1. An Examination of the Relation between Burn Severity and Forest Height Change in the Taylor Complex Fire using LIDAR data from ICESat/GLAS Andrew Maher Qingyuan Zhang a,b, Bobby H. Braswell c, Elizabeth M. Middleton b, and Andrew T. Hudak d a Goddard Earth Sciences & Technology Center, University of Maryland, Baltimore County, Baltimore, MD 21228 b Biospheric Sciences Branch, Code 614.4, NASA/Goddard Space Flight Center, Greenbelt, MD 20771 c Complex Systems Research Center, University of New Hampshire, Durham, NH, 03824 d Rocky Mountain Research Station, USDA Forest Service, Moscow, ID 83843

2. Motivation Wildfires consume above ground biomass, releasing carbon into the atmosphere. Standard remote sensing methods for analyzing post-fire burn areas can estimate total carbon release, biomass loss, and smoke production, but cannot directly observe the change in vegetation structure (Miller et al, 2006). Better understanding of change in vegetation structure would allow for a more detailed ecological analysis of fire disturbance areas, validation of current change detection algorithms, and other scientific analyses.

3. Landsat TM Burn Severity Classification Reflectance of TM band 4 (near infrared; NIR) and band 7 (short wave infrared; SWIR) Burn severity levels (high, moderate, low, unburned) derived from dNBR thresholds Charred area; no direct observation of vegetation structure

4. ICESat/GLAS 70m diameter footprints spaced every 175m Distribution of vegetation height within footprint Non-continuous swaths (time series analysis becomes tricky) Products Used GLA01 –Raw waveform (digital bins) –Background noise GLA14 –Signal beginning, signal end, etc. –Gaussian fits (up to 6) Typical GLAS shot waveform (Harding et al. 2005)

5. Objectives 1.Assess fire disturbance using burn severity classes derived dNBR. 2.Investigate the fire effect on canopy heights using GLAS data. 3.Compare two approaches and their relation. Use Taylor Complex fire in Alaska, 2004 as case study. –Largest US fire of 2004 (478,274 ha) –Landsat TM images on 9/15/2003 and 9/8/2004 were acquired. Low, Moderate, and High Burn Severity Areas in Alaskan Taylor Complex Fire (Lentile et al. 2006)

6. Methods 1.Location Matching Approach Find location with an overlapping pre-fire and post-fire shot. Characterize change in waveform in relation to burn severity. 2.Statistical Approach Apply filters to GLA14 data and GLA01 waveforms to reduce bad interpretations of waveforms and/or noisy waveforms. Calculate means and confidence intervals of various height metrics (i.e. extent, height of mean energy) for each burn severity, pre-fire and post-fire. Burn Severity Map of Taylor Complex Fire with GLAS shots from 2003-2006 (~57,000 shots)

7. Location Matching Approach Burn severity class: Low

8. Location Matching Approach Burn severity class: Moderate

9. Location Matching Approach Burn severity class: High

10. Location Matching Approach

11. Statistical Approach - Filtering Numerical filters on GLA01 and GLA14 data –Max lidar return > 70 –Signal to noise ratio (snr) > mean(snr of all shots) –Extent (signal beginning – ground peak offset) < 80m –Common area Visual Filter on waveform –Verify GLA14 data matches the features of the waveform.

13. Conclusions GLAS data shows that change in canopy height correlates with burn severity. Only pre-fire heights are significantly different for different burn severities. –Differencing indices, such as dNBR, are known to be correlated with pre-change image (Miller et al. 2006).

14. Future Considerations Statistically quantify correlation of dNBR values to change in canopy heights. Analyze height change in unburned areas. –Check for spatial and/or temporal patterns in unburned height change to identify cause (i.e. incorrect burn classification and/or noise) –Search for other causes of disturbance. Test alternative waveform processing methods. –More advanced numerical analysis (i.e. Fourier analysis, wavelets) –Web-based machine learning application

15. Thank You Qingyuan Zhang Bobby H. Braswell Elizabeth M. Middleton Andrew T. Hudak George Hurtt Research and Discover Program NASA Goddard Space Flight Center