Daily Burned Area Mapping for Prescribed Rangeland Burning in the Flint Hills Region Using MODIS Data

Abstract

HighlightsAverage burn frequency and fire size were larger in the center part of the Flint Hills region.The maximum daily burned area was 0.2 million ha. Even distribution of fires can reduce smoke impact.Fires were concentrated on days with high solar radiation. Changing this pattern can reduce the impact on O3.Abstract. Smoke from prescribed burning in the Flint Hills region impacts air quality and contributes to the exceedances of ozone (O3). The objectives of this study were 1) to map the daily burned area in this region from 2003 to 2019 using the combination of Moderate Resolution Imaging Spectroradiometer (MODIS) highest resolution imagery and standard active fire data from satellite, and 2) to identify the spatial and temporal distributions and patterns of daily fire activities. Red and near-infrared images were combined, and supervised minimum distance classification of the bi-spectral images was applied to map the daily burned area. Results showed that fire activities were highly concentrated in a few days in mid-April. The annual burned percentage (ranged from 11% to 52%) and the average fire size (ranged from 160 to 400 ha) were larger in the central part of the Flint Hills region than in the Southern part and at the edge. On average, the preferred weather conditions by landowners only occurred in around 10 days in one spring burning season. The maximum daily burned area in the Flint Hills study region was as high as 0.2 million ha, about 1/6 of the total burned area in the whole spring burning season. Based on analysis of historical daily burned area and weather data, most fires occurred on days with high solar radiation, favoring O3 production. Changing this pattern or more evenly distributed fires can reduce the smoke impact on daily O3. The results of this study provided a solid foundation for the ongoing development of O3 regression models using daily burned area and meteorological factors as predictor variables. Keywords: MODIS, Ozone, Prescribed burning, Remote sensing, Smoke impact.