# The Spotting Distribution of Wildfires
## 4 Discussion
### Measurements of Spotting Distributions  
The primary challenge for the spotting experimentalist is the paucity of quantitative observations from real fires. The landing fire brands could be visualized by visual recording or infrared recording. In the paper \"Monitoring Insect Dispersal\", by [PERSON] _et al._ in the collection [27], the authors discuss \"vertically looking radar\" (VLR). Such radar has been used to study insect dispersal, and consists of a series of gates capable of monitoring the skies from 100 m to a kilometre above ground. In addition, the VLR system is capable of determining flying mass, direction and magnitude of the velocity vector of a flying brand. One could imagine field experiments where such instrumentation is employed, in order to count how many, to which height and with what mass are the firebrands being released.  
In field situations, the ignition probability can be estimated by the number of spot fires which result per unit of landed firebrand mass, or ideally extrapolated from laboratory experiments. Satelite data, or other forms of radar collection could be of use here as well; while individual spotting events may only be observable through the appearance of a new fire, if we had detailed spotting information for a particular fire situation, such information could help inform the likelihood of long-distance dispersal.  
There are some field experiments, in particular from Australia's Project Vesta [54; 55], where attempts have been made to directly measure the spotting distribution. In particular, in a series of experimental fires, firebrand distributions were measured by catching brands on plastic sheets. The goal was to validate earlier firebrand modelling employing the CSIRO wind tunnel by [PERSON] [9], though the results were mostly qualitative and the need for model improvement was a primary finding.  
In controlled lab experiments, several trees could be alighted in a wind stream and all landing embers can be first put out, then counted and weighed, as has been done in experiments by [PERSON] [44; 45]. Both of these approaches (field and lab) give us the landing distribution \(\mathbb{L}(x,m)\). To get the spotting distribution \(\mathbb{S}(x)\) we need a second ingredient, which is the probability of ignition \(E(m)\). Several lab experiments have been done already, where burning material is thrown into various fuel beds and the ignition probability has been measured using regression analysis in quite some depth ([46; 47]). In the very heteeogeneous natural spotting environment, understanding the variability in spotting ignition probabilities over space and time is very important.  
We believe that many of this data is already available in various fire management and research centers, but, to our knowledge, they have not been systematically examined to estimate a spotting distribution. Promising data are available for example for the 1961 Basin Fire in the Sierra National Forest (USA) [56], the 1994 South Canyon Fire in Colorado [57], the 1994 Butte City Fire in Idaho [58] and the Oakland/Berkeley Hills Fire [59], which in particular was described in the review paper by [PERSON] _et al._[12]. We leave a detailed exploration of these data to future research and we write this paper in the hope of generating increased interest in better quantifying the lesser known model components.  
We have seen that the derivation of specific spotting distributions depends on many physical details, which we outline in the Appendix. However, direct measurement might enable us to skip the detailed physical modelling and rather use an empirically measured spotting distribution.