Assessing factors impacting inter-satellite variability of grassland curing estimates for fire monitoring in Victoria, Australia using remote sensing

Abstract

Grassland fires in Victoria, Australia pose significant environmental issues. Monitoring these fires relies on the Grassland Curing Degree (GCD) indicator and the corresponding Grassland Curing Map (GCM) for spatial distribution. Inter-satellite variability (ISV) assesses the variations in Grassland Curing Maps (GCMs) produced from remote sensing data with varying spatial resolutions (SR). Higher SR data improves GCM accuracy but increases processing time. ISV helps identify priority areas that need higher SR imageries. This study analyzes sample sites in Victoria and finds correlations between ISV, seasonality, temperature, precipitation, and distance to residential areas. Results reveal lower ISV during summers and autumns compared to winters and springs. Temperature shows a strong negative linear relationship with ISV, indicating that higher temperatures result in lower ISV. Precipitation exhibits a weak positive correlation with ISV, suggesting heavier precipitation leads to increased ISV. Distance to grasslands negatively correlates with ISV, indicating that greater distances from residential lands result in lower ISV. Based on these findings, it is recommended to use higher SR satellite data for GCM creation during winters and springs when temperatures are low, precipitation is heavy, and areas are closer to residential lands. Implementation suggestions are provided for fire management based on these results.

Keywords

• grassland fire
• remote sensing
• environmental monitoring
• decision support
• gis
• earth observation