Estimating soil surface moisture in areas with high fire incidence in Serra da Canastra National Park, Brazil, using OLI and TIRS landsat-8 sensor data

The Serra da Canastra National Park (SCNP) is an important conservation unit of the Cerrado biome (Brazilian savanna) located in a mountainous area in southeastern Brazil, where the headwaters of the São Francisco River, one of the longest rivers in the country, are located. In this area, large forest fires have occurred annually, destroying native vegetation and fauna. Due to the large expanse of the Serra da Canastra National Park, firefighting in this location is a very difficult and time-consuming task. This article presents a methodological procedure for mapping soil surface moisture in areas that have shown high fire frequencies over a timespan longer than 20 years in the national park using images from the OLI (Operational Land Imager) and TIRS (Thermal Infrared Sensor) instruments onboard the Landsat-8 satellite. A soil surface moisture map was generated based on the drying of the vegetation using the temperature index calculated from a scatterplot of surface temperatures and vegetation index values in each pixel image. The vegetation index values were calculated from the normalized difference vegetation index (NDVI) algorithm using the red and near-infrared spectral bands of the OLI. The soil surface temperature was estimated using data from the TIRS sensor. We observed that areas with minimal moisture occurred on convex slopes, while areas with maximal moisture occurred on concave slopes. In addition, we found that areas with minimal moisture were more frequently located on north- and northeast-facing slopes, while areas with maximal moisture were more frequently found on south- and southwest-facing slopes. The accuracy of the soil surface moisture map was evaluated based on relative volumetric soil moisture data collected in the field using an instantaneous electronic soil moisture meter. The results of this research may contribute to the monitoring and forecasting of other areas highly susceptible to the occurrence of fire and to the planning of firefighting actions in the Serra da Canastra National Park.