Utilizing Vegetation and Environmental New Micro Spacecraft (VENµS) Data to Estimate Live Fuel Moisture Content in Israel's Mediterranean Ecosystems

Abstract

Increasing fire activity in Mediterranean ecosystems necessitates the development of new methods to quantify fire risk. Fire risk is strongly affected by live fuel moisture content (LFMC) in plants. Unfortunately, LFMC is time-consuming to measure in-situ. Remote sensing is a promising alternative to field sampling of LFMC, but existing approaches utilize sensors with high spatial resolution but infrequent revisit times, or frequent acquisition at coarse spatial grains. We developed and evaluated LFMC models for Israel's Mediterranean ecosystems using Vegetation and Environmental New Micro Spacecraft (VENμS), a satellite which was developed specifically for monitoring Mediterranean vegetation. We combined vegetation indices derived from VENμS with ancillary data to build statistical models of LFMC in six study sites located along a steep rainfall gradient. Out of the five vegetation indices we tested, only red-edge position was a significant predictor of LFMC, though its effect depended on tree cover. A model including red-edge position, tree cover, year-day, and slope-aspect explained 32.5% of the variation in LFMC. The moderate predictive power of this model was higher than expected given that VENμS does not have the shortwave infrared (SWIR) bands which are typically used to detect water content in plants. A comparison with six vegetation indices derived from Sentinel 2 data revealed that VENμS' data explained considerably more variation in LFMC, even though some Sentinel 2 VI's are based on SWIR bands. Our results suggest that VENμS data, combined with ancillary data, may provide a rough estimate of LFMC in Israel's Mediterranean regions and as such might be suitable for preliminary monitoring purposes.

Keywords

• Fire risk
• live fuel moisture
• Mediterranean
• Sentinel 2
• vegetation and environmental new micro spacecraft (VENµS)