Abstract
Fuel load prediction equations that make use of aerial photographs were developed for Mixed Conifer, Ponderosa pine (Pinus ponderosa Dougl. Ex Laws.) and Pinyon-Juniper (Pinusedulis Engelm.) (Juniperus monosperma Engelm.) cover types from one time measurements made in the .Santa Fe watershed located in the Sangre de Cristo Mountains of northern New Mexico. Additional fuel sampling occurred at Los Alamos National Laboratory (LANL) located in the Jemez Mountains of Northern New Mexico. Use of these or similar prediction equations may be limited to certain regions and community types that exhibit similar regional characteristics such as terrain, soils, and weather conditions. This was demonstrated when the prediction equations developed from the Santa Fe watershed data set was applied to both the watershed and LANL data sets for comparison. The results of the watershed data set were favorable and exhibited a high degree of relative accuracy. The results from tl1e LANL data set did not share tl1e same degree of accuracy but rather exhibited a high degree of error. This may strongly indicate possible limitations for applied use of prediction equations of this nature to regions tl1at exhibit similar characteristics such as terrain, soils and weather. Small difference in site characteristics, such as the amount of precipitation or evapotranspiration that occurs, may have an effect on tl1e amount of bio-mass or fuels generated on one site that is not reflected on another site even though they may be within a few miles of each other.
Applied use of the prediction equations required less time than traditional fuel sampling performed on-site, but suffered from a loss of accuracy. It is strongly suggested that additional study of this method be undertaken to generate more accurate and reliable equations. Hopefully, more accurate equations may augment existing fuel sampling techniques and be put to practical use in the future for fire planning purposes.
Original language | Undefined/Unknown |
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State | Published - Jan 1 2000 |