Use of Temporal Indicators for Invasive Plant Species in the USGSNASA Invasive Species Forecasting S

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Use of Temporal Indicatorsfor Invasive Plant
Speciesin theUSGS/NASA Invasive Species
Forecasting System 

• Jeffrey T. Morisette, Jeffrey A. Pedelty, James
  A. Smith, John L. SchnaseNASA Goddard Space
  Flight Center Thomas J. Stohgren Catherine
  CrosierUSGS National Institute of Invasive
  Species Science Jim Graham,Greg Newman,
  Mohammed A. Kalkhan, Robin ReichColorado State
  University
• ESA August 2004

2
Use of Temporal Indicatorsfor Invasive Plant
Speciesin theUSGS/NASA Invasive Species
Forecasting System 

• Jeffrey T. Morisette, Jeffrey A. Pedelty, James
  A. Smith, John L. SchnaseNASA Goddard Space
  Flight Center Thomas J. Stohgren Catherine
  CrosierUSGS National Institute of Invasive
  Species Science Jim Graham,Greg Newman,
  Mohammed A. Kalkhan, Robin ReichColorado State
  University
• ESA August 2004

3
Use of Temporal Indicatorsfor Invasive Plant
Speciesin theUSGS/NASA Invasive Species
Forecasting System 

• Jeffrey T. Morisette, Jeffrey A. Pedelty, James
  A. Smith, John L. SchnaseNASA Goddard Space
  Flight Center Thomas J. Stohgren Catherine
  CrosierUSGS National Institute of Invasive
  Species Science Jim Graham,Greg Newman,
  Mohammed A. Kalkhan, Robin ReichColorado State
  University
• ESA August 2004

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Federal Government Response

• National Invasive Species Council (EO 13122 -
  1999)
• USGS has a lead role in dealing with invasive
  species science in natural and semi-natural areas

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USGS / NASA InvasiveSpecies Partnership

• Launched two years ago
• One of NASAs twelveNational Applications
  areas
• Engineering, High-End Computing, EOS Data
• Activities involve
• USGS National Institute of Invasive Species
  Science
• NASA Goddard Space Flight Center
• And many others

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USGS Science / Client Needs

• On-demand, predictive landscape- and
  regional-scale models and maps for biological
  invasions
• Integrated access to tailored NASA data

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USGS Predictive Modeling
Output GIS - Spatial Statistical Dynamic Models
and Maps
Trend Surface Analysis With Stepwise Multiple
Regression Using OLS, GLS, SAR, or Exhaustive
Regression
Input Variables (150) Remotely Sensed
data (ETM, SPOT, MTI, EO1, etc.) Derived Remote
Sensing (Vegetation Indices, PCA Tasseled Cap,
other) Biotic/Abiotic Data Topographic
Data Species Data Vegetation- Forest Data Soils
Characteristics Cryptobiotic Crusts Wildfire
Severity Biodiversity Air Pollution Geology,
Other Environmental Data
Hot spots of native biodiversity Distribution
of non-native species Potential spread
of invasive species. Barriers to rapid
invasions. Corridors that may accelerate
invasions. Economic and environmental risk
assessments, vulnerability of habitats to
invasion. Priorities for control and
containment.
Testing if There Is Spatial Auto-Correlation In
the Residuals
No
Final Trend Surface Map Large - Small Scale
Variability
Yes
Testing if Residuals Cross-Correlated with Other
Variables
Yes
Yes
No
Model Residuals Using Co-Kriging
Regression Trees Classifications
Model Residuals Using Kriging (Universal,
Ordinary, other)
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Model Outputs
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USGS Predictive Modeling
Output GIS - Spatial Statistical Dynamic Models
and Maps
Trend