Kaskaoutis DG (2008) Influence of natural and anthropogenic activities on UV Index variations–a study over tropical urban region using ground based observations and satellite data. J Atmos Chem 59(3):219–236CrossRefGoogle Scholar
  5. Badarinath KVS, Sharma AR, Kharol SK, Prasad VK (2009) Variations in CO, O3 and black carbon aerosol mass concentrations associated with planetary boundary layer (PBL) over tropical urban environment in India. J Atmos Chem 62(1):73–76CrossRefGoogle Scholar
  6. Borbas EE, Seemann SW, Kern ANIKO, Moy LESLIE, Li J, Gumley LIAM, Menzel WP (2011) MODIS atmospheric profile retrieval algorithm theoretical basis document [Electronic resource]. http://modis-atmos. gsfc. nasa. gov/MOD07_L2/atbd. html. 10 Aug 2015Google Scholar
  7. Brauer M, Hisham-Hashim J (1998) Peer reviewed: fires in Indonesia: crisis and reaction. Environ Science & Technology 32(17):404A-407AGoogle Scholar
  8. Camia A, Amatulli G, Barbosa P, San-Miguel-Ayanz J (2007) Fire danger forecast in the European Forest Fire Information System (EFFIS). In: Proceedings of the fourth International Wildland Fire Conference, Wildfire2007, Seville, Spain 13–17 May.Google Scholar
  9. Camia A, Amatulli G (2009) Weather factors and fire danger in the Mediterranean. In: Chuvieco E (ed) Earth observation of wildland fires in Mediterranean ecosystems. Springer, Berlin, pp 71–82. JRC55075CrossRefGoogle Scholar
  10. Carrega P (1991) A meteorological index of forest fire hazard in Mediterranean France. Int J Wildland Fire 1(2): 79-86Google Scholar
  11. Chandler CC (1961) Risk rating for fire prevention planning. J Forestry 59.2:93–96Google Scholar
  12. Chuvieco E (ed) (2003) Wildland fire danger estimation and mapping. The role of remote sensing data. World Scientific Publishing, SingaporeGoogle Scholar
  13. DeBano LF, Neary DG, Ffolliott PF (1998) Fire’s effects on ecosystems. Wiley, New YorkGoogle Scholar
  14. Food and Agriculture Organization (FAO) (1986) Wildland fire management terminology. FAO Forestry Paper 70, Food and Agriculture Organization of the United Nations, 257 ppGoogle Scholar
  15. FPD (2007a) The materials about Forest Fire Protection Training Forest Protection Department, Ministry of Agriculture and Rural DevelopmentGoogle Scholar
  16. FPD (2007b) Forest Fire Risk Information System - Forest Protection Department, Ministry of Agriculture and Rural Development
  17. Gaveau DLA, Mohammad AS, Kristell H, Bruno L, Sean S, Wooster M et al (2014) Major atmospheric emissions from peat fires in Southeast Asia during non-drought years: evidence from the 2013 Sumatran fires. Sci Rep 4.
  18. Giglio L, Descloitres J, Justice CO, Kaufman Y (2003) An enhanced contextual fire detection algorithm for MODIS. Remote Sens Environ 87:273–282CrossRefGoogle Scholar
  19. Goldammer JG, Jenkins MJ (eds) (1990) Fire in ecosystem dynamics. Mediterranean and northern perspectives. SPB Academic Publishing, The Hague. 199 pGoogle Scholar
  20. de Groot WJ, Field RD, Brady MA, Roswintiarti O, Mohamad M (2007) Development of the Indonesian and Malaysian fire danger rating systems. Mitig Adapt Strat Glob Chang 12(1):165–180CrossRefGoogle Scholar
  21. Gupta PK, Prasad VK, Sharma C, Sarkar AK, Kant Y, Badarinath KVS, Mitra AP (2001) CH4 emissions from biomass burning of shifting cultivation areas of tropical deciduous forests–experimental results from ground-based measurements. Chemosphere Global Change Sci 3(2):133–143CrossRefGoogle Scholar
