The process of grassland curing can significantly impact the likelihood of ignition and the rate of spread of a grass fire. The degree of curing, expressed as a percentage by weight, is one of the key inputs to fire spread models and fire danger rating systems such as the McArthur (1977) Grassland Fire Danger Meter. Many jurisdictions have relied on visual estimates of curing percentage, typically provided by regional volunteers, as an efficient alternative to weight based estimates of curing.

Currently the  Country Fire Authority (CFA) publishes detailed state-wide curing maps using satellite imagery and data provided by volunteers who regularly report visual estimates of curing (Martin et al., 2014). The map is used to predict the progression of high fire danger conditions across the state. However, visual curing estimates are subjective and accuracy depends on the experience of the volunteer. There are also many regions where regular assessment and reporting of curing levels are more difficult.

The CFA, CSIRO and Environmental Sensing Systems are currently testing a number of ground-based sensing technologies for objective and automated recording of curing levels. These sensing systems have been installed at a test site in Victoria and have been recording and wirelessly transmitting data during the latter half of the 2013-2014 fire season. This poster will provide an overview of the sensing systems being trialled by the team and provide preliminary results showing the relationship between weight based measurements of curing, estimates based on visual observations and those derived from the automated sensor systems.