Development and Evaluation of the Photoload Sampling Technique

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.

[1]  James K. Brown,et al.  Handbook for inventorying surface fuels and biomass in the interior West. General technical report , 1982 .

[2]  John K. Brown,et al.  Downed dead woody fuel and biomass in the Northern Rocky Mountains , 1981 .

[3]  German Sausage.  USDA is an equal opportunity provider and employer , 2015 .

[4]  Jw Van Wagdendonk,et al.  Physical properties of woody fuel particles of Sierra Nevada conifers , 1996 .

[5]  Testing the accuracy of growth and yield models for southern hardwood forests. , 2000 .

[6]  James K. Brown,et al.  Surface Fuel Loadings and Prediced Fire Behavior for Vegetation Types in the Northern Rocky Mountains , 1986 .

[7]  Van Wagner.  The Line Intersect Method in Forest Fuel Sampling , 1968 .

[8]  R. D. Ottmar,et al.  Consume users guide. Forest Service general technical report , 1993 .

[9]  M. A. Fosberg,et al.  Drying Rates of Heartwood Below Fiber Saturation , 1970 .

[10]  Robert E. Keane,et al.  First Order Fire Effects Model: FOFEM 4.0, user's guide , 1997 .

[11]  John F. Caratti,et al.  FIREMON: Fire Effects Monitoring and Inventory System , 2012 .

[12]  Duncan C. Lutes.  Assessment of the Line Transect Method: An Examination of the Spatial Patterns of Down and Standing Dead Wood 1 , 2002 .

[13]  J. Agee.  Fire Ecology of Pacific Northwest Forests , 1993 .

[14]  M. Harmon,et al.  Ecology of Coarse Woody Debris in Temperate Ecosystems , 1986 .

[15]  James K. Brown.  A Planar Intersect Method for Sampling Fuel Volume and Surface Area , 1971 .

[16]  D. Neary,et al.  Fire's effects on ecosystems , 1998 .

[17]  W. C. Fischer.  Photo guide for appraising downed woody fuels in Montana forests: Interior ponderosa pine, ponderosa pine - larch - Douglas-fir, larch - Douglas-fir, and interior Douglas-fir cover types , 1981 .

[18]  D. H. Knight,et al.  Aims and Methods of Vegetation Ecology , 1974 .

[19]  Duncan C. Lutes.  Comparison of methods for the quantification of coarse woody debris and identification of its spatial scale| A study from the Tenderfoot Creek Experimental Forest, Montana , 1999 .

[20]  Göran Ståhl,et al.  Point relascope sampling of downed coarse woody debris , 1999 .

[21]  C. S. Wright,et al.  Stereo photo series for quantifying natural fuels Volume IX: oak/juniper in southern Arizona and New Mexico. , 2007 .

[22]  J. Gove,et al.  Point Relascope Sampling: A New Way to Assess Downed Coarse Woody Debris. , 2001 .

[23]  Joe H. Scott,et al.  Stereo Photo Guide for Estimating Canopy Fuel Characteristics in Conifer Stands , 2015 .

[24]  Robert E. Keane,et al.  The photoload sampling technique: estimating surface fuel loadings from downward-looking photographs of synthetic fuelbeds , 2007 .

[25]  Robert E. Keane,et al.  A comparison of five sampling techniques to estimate surface fuel loading in montane forests , 2008 .

[26]  C. E. Van Wagner,et al.  Conditions for the start and spread of crown fire , 1977 .

[27]  James K. Brown.  Handbook for inventorying downed woody material , 1974 .

[28]  R. Rothermel.  A Mathematical Model for Predicting Fire Spread in Wildland Fuels , 2017 .

[29]  Jerry Williams,et al.  Protecting People and Sustaining Resources in Fire-Adapted Ecosystems A Cohesive Strategy , 2000 .

[30]  F. Albini.  Estimating Wildfire Behavior and Effects , 1976 .

[31]  R. Keane,et al.  Mapping wildland fuels for fire management across multiple scales: Integrating remote sensing, GIS, and biophysical modeling , 2001 .

[32]  Robert W. Mutch,et al.  Fighting Fire with Prescribed Fire: A Return to Ecosystem Health , 1994, Journal of Forestry.

[33]  R. Burgan,et al.  BEHAVE : Fire Behavior Prediction and Fuel Modeling System -- FUEL Subsystem , 1984 .