HR: 0800h
AN: B11D-0769    [Abstracts]
TI: Geostatistical Modeling of Forest Fire Burn Severity
AU: Koziol, B W
EM: bkoziol@mtu.edu
AF: Michigan Tech Research Institute, 3600 Green Ct., Suite 100, Ann Arbor, MI 48105, United States
AU: * French, N H
EM: nancy.french@mtu.edu
AF: Michigan Tech Research Institute, 3600 Green Ct., Suite 100, Ann Arbor, MI 48105, United States
AB: Connecting remotely sensed measures of burn severity (i.e. Differenced Normalized Burn Ratio [DNBR]) with fuel properties during a burn is important for biomass consumption estimation. Results from a step-wise geostatistical analysis designed to measure the relative influence of physiographic and climatic factors affecting forest fire burn severity are presented. Universal and co-kriging inverse methods were used to assess spatial covariance and generate DNBR predictions and error assessments. Inputs to the model include topography, annual direct incident radiation, fire weather (i.e. temperature, relative humidity), and fuel loading. Annual direct incident radiation and fire weather exhibited correlations with burn severity implying a link with fuel moisture. Inclusion of mechanistic fuel moisture models is suggested to supplement the proximate measures used.
DE: 0426 Biosphere/atmosphere interactions (0315)
DE: 0428 Carbon cycling (4806)
DE: 0429 Climate dynamics (1620)
DE: 0430 Computational methods and data processing
DE: 0480 Remote sensing
SC: Biogeosciences [B]
MN: 2007 Fall Meeting