High-detail fuel moisture content monitoring using the RISERnet sensor network (#112)
Sensor networks (wireless networks of sensor-enabled computing devices deployed in the field) can generate high-detail and real-time information about sensitive and changing environments. RISERnet is one such sensor network of almost 100 nodes deployed over a 1km square region of forest in the Dandenong Ranges, Victoria. This network continually monitors a range of environmental parameters, including solar radiation, soil moisture, temperature, humidity, wind speed, and wind direction. Based on this data, the RISER research project (resilient information systems for emergency response) is developing the capability to derive estimates of fuel moisture content (FMC) at much finer levels of detail than possible with current technologies. Adapting established models of fuel moisture content (e.g., Matthews, 20061 ), the project is using the environmental data from the sensor network to compute fuel moisture content over the monitored area with high spatial detail (10s of metres) and temporal detail (variations over the course of hours). The results will then be experimentally validated using independent field measurements of fuel moisture. Using new data sources in this way can help to increase the resilience of the information systems for emergency response. Resilient information systems must continue to capture, collate, and communicate timely and relevant information, even in the extreme and unexpected circumstances surrounding an emergency. By diversifying the range of information sources available to decision makers and the level of spatial and temporal detail in those information sources, the ultimate aim is to improve situational awareness of conditions in the forest.
- Matthews, S. (2006) A process-based model of fine fuel moisture. International Journal of Wildland Fire, 15:155-168.