  22. Ha CT (2013) Vietnam National Forest Status of 2012. Annual report of Ministry of Agriculture and Rural DevelopmentGoogle Scholar
  23. Hanewinkel M, Hummel S, Albrecht A (2011) Assessing natural hazards in forestry for risk management: a review. Eur J For Res 130(3):329–351CrossRefGoogle Scholar
  24. Hayasaka H, Noguchi I, Putra EI, Yulianti N, Vadrevu K (2014) Peat-fire-related air pollution in Central Kalimantan, Indonesia. Environ Pollut 195:257–266CrossRefGoogle Scholar
  25. Huang K, Fu JS, Hsu NC, Gao Y, Dong X, Tsay SC, Lam YF (2013) Impact assessment of biomass burning on air quality in Southeast and East Asia during BASE-ASIA. Atmos Environ 78:291–302CrossRefGoogle Scholar
  26. Huffman GJ, Bolvin DT, Nelkin EJ, Wolff DB, Adler RF, Gu G, Hong Y, Bowman KP, Stocker EF (2007) The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. J Hydrometeorol 8:38–55CrossRefGoogle Scholar
  27. Kant Y, Ghosh AB, Sharma MC, Gupta PK, Prasad VK, Badarinath KVS, Mitra AP (2000) Studies on aerosol optical depth in biomass burning areas using satellite and ground-based observations. Infrared Phys Technol 41(1):21–28CrossRefGoogle Scholar
  28. Kharol SK, Badarinath KVS, Sharma AR, Mahalakshmi DV, Singh D, Prasad VK (2012) Black carbon aerosol variations over Patiala city, Punjab, India—a study during agriculture crop residue burning period using ground measurements and satellite data. J Atmos Sol Terr Phys 84:45–51CrossRefGoogle Scholar
  29. Le TH, Nguyen TNT, Lasko K, Ilavajhala S, Vadrevu KP, Justice C (2014) Vegetation fires and air pollution in Vietnam. Environ Pollut 195:267–275CrossRefGoogle Scholar
  30. MARD (2003) Land use classification, planning and allocation of forest land. In: Vietnam forestry sector manual, HanoiGoogle Scholar
  31. Munger TT (1916) Graphic method of representing and comparing drought intensities. Mon Weather Rev 44:642–643CrossRefGoogle Scholar
  32. Nesterov V (1949) Forest fires and methods of fire risk determination. Russian Goslesbumizdat MoscowGoogle Scholar
  33. Nguyen TT, Bui HQ, Pham HV, Luu HV, Man CD, Pham HN, Le HT, Nguyen TT (2015) Particulate matter concentration mapping from MODIS satellite data: a Vietnamese case study. Environmental Research Letters 10(9):p.095016Google Scholar
  34. Pham TT, Moeliono M, Nguyen TH, Nguyen HT, Vu TH (2012) The context of REDD+ in Vietnam: drivers, agents and institutions Center for International Forestry Research (CIFOR), Bogor, IndonesiaGoogle Scholar
  35. Prasad VK, Kant Y, Gupta PK, Elvidge C, Badarinath KVS (2002) Biomass burning and related trace gas emissions from tropical dry deciduous forests of India: a study using DMSP-OLS data and ground-based measurements. Int J Remote Sens 23(14):2837–2851CrossRefGoogle Scholar
  36. Prasad VK, Badarinath KVS, Eaturu A (2008a) Biophysical and anthropogenic controls of forest fires in the Deccan Plateau, India. J Environ Manage 86(1):1–13CrossRefGoogle Scholar
  37. Prasad VK, Badarinath KVS, Eaturu A (2008b) Effects of precipitation, temperature and topographic parameters on evergreen vegetation greenery in the Western Ghats, India. Int J Climatol 28(13):1807–1819CrossRefGoogle Scholar
  38. Pyne SJ, Andrews PL, Laven RD (1996) Introduction to wildland fire. John Wiley and Sons Inc., New York. 769 pGoogle Scholar
