1887
PDF

Abstract

Summary

Catastrophic landscape fires of 2020 that in four episodes burnt at least 160 000 ha of forest and other lands in the Chornobyl Exclusion Zone, Zhytomyrska, Kharkivska and Luhanska oblasts required development and implementation of modern web-based platforms, that combine use of geoinformation technologies, remote sensing data and advanced fire science methods for better spatio-temporal assessment of fire risks in landscapes and modelling potential behavior of catastrophic fires. Common access to data on such platform of policy makers, agencies and fire managers as well as other stakeholders will contribute to better prevention and suppression of fires in regional and national scale. Main features and functions of geoportal “Landscape Fires of Ukraine” presented in the paper as well as some pilot cases that demonstrate capacity of this perspective tool that could be important step toward transition to integrated landscape fire management in Ukraine.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.20215521113
2021-05-11
2024-04-26
Loading full text...

Full text loading...

/deliver/fulltext/2214-4609/2021/gis2021/A_web-based_platform_LANDSCAPE_FIRES_regional-level_fire_management.html?itemId=/content/papers/10.3997/2214-4609.20215521113&mimeType=html&fmt=ahah

References

  1. Ager, A.A., Lasko, R., Myroniuk, V., Zibtsev, S., Day, M.A., Usenia, U., Bogomolov, V., Kovalets, I. and Evers, C.R.
    [2019] The wildfire problem in areas contaminated by the Chernobyl disaster. Science of the Total Environment, 696, 133954.
    [Google Scholar]
  2. Baig, M.H.A., Zhang, L.F., Shuai, T. and Tong, Q.X.
    [2014] Derivation of a tasselled cap transformation based on Landsat 8 at-satellite reflectance. Remote Sensing Letters, 5(5), 423–431.
    [Google Scholar]
  3. Breiman, L.
    [2001] Random forests. Machine Learning, 45(1), 5–32.
    [Google Scholar]
  4. Dixon, G.E. and Keyser, C.E.
    [2008] Lake States (LS) Variant Overview – Forest Vegetation Simulator. USDA Forest Service, Forest Management Service Center, 54 (International Report).
    [Google Scholar]
  5. Finney, M.A.
    [1998] FARSITE: Fire Area Simulator-model development and evaluation. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, 47.
    [Google Scholar]
  6. [2002] Fire growth using minimum travel time methods. Canadian Journal of Forest Research, 32(8), 1420–1424.
    [Google Scholar]
  7. [2006] An Overview of FlamMap Fire Modeling Capabilities. Conference Proceedings. 28–30 March 2006. USDA, Forest Service, Rocky Mountain Research Station, 213–220.
    [Google Scholar]
  8. Hansen, M.C., Potapov, P.V., Moore, R., Hancher, M., et al.
    [2013] High-Resolution Global Maps of 21st-Century Forest Cover Change. Science, 342(6160), 850–853.
    [Google Scholar]
  9. Kalabokidis, K., Ager, A., Finney, M., Athanasis, N., Palaiologou, P. and Vasilakos, C.
    [2016] AEGIS: A wildfire prevention and management information system. Natural Hazards and Earth System Sciences, 16(3), 643–661.
    [Google Scholar]
  10. Miller, C., Abatzoglou, J., Brown, T., and Syphard, A.D.
    [2011] Wilderness Fire Management in a Changing Environment. The Landscape Ecology of Fire, 269–294.
    [Google Scholar]
  11. Miller, C. and Ager, A.A.
    [2013]. A review of recent advances in risk analysis for wildfire management. International Journal of Wildland Fire, 22(1), 1–14.
    [Google Scholar]
  12. Modugno, S., Balzter, H., Cole, B. and Borrelli, P.
    [2016] Mapping regional patterns of large forest fires in Wildland–Urban Interface areas in Europe. Journal of Environmental Management, 172, 112–126.
    [Google Scholar]
  13. Myroniuk, V., Kutia, M., Sarkissian, A.J., Bilous, A. and Liu, Sh.
    [2020] Regional-Scale Forest Mapping over Fragmented Landscapes Using Global Forest Products and Landsat Time Series Classification. Remote Sensing, 12(1), 187.
    [Google Scholar]
  14. Rollins, M.G.
    [2009] LANDFIRE: A nationally consistent vegetation, wildland fire, and fuel assessment. International Journal of Wildland Fire, 18(3), 235–249.
    [Google Scholar]
  15. Scott, J.H. and Burgan, R.E.
    [2005] Standard fire behavior fuel models: a comprehensive set for use with Rothermel’s surface fire spread model. (RMRS-GTR-153). USDA, Forest Service, Rocky Mountain Research Station, 72 (General Technical Report).
    [Google Scholar]
  16. Simard, M., Pinto, N., Fisher, J.B., and Baccini, A.
    [2011] Mapping forest canopy height globally with spaceborne lidar. Journal of Geophysical Research, 116(G4), G04021.
    [Google Scholar]
  17. Tedim, F., Xanthopoulos, G., and Leone, V.
    [2015]. Forest Fires in Europe: Facts and Challenges. In Wildfire Hazards, Risks and Disasters. Elsevier, Chapter 5, 77–99.
    [Google Scholar]
  18. World Bank Policy Note: Managing Wildfires in a Changing Climate
    World Bank Policy Note: Managing Wildfires in a Changing Climate [2020]. The World Bank, 32.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20215521113
Loading
/content/papers/10.3997/2214-4609.20215521113
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error