USDA Forest Service, Remote Sensing Applications Center, FSWeb: WWW: Monitoring Vegetation...
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![Page 1: USDA Forest Service, Remote Sensing Applications Center, FSWeb: WWW: Monitoring Vegetation Regeneration.](https://reader037.fdocuments.net/reader037/viewer/2022102805/5517f502550346c1568b4d49/html5/thumbnails/1.jpg)
USDA Forest Service, Remote Sensing Applications Center, FSWeb: http://fsweb.rsac.fs.fed.us
WWW: http://www.fs.fed.us/eng/rsac/
Monitoring Vegetation Regeneration after Wildfire
Jess Clark
USFS Remote Sensing Applications CenterIn cooperation with:
Marc Stamer (San Bernardino NF), Kevin Cooper (Los Padres NF), Carolyn Napper (San Dimas T&D), Terri Hogue (UCLA)
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Need for Post-fire Monitoring
• Wildfire Effects• BAER Assessments and Treatments• Monitoring Requirements
– Who, how often, for how long, who pays?• Values at Risk
Photo credit: Robert Leeper
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Role of Remote Sensing
• Severity mapping (NBR / dNBR)• Monitoring (NDVI / EVI)• Predictive Modeling (Regression)• Decision Support Tools
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Role of Remote Sensing
• Vegetation Indices– NDVI, EVI, NBR
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Severity Mapping
• Snapshot in time (NBR / dNBR)– e.g., BAER, RAVG, MTBS– Classes / protocols well defined
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Monitoring
• NDVI / EVI for monitoring over time– Trends Analysis
• Current compared to pre-fire condition
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Monitoring
• NDVI / EVI for monitoring over time– Hybrid Static Cover Layer
• Pixel values represent actual cover values
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Project Objectives
• Assess effectiveness of remote sensing to monitor vegetation regeneration– Methods:
• Field data collection• Remote sensing based observations• Correlation analysis / predictive modeling• Application
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Locations
• Six fires: Old (2003), Am. River Complex (2008), La Brea (2009), Station (2009), Bull (2010), Canyon (2010)
Am. River Complex
Bull / Canyon
Old
StationLa Brea
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Methods – Field Data Collection
• Pole-mast photography– “Plot” = area of
homogeneous ground condition
– Between 4 and 10 photos per plot
– Photos interpreted later
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Methods – Photo Interpretation
• Pole-mast photography– Each photo interpreted cover vs. no-cover– Stats summarized by plot (4 to 10 photos)
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Methods – Satellite Imagery
• Imagery collected pre- and post-fire• NDVI / EVI creation• Pixel values summarized by plot areas
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Results
• NDVI and EVI both showed relatively high correlation to ground cover
• Leads to application of thresholds for thematic output
0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80
0
20
40
60
80
100
120
f(x) = − 466.037310938107 x² + 519.495828059246 x − 40.0240177691607R² = 0.723908499042396
Ground Cover and EVI
0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80
0
20
40
60
80
100
120
f(x) = − 238.492333272508 x² + 390.067742280946 x − 51.0262670408163R² = 0.64865204261544
Ground Cover and NDVI
EVI Value NDVI Value
% G
roun
d Co
ver
% G
roun
d Co
ver
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Discussion and Limitations
• Less than perfect field data collection– Clumping of fires, not values
• Some historic (recovered) fires and some current (still black) fires
– Muddy results in critical data range• Poor linear function in the 0.2 – 0.35 NDVI
data range
0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80
0
20
40
60
80
100
120
Ground Cover and NDVI
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Application for New Fires
• Time series imagery for new fires– Horseshoe 2,
Monument, Schultz• NDVI and EVI
cover map• Available for
evaluation
Schultz
Horseshoe 2
Monument
Phoenix
Tucson
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Schultz (2010) – Applied Results
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Horseshoe 2 (2011) – Applied Results
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Monument (2011) – Applied Results
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Decision Support Tool
• Tool for resource managers / line officers
• When has the risk sufficiently lessened?
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USDA Forest Service, Remote Sensing Applications Center, http://fsweb.rsac.fs.fed.us
Decision Support Tool
• Post-fire Watershed Planning Decision Support Process
1. Define critical values2. Define AOI3. Acquire imagery and VI4. Summarize VI by AOI5. Probability of damage6. Identify risk7. More ESR work needed?
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USDA Forest Service, Remote Sensing Applications Center, FSWeb: http://fsweb.rsac.fs.fed.us
WWW: http://www.fs.fed.us/eng/rsac/
Comments / Questions?
Jess Clark
801-975-3769