Abstract
Abstract. Forest fire is one of the most serious environmental problems in Kenya that influences human activities, climate change and biodiversity. The main goal of this study is to apply medium resolution sensors (Landsat 8 OLI and Sentinel 2 MSI) to produce burnt area severity maps that will include small fires (< 100 ha) in order to improve burnt area detection and mapping in Kenya. Normalized burnt area indices were generated for specified pre- and post-fire periods. The difference between pre- and post-fire Normalized Burnt Ration (NBR) was used to compute δNBR index depicting forest disturbance by fire events. Thresholded classes were derived from the computed δNBR indices to obtain burnt severity maps. The spatial and temporal agreements of the Burnt area detection dates were validated by comparing against the MODIS MCD641 500 m products and MODIS Fire Information for Resource Management System (FIRMS) 1 km daily product hot-spot acquisition dates. This approach was implemented on Google Earth Engine (GEE) platform with a simple user interface that allows users to auto-generate burnt area maps and statistics. The operational GEE application developed can be used to obtain burnt area severity maps and statistics that allow for initial accurate approximation of fire damage.
Highlights
Fire is a natural disturbance that profoundly influences people, climate and ecosystems to promote biodiversity (Kelly and Brotons, 2017)
This study looks into the lack of a harmonized burnt area detection and mapping approach using medium spatial resolution optical imagery
This study developed a Google Earth Engine (GEE) application to detect burnt areas and determine burn severity from Landsat 8 OLI and Sentinel 2 MSI data
Summary
Fire is a natural disturbance that profoundly influences people, climate and ecosystems to promote biodiversity (Kelly and Brotons, 2017). In the last centuries, human induced fires and suppression efforts have altered the natural fire regimes causing a negative effect on forest cover, resilience and biodiversity (Chuvieco et al, 2019; Lewis et al, 2015). Fires that occur in densely populated areas affect air quality and are linked with health impacts to infants, people with respiratory complications and individuals with heart problems (Reid et al, 2016). As Viedma et al (2017) puts it, Land Use-Land Cover (LULC) changes by human influence has led to more hazardous landscapes, with consequent increase in fires
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