Active Fire Detection using Geostationary Satellites L Giglio
- Slides: 24
Active Fire Detection using Geostationary Satellites L. Giglio SSAI/University of Maryland GOFC Global Geostationary Fire Monitoring Applications Workshop 23 -25 March 2004
Overview • Satellite-based fire detection algorithms • Generic issues related to multi-satellite fire monitoring • Polar vs. geostationary satellite suite comparison – Issues – Biases
Introduction • Multiple systems currently providing active fire data and new systems are being planned • Different systems offer different capabilities – Different detection capabilities (spatial/temporal) – Different fire monitoring groups using different methods and different algorithms • Accuracy of the different systems not well quantified – Systematic validation activities being initiated • User community is starting to combine data from these multiple systems – complementary data sets
Satellite-Based Fire Detection Algorithms • Virtually all exploit tremendous radiative energy emitted at ≈4 µm, usually in conjunction with a longer wavelength ≈10 µm band – Exception is DMSP-OLS • ABBA/WF-ABBA (Prins et al. ) are the premier detection algorithms for geostationary satellite instruments – GOES VAS, GOES Imager • Detection principals are well-described elsewhere
Geostationary Satellite Suite • GOES-8 – 1995 -2003 • GOES-10 – 1998 onward • GOES-12 – 2003 onward • MSG-1 – 2003 onward • MTSAT – Late 2004
International Global Geostationary Active Fire Monitoring: Geographical Coverage 80 60 -120 GOES-W -80 GOES-E -40 0 40 80 120 MSG 160 MTSAT 40 Satellite View Angle 80° 65° 20 0 -20 -40 -60 -80 322
Multi-Satellite Fire Monitoring: Generic Issues • Systems have – Different spatial resolutions – Different radiometric characteristics – Different temporal sampling • How do we combine observations from multiple instruments in a consistent, meaningful manner?
Polar Fire Monitoring: Strengths and Weaknesses • Strengths – Global coverage • Frequency of global coverage depends on scan width – Higher spatial resolution • Moderate resolution – AVHRR, MODIS (1 km) • High resolution – Landsat, ASTER (30 m) • Weaknesses – Fewer opportunities for cloud-free observations • MODIS Terra/Aqua give four observations per 24 hrs – Greater variance in envelope of detectable fires (off nadir vs. nadir) – Temporal sampling issues related to diurnal fire cycle
Theoretical Detection Envelope • MODIS • Temperate deciduous rainforest • Night • 0° scan angle • Summer • No background fires
Geostationary Fire Monitoring Suite: Strengths and Weaknesses • Current Strengths – Hemispheric fire monitoring – Near-real time data for fire management – Few/no temporal sampling issues related to diurnal fire cycle – Broad Direct Broadcast capability • Current Weaknesses – Gaps in global spatial coverage – Spatial biases in envelope of detectable fires
Potential Gaps in Spatial Coverage
Spatial Biases in Envelope of Detectable Fires (1 of 2) • For instruments on board geostationary satellites, pixel size varies as a function of distance from the sub-satellite point – Introduces spatial gradient in the envelope of detectable fires
Size of footprint relative to footprint size at subsatellite point.
Spatial Biases in Envelope of Detectable Fires (2 of 2) • Complicates comparison of fire activity in different regions, even using a single satellite • Not an issue for near-real time fire monitoring • Will need to be addressed in production of a global data set
High resolution sensors can provide muchneeded fire size distributions. ASTER Scene 2. 4 µm R 1. 6 µm G 0. 5 µm B
Size Distribution of Active Fires
Southern Africa, 2000 Morisette et al. , in press.
GOES Diurnal Cycle Research Issue • How to merge different sampling of diurnal fire cycle? – Temporal sampling exhibits a spatial dependence since local time varies with longitude – What impact does this have on the number of fires detected when combined with the spatial variation in detection envelope?
TRMM VIRS Diurnal Fire Cycle Borneo 1999 -2001
GOES Local Sampling Time: Function of Longitude
Summary • Geostationary satellite suite will provide a major contribution to global fire monitoring capability • Ultimately envision merging both polarorbiting and geostationary fire data sets to exploit strengths of each • Interesting research opportunities in addressing potential issues
- Geosynchronous and geostationary satellite difference
- Geostationary orbit
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