  39. Rodell M, Houser PR, Jambor U, Gottschalck J, Mitchell K, Meng C-J, Arsenault K, Cosgrove B, Radakovich J, Bosilovich M, Entin JK, Walker JP, Lohmann D, Toll D (2004) The Global Land Data Assimilation System. Bull Am Meteorol Soc 85:381–394CrossRefGoogle Scholar
  40. San-Miguel-Ayanz J, Barbosa P, Liberta G, Schmuck G, Schulte E, Bucella P (2003) The European forest fire information system: a European strategy towards forest fire management. Proceedings of the 3rd international wildland fire conference, Sydney, Australia. US Department of Interior: Bur Land Management CD-ROMGoogle Scholar
  41. Sena ET, Artaxo P, Correia AL (2013) Spatial variability of the direct radiative forcing of biomass burning aerosols and the effects of land use change in Amazonia. Atmos Chem Phys 13(3):1261–1275CrossRefGoogle Scholar
  42. Seinfeld JH, Pandis SN (2016) Atmospheric chemistry and physics: from air pollution to climate change. John Wiley & SonsGoogle Scholar
  43. Thompson MP, Calkin DE, Finney MA, Gebert KM, Hand MS (2013) A risk-based approach to wildland fire budgetary planning. Forest Sci 59(1):63–77CrossRefGoogle Scholar
  44. Vadrevu KP, Justice CO (2011) Vegetation fires in the Asian region: satellite observational needs and priorities. Global Environ Res 15(1):65–76Google Scholar
  45. Vadrevu KP, Eaturu A, Badarinath KV (2006) Spatial distribution of forest fires and controlling factors in Andhra Pradesh, India using spot satellite datasets. Environmental Monitoring and Assessment 123(1):75-96Google Scholar
  46. Vadrevu KP, Anuradha E, Badarinath KVS (2010) Fire risk evaluation using multicriteria analysis—a case study. Environ Monit Assess 166(1–4):223–239CrossRefGoogle Scholar
  47. Vadrevu KP, Louis G, Justice C (2013) Satellite based analysis of fire–carbon monoxide relationships from forest and agricultural residue burning (2003–2011). Atmos Environ 64:179–191CrossRefGoogle Scholar
  48. Vadrevu KP, Lasko K, Giglio L, Justice C (2014) Analysis of Southeast Asian pollution episode during June 2013 using satellite remote sensing datasets. Environ Pollut 195:245–256CrossRefGoogle Scholar
  49. Vadrevu KP, Lasko KL, Giglio L, and Chris Justice (2015) Vegetation fires, absorbing aerosols and smoke plume characteristics in diverse biomass burning regions of Asia. Environ Res Lett 105003Google Scholar
  50. Van Wagner CE (1987) Development and structure of the Canadian forest fire weather index system. Canadian Forestry Service Forestry Technical ReportGoogle Scholar
  51. Viegas DX, Biovio G, Ferreira A, Nosenzo A, Sol B (1999) Comparative study of various methods of fire danger evaluation in southern Europe. Int J Wildland Fire 10:235–246CrossRefGoogle Scholar
  52. Wu T, Li Y (2013) Spatial interpolation of temperature in the United States using residual kriging. Appl Geogr 44:112–120CrossRefGoogle Scholar

Copyright information

© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2018

Authors and Affiliations

  • Ba Tung Nguyen
    • 1
  • Khac Phong Do
    • 1
  • Nguyen Le Tran
    • 1
  • Quang Hung Bui
    • 1
  • Thi Nhat Thanh Nguyen
    • 1
  • Van Quynh Vuong
    • 2
  • Thanh Ha Le
    • 1
  1. 1.University of Engineering and TechnologyVietnam National University, HanoiHanoiVietnam
  2. 2.Vietnam Forestry UniversityHanoiVietnam

Personalised recommendations