Wildland fire managers need better estimates of fuel loading so they can accurately predict potential fire behavior and effects of alternative fuel and ecosystem restoration treatments. This report presents the development and evaluation of a new fuel sampling method, called the photoload sampling technique, to quickly and accurately estimate loadings for six common surface fuel components using downward looking and oblique photographs depicting a sequence of graduated fuel loadings of synthetic fuelbeds. This report ...
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Wildland fire managers need better estimates of fuel loading so they can accurately predict potential fire behavior and effects of alternative fuel and ecosystem restoration treatments. This report presents the development and evaluation of a new fuel sampling method, called the photoload sampling technique, to quickly and accurately estimate loadings for six common surface fuel components using downward looking and oblique photographs depicting a sequence of graduated fuel loadings of synthetic fuelbeds. This report details the methods used to construct the photoload sequences (series of photos depicting gradually increasing loadings) for the six fuel components. A companion paper (RMRS-GTR-190) presents the set of photoload sequences developed from this study for common fuelbed conditions found in the northern Rocky Mountains of Montana, USA, along with a detailed sampling protocol that can be used with these photoload picture series to estimate fuel component loadings in the field at various levels of effort and scale. An evaluation of the photoload sampling technique was conducted where 29 participants were asked to estimate loadings for the six fuel components on five sites using the photoload technique. These visual estimates were compared with actual measured loadings to obtain estimates of accuracy and precision. We found that photoload estimates consistently underestimated fuel loadings (average bias 0.182 kg m-2 or 0.8 tons acre-1) but the error of the estimate (0.018 kg m-2 or 0.08 tons acre-1) was within 10 to 50 percent of the mean depending on fuel component. We also found that accuracy and precision of the photoload estimates increased with increasing field experience and also with increasing fuel loadings.
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