Forest fires preparedness, Ukraine (2020-04-24)

Activation date: 2020-04-24
Event type: Wildfire

Activation reason:

The United Nation Development Program (UNDP) Ukraine’s Accelerator Lab works on documenting existing solutions and running experiments to test new solutions. Possible solutions include increasing the use of satellite monitoring technologies, raising awareness about sustainable agriculture such as low/no-till farming, utilizing crop residue for bio-energy, and recycling biomass to create animal feed and other household products. Interventions to limit the severity of the burning of leaves, crops, and peatlands can be made at the local policy level. As part of this program, the Copernicus EMS RRM was activated with the scope to produce suitable data to explore the issues of forest/wildfires hazards for a test area. The AOI chosen for this cases study is located south of Kremenchuts'ke reservoir near the town of Chyhyryn. Core elements of the activation comprise the analysis and generation of geospatial datasets with respect to historical fire events over a period of 5 years, fire hazard based on a multi-criteria evaluation approach, and the fire exposure of critical infrastructure, assets and population.Analysis and determination of the historic fire events.For historical fire events, the surfaces and corresponding timestamps of fires that occurred were mapped, in the periods of March-April and September-November of 2015-2020. The applied method uses a synergistic approach between: a) the combined use of thermal anomalies (fire radiative power that is used to map Hot Spots (HS), from MIR and TIR bands), and b) burnt areas classification based in reflectance from NIR, SWIR and visible bands (based on freely available Sentinel 2 and Landsat 8 HR1 images). The latter was performed using the dNBRs of consecutive S2/L8 data, in conjunction with visual interpretation.Determination of the fire hazard areasThe fire hazard is composed of multiple baseline layers. Factors relating to fuel (LULC), accessibility (e.g. transport), topography, climate, and historical distribution of fire events were considered for the estimation of forest fire hazard. The value ranges of each of factors were standardized between 1 and 10 according to e.g. interviews with the AU, with 1 being low fire hazard and 10 very high fire hazard. The final step comprised the weighting of the relative importance of each of the factors and summing all weighted factors in effect performing a linear weighted averaging in order to weight the relative importance of each input factor.Extraction and interpolation of elements (assets, population) exposed to fire hazardThe fire exposure is based on the result of the fire hazard map. To determine the exposure of critical infrastructure and population, two input layers were created - population density and asset map. The exposure of those assets is determined in a combination with the hazard map. Additional tables illustrate the number, surface and length of exposed assets according to the hazard levels. 

European Commission, Joint Research Centre (JRC) (2020): Forest fires preparedness, Ukraine (2020-04-24). European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/c05ee6fd-5116-4a85-a91c-9dd03877f293

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