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Advanced Remote Sensing Technologies for Monitoring Postburn Vegetation Trends and Conditions
Natural resource managers have been unable to statistically monitor the results of prescribed fires in the grassland-shrub environment. Often, only a yearly ocular review of a prescribed fire is practicable. This kind of ocular monitoring may miss critical information and may be misleading in assessing the ecosystem for fire effects, damages, and benefits; evaluating the success or failure of the burn; and determining the return interval for the reintroduction of fire. Natural resource managers and the scientific community need to develop efficient methods for evaluating the results of prescribed fires. Often prescribed fires are proposed and implemented because it is believed that the natural fire regime has been altered and that prescribed fire will restore the land to a healthier state. However, this may not be the case and there is rarely any followup after a prescribed fire to evaluate the results. In this proposal, we suggest that grassland-shrub and sagebrush vegetation communities can be consistently and accurately identified and mapped by using imaging spectroscopy, an advanced remote sensing technique.
- Quantify by advanced remote sensing techniques the effect over time of prescribed fire in a grassland-shrub environment to assess its success in accomplishing the goals set forth in the Burn Plan for two study sites. Results will then be used to develop ccurate trend data that will determine whether the prescribed fire objectives were met. Remote sensing and field techniques developed and used in this project will be documented in a format understandable to wildland fire managers and publicly distributed through a project Internet site.
- Test the relations between ground-measured chlorophyll and moisture content with the appropriate absorption features on simultaneously acquired airborne hyperspectral imagery to develop a reliable remote biomass and moisture-content monitoring system. A monitoring system of this type would permit development of multiple levels of burning characteristics for individual fuel types, enhancing inputs to computer-based fire modeling systems such as BEHAVE (Andrews 1984; Andrews and Chase 1989; Burgan and Rothermel 1984) and FARSITE (Finney 1998) beyond present capabilities. Such information may also be used to verify the accuracy of Remote Automatic Weather Station (RAWS) data moisture estimates of nearby fuels, and could be used to provide more accurate information for fuels in areas remote to RAWS data.
Box 25046 Denver Federal Center MS 964
Denver, CO 80225-0046
Phone: (303) 236-1359
- Kokaly, R.F., Rockwell, B.W., Haire, S.L., and King, T.V.V., 2007, Characterization of post-fire surface cover, soils, and burn severity at the Cerro Grande Fire, New Mexico, using hyperspectral and multispectral remote sensing: Remote Sensing of the Environment, v. 106, no. 3, pp. 305-325.
- Kokaly, R.F., 2002, Application of airborne imaging spectroscopy to areas impacted by wildfires, in J. L. Colbert, & R. K. Livingston (Eds.), Second U.S. Geological Survey Wildland Fire Workshop: U.S. Geological Survey Open-File Report 2002-11, p. 59.
- Kokaly, R., Rockwell, B., and Haire S., 2005, Characterization of Post-Fire Land Cover Using AVIRIS Data: 2005 AVIRIS Workshop, May 24, 2005.
- Robichaud, P.R., Lewis, S.A., Laes, D.Y.M., Hudak. A.T., Kokaly, R.F., and Zamudio, J.A., 2007, Postfire soil burn severity mapping with hyperspectral image unmixing: Remote Sensing of the Environment, vol. 108, pp. 467-480.