Based on the physical concept of heat energy of pre-ignition,a new fire susceptibility index (FSI) is used to estimate forest fire risk. This physical basis allows calculation of ignition probabilities and comparisons...Based on the physical concept of heat energy of pre-ignition,a new fire susceptibility index (FSI) is used to estimate forest fire risk. This physical basis allows calculation of ignition probabilities and comparisons of fire risk across eco-regions. The computation of the index requires inputs of fuel temperature and fuel moisture content (FMC),both of which can be estimated using remote sensing data. While ASTER data for land surface temperatures (LST) was used as proxys for fuel temperatures,fuel moisture content is estimated by regression technique utilizing the ratio NDVI/LST of ASTER data. FSIs are computed in peninsular Malaysia for nine days before the fires of 2004 and 2005 and validated with fire occurrence data. Results show that the FSI increases as the day approaches the fire day. This trend can be observed clearly about four days before the day of fire. It suggests that FSI can be a good estimator of fire risk. The physical basis provides a more meaningful FSI,allows calculation of ignition probabilities and facilitates the development of a future class of fire risk models. FSI can be used to compare fire risk across different eco-regions and time periods. FSI retains the flexibility to be localized to a vegetation type or eco-regions for improved performance.展开更多
基金Projects KSTAS/MACRES/T/2/2004 supported by the Airborne Remote Sensing (MARS) Program of Malaysia, 4067113040671122 by the National Natural Science Foundation of China
文摘Based on the physical concept of heat energy of pre-ignition,a new fire susceptibility index (FSI) is used to estimate forest fire risk. This physical basis allows calculation of ignition probabilities and comparisons of fire risk across eco-regions. The computation of the index requires inputs of fuel temperature and fuel moisture content (FMC),both of which can be estimated using remote sensing data. While ASTER data for land surface temperatures (LST) was used as proxys for fuel temperatures,fuel moisture content is estimated by regression technique utilizing the ratio NDVI/LST of ASTER data. FSIs are computed in peninsular Malaysia for nine days before the fires of 2004 and 2005 and validated with fire occurrence data. Results show that the FSI increases as the day approaches the fire day. This trend can be observed clearly about four days before the day of fire. It suggests that FSI can be a good estimator of fire risk. The physical basis provides a more meaningful FSI,allows calculation of ignition probabilities and facilitates the development of a future class of fire risk models. FSI can be used to compare fire risk across different eco-regions and time periods. FSI retains the flexibility to be localized to a vegetation type or eco-regions for improved performance.
