P1.37
GOES-R ABI fire detection and monitoring development activities
Christopher C. Schmidt, CIMSS/Univ. of Wisconsin, Madison, WI; and S. Lindstrom, J. Hoffman, J. Brunner, and E. M. Prins
The international environmental monitoring and scientific research communities have stressed the importance of utilizing operational satellites to produce routine fire products for hazards applications and to ensure long-term stable records of fire activity for land-use/land-cover change analyses and global climate change research. Since the year 2000, the GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA) has been providing diurnal information on fire activity throughout the Western Hemisphere. The Advanced Baseline Imager (ABI) on GOES-R and beyond will enable continued analysis of fire activity with significant improvements in fire detection and sub-pixel fire characterization. UW-Madison CIMSS has modified the current WF_ABBA to take advantage of the enhanced fire monitoring capabilities of ABI. Modifications include updating modules that identify and characterize sub-pixel fire activity. Various GOES-R ABI proxy data sets are used to test the updates. In order to understand the impact of these modifications and to evaluate the performance of the GOES-R ABI WF_ABBA, the algorithm was applied to simulated GOES-R ABI data derived from higher spatial resolution MODIS data and model simulated ABI data. The results demonstrate the robustness of the algorithm to meet GOES-R requirements for fire monitoring.
Poster Session 1, Fifth GOES Users' Confererence Poster Session
Wednesday, 23 January 2008, 2:30 PM-4:00 PM, Exhibit Hall B
Previous paper Next paper