AUTHOR=Suresh Babu K. V. , Singh Swati , Kabdulova G. , Gulnara Kabzhanova , Baktybekov G. TITLE=Geospatial assessment of forest fire impacts utilizing high-resolution KazEOSat-1 satellite data JOURNAL=Frontiers in Forests and Global Change VOLUME=Volume 7 - 2024 YEAR=2024 URL=https://www.frontiersin.org/journals/forests-and-global-change/articles/10.3389/ffgc.2024.1296100 DOI=10.3389/ffgc.2024.1296100 ISSN=2624-893X ABSTRACT=

Forest fires or wildfires frequently occur in Kazakhstan, especially in the months from June to September, damaging the forest resources. Burnt area mapping is important for fire managers to take appropriate mitigation steps and carry out restoration activities after the fire event. In this study, KazEOSat-1 high-resolution satellite datasets are used to map the burnt area in the regions of Kazakhstan. KazEOSat-1 satellite is in a Sun-synchronous orbit, consisting of four bands, namely blue, green, red, and NIR multispectral bands, in 4 m spatial resolution, while panchromatic data are in 1 m spatial resolution. This study examined three spectral indices, namely AVI, BAI, and GEMI, for mapping the burnt area based on the four spectral bands NIR, blue, red, and green of the KazEOSat-1 satellite datasets. The DN values for each band are used to determine TOA reflectance, which is then used as a basis for deriving the aforementioned spectral indices. The results of spectral indices, AVI, BAI, and GEMI are compared based on a discriminative index (M) for quantifying the effectiveness of each index based on burned area derived from KazEOSat-1 datasets. The spectral index BAI shows higher M values than other indices; therefore, the index BAI has the higher capability to extract the burned area as compared with AVI and GEMI. Accuracy was calculated based on the number of forest fire incidents that fell in burned and unburned areas, and the results indicate that BAI shows the highest accuracy, whereas AVI shows the lowest accuracy among them. Therefore, the BAI has the highest ability for extracting the burned area using the KazEOSat-1 satellite datasets. As the revisit time period of KazEOSat is 3 days, this study will be useful to map the burnt area and fire progression in Kazakhstan.