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Use of Remote Sensing Data for Delineation of Wildland Fire Effects. Presented by: Jason Adams Spatial Database Administrator Yukon Wildland Fire Management. Overview. Background Information Platforms Utilized Methodologies Employed Conclusions. Remote Sensing Platforms.
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Use of Remote Sensing Data for Delineation of Wildland Fire Effects Presented by: Jason Adams Spatial Database Administrator Yukon Wildland Fire Management
Overview • Background Information • Platforms Utilized • Methodologies Employed • Conclusions
Remote Sensing Platforms • MODIS (Moderate Resolution Imaging Spectroradiometer) • LandSAT TM/ETM (Thematic Mapper) • SPOT Image • QuickBird • Airborne GPS
Background Information • MODIS Hotspot Fire Detections
Background Information • False colour MODIS image Fall 2004 • LandSAT TM Bands very similar
Background Information Red = Band 7 (mid-IR) Green = Band 4 (near-IR) Blue = Band 3 (visual red)
MODIS Platform • There are two main products of the MODIS program employed by WFM. • Hotspot data (Thermal) • False colour imagery (Reflected Infrared)
Using MODIS Hotspot Data Classic Geoprocessing Hotspot points Buffer points Back-Buffer points
Using MODIS Hotspot Data Map Display
SPOT Image • 10m SPOT Imagery • Black indicates burn area, red indicates healthy vegetation (Similar to IR Photo) • Heads up digitized on tablet PC running ArcMap
Quickbird • In 2007 this image was acquired along the Dempster Highway and contained part of a 2007 fire. • Testing phase for uses in delineation of fire effects.
LandSAT TM • Overview of 2007 fire DA-11 in a 7-4-3 LandSAT TM band combination • Detail shown at level used for Heads-up digitizing. • Scene Level View, DA-11 seen in bottom left quadrant. • Even light cloud cover is still valuable.
Comparison of Methods • Fire BC-03-2006 • MODIS Hotspot Buffer • GPS Perimeter • LandSAT Perimeter • Comparison in detail
TM4 – TM7 NBR = TM4 + TM7 Burn Severity & LandSAT Landsat Pre and Postfire Views of the Herron River Fire, DENA 2001
Burn Severity & LandSAT • WFM has run a trial with dNBR • Some challenges are faced. • Could lead to automated fire poly generation with some GIS processing. • No field verification program, see challenges above.
Airborne GPS • Becoming rare for use as final mapping as cost and accuracy of hyper-spectral satellite imagery is becoming lower, soon to be free (LandSAT). • Mainly used on campaign fires where data is needed right away. • Although accuracy is “better” on GPS units then a 30m pixel LandSAT image the method of collection (flying around in a helicopter) compromises this. Picture an intoxicated individual walking a line.
GPS Accuracy Three hour plot of stationary GPS, differentially corrected
Airborne GPS Real World example BC-03-06 Pre Fire LandSAT Scene Pre Fire LandSAT Scene with GPS Track Post Fire LandSAT Scene Post Fire LandSAT Scene with GPS Track Post Fire LandSAT Scene with GPS Track (blue) and RS digitized perimeter (yellow) Comparison of GPS Track (blue) and RS digitized perimeter (black)
Methodologies • Primary method of fire effects (perimeter) data capture is via digitizing hyperspectral imagery on tablet PC. • Secondary method is GPS capture • Future methods to use hyperspectral data and dNBR, this will give both perimeter and severity data.
Conclusions • Given the size of the Yukon and staffing level, Remote Sensing is the ONLY option for collection of fire data. • For present time LandSAT is perfectly adequate, SPOT shows a gain is precision but would be cost prohibitive. • Quickbird is interesting however would probably be only used for WUI or large scale mapping of culturally/ecologically significant targets
Thank-you Haeckel Hill Fire, Whitehorse, 1991