Search

The russian military aggression and the related socio-economic and environmental consequences have significantly affected the climate and production of ecosystem services through damage to forests, ecosystems, landscape fires and emissions of gases into the atmosphere. The study aims to estimate carbon dioxide emissions due to landscape fires in Ukraine during the year 2022. The OroraTech wildfire monitoring technology was used to detect fires, while perimeters of burned areas were delineated with Sentinel 2 time series. The Copernicus Dynamic Land Cover map was used to extract burned land covers. Emissions were calculated based on the intensity of fires (dNBR) with the share of burned biomass in different types of land cover. Biomass models were selected considering the dominant tree species within a specific region and the species structure of the sown areas of croplands. The volume of biomass losses was estimated as a result of fires of different severities. It was estimated that during in 2022, landscape fires burned 749.5 thousand hectares thereof: croplands - 419.1 thousand hectares; other natural vegetation - 273.8 thousand hectares; conifer forests - 31.1 thousand hectares; other forests - 25.5 thousand hectares. The impact of the war on landscape fires is confirmed by the large proportion of fires in the 60-kilometre buffer zone along the frontline - 68.9% of the total area of fire. Among all fires, 42.5% of fires occurred in the occupied territory. Total CO2 emissions from all types of landscape fires reached 5.20 million tons and other greenhouse gases - 0.28 million tons. It is the first detailed mapping of landscape fires with an analysis of each polygon for the whole territory of Ukraine. The results provide important information for assessing the loss of ecosystem services and estimating carbon dioxide emissions as well as for confirming the impact of hostilities on landscape fires. [ABSTRACT FROM AUTHOR]

Evaluation of forest fire severity is a basis of post-fire forest management. Remote sensing-based methods enable reliable delineation of fire perimeters, however, assessments of the degree of forest damage need to be verified and adjusted through field sampling. The forest damage assessment conducted in this study is useful for practitioners to understand and justify the design of clear cuts for restoration purposes. Thus, the aim of the study is to verify the different approaches to field assessment of forest fire severity. In this paper, the authors present a site-specific assessment of large wildfires in Luhansk oblast, Ukraine occurred in 2020 using field-based burn severity indices. The Composite Burn Index (CBI) and the Geometrically Structured Composite Burn Index (GeoCBI) were used to estimate the extent of forest damage. The Burned Area Emergency Response (BAER) methodology was also tested to assess the extent of soil damage. The authors used PlanetScope images to delineate perimeters of burned areas. These perimeters were overlaid over a forest inventory database to extract forest attributes and site characteristics for all forested and unforested areas affected by fires. Within the fire perimeters, the burned area was stratified into six strata to independently account for forest damage in diverse types of land cover. In total 73 test plots were proportionally distributed among different classes of land cover to assess fire severity using CBI, GeoCBI, and BAER approaches. It was found that the fire’s footprints covered 39,782 hectares. Among that area, 21.2% were forested lands. About 78% of burned forests were pine plantations. The highest fire intensity levels were estimated within pure pine plantations that were grown in very dry sites, while the lowest ones were associated with hardwoods forests in moisture site conditions. The average estimates of fire severity using the field-based indices varied within strata (CBI>GeoCBI) which could be an issue for assessing burn severity using remote sensing-based approaches. The authors also concluded that the BAER methodology contributed less to assessing the fire intensity because soil burn severity is not directly related to vegetation damage. This work creates a foundation for further assessment of fire severity using satellite imagery. As a result of this study, a spatial data set of sample plots was proposed that can facilitate calibrating approaches used to map fire severity in the region. [ABSTRACT FROM AUTHOR]