u.s. department of the interior u.s. geological survey normalized difference vegetation index for...
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U.S. Department of the InteriorU.S. Geological Survey
Normalized Difference Vegetation Index for Restoration Monitoring
Bruce K. Wylie1, Steve Boyte2, and Yingxin Gu3
1. U.S. Geological Survey (USGS) Earth Resources Observation and Science Center, Sioux Falls, SD.2. SGT, Inc., Contractor to U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS)
Center, Sioux Falls, SD. Work performed under contract 08HQCN00053. ASRC Research & Technology Solutions, Contractor to U.S. Geological Survey (USGS) Earth Resources
Observation and Science (EROS) Center, Sioux Falls, SD. Work performed under USGS contract 08HQCN0007
Funding: USGS Land Remote Sensing, Geography Analysis and Monitoring, Climate Effects Network, and Earth Surface Dynamics and Bureau of Land Management
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Impacts of rangeland condition
Carbon sequestration and SOM preservation Water quality, sedimentation, and erosion Wildlife cover and sage grouse habitat Livestock weight gains
OBJECTIVES Tracking of range condition
Past, current, future
Facilitate adaptive management & restoration
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Rangeland production variability
Moisture-limited rangelands exhibit high interannual variations in productivity Can make management effects less evident
Grassland 2000-2006 variability in Net Ecosystem Exchange (Zhang et al. 2010)
Vegetation variability from White et al. (2005)
1st Quartile (minimum)2nd Quartile3rd Quartile4th Quartile (maximal)
Relative vegetation variability
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Separation of rangeland weather variation and nonweather variations Allows for more consistent historical trend
analysis in 1) weather-related variations and 2) nonweather-related variations
Management effects are de-trended from weather variations
Weather variations are de-trended from management and disturbance variations
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A proxy for rangeland productivity
Remotely sensed Normalized Difference Vegetation Index has been correlated to biomass, GPP, photosynthetic potential, and Leaf Area Index
NDVI =NIR – REDNIR + RED
RED NIR
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Proxy for range productivity Growing Season NDVI (GSN)
MODIS 250 NDVI Grazing Effects
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
12/6 1/25 3/15 5/4 6/23 8/12 10/1 11/20 1/9
ND
VI
A
B
MODIS 250 m NDVI grazing effects
April
June
July
October
A
B
A: grazing B: non-grazing
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Predict GSN from weather (Expected ecosystem performance – EEP)
2007 MODIS Growing SeasonNDVI (250 m)
EEPPrecipitation, maximum and minimum temperature for 3 seasons
•Winter: Nov. – Feb.•Spring: March – May •Summer: June – July
,
, weather)
=
= f (site potential
Soil Survey Geographic Database Productivity Index or long-term GSN
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Piecewise regression model to estimate rangeland performance based on weather conditions
Act
ual G
row
ing
Sea
son
ND
VI
Weather Estimated Growing Season NDVI
90 percent confidence intervals determine outliers
Overperformance
Normal
Underperformance
The models are developed from more than 10,000 random locations across multiple years
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Example Ecosystem Performance for Big Sagebrush in the Upper Colorado River Basin (2006)
Site potential
Expected ecosystem performance Real ecosystem performance
Ecosystem performance anomalies
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Ecosystem performance anomaly applications: Owyhee Uplands, Upper Colorado River Basin, and Platte River Basin
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Performance anomaly validation with percent bare ground and stocking rates (acres/animal unit month)Regions identified as persistently underperforming tended to have a higher percentage of bare soil
Regions identified as persistently overperforming tended to have a lower percentage of bare soil
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Owyhee rangeland condition and trends
Ecosystem performance anomaly map for 2000-2008
Trend map displays the trend at different levels of significance
Land Cover R2
Big Sage 0.83
Grass 0.90
Low Sage 0.81
Other Veg 0.71
Purshia 0.79
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Owyhee 2040 Big Sage productivity estimates (percent of current productivity)
Big Sage model applied to a near-term future climate projection
Data from National Center for Atmospheric Research (model CCSM3, moderate emission scenario-A1b)
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Sagebrush 2006 performance anomalies for the northern part of the Upper Colorado River Basin
Four rangeland types were modeled and mapped but only the Big Sage is shown
Overperform
Normal
Underperform
Land Cover R2
Grass 0.97
Big Sage 0.94
Pinion Juniper 0.94
Salt Scrub 0.89
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Land Cover R2
Grass 0.86
Platte Basin grass anomalies: implications for Switchgrass biofuel expansion
Applied to grass areas
Applied to crop areas
Crop areas which maybe more productive as grassProductive, good condition grasslands
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Investigating variations in the weather axis
Difference between the weather-based (predict) GSN and the GSN site potential map for Big Sagebrush(2006)
USGS VegDRI map (June to September) U.S. drought monitoring map (average conditions between June and September, 2006)
0
20
40
60
80
100
120
0 20 40 60 80 100 120
Site Potential
Es
tim
ate
d G
row
ing
Seaso
n N
DV
I
WetDroughtNormal1:1 line
Upper Colorado River Basin (2005-2007) for big sage
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Summary
This study accounts for interannual weather effects on vegetation so that trend and persistence analysis are consistent
It provides land managers rangeland histories and trends
Such studies help optimize field visits and range restoration
They help put current studies into longer perspectives (historical and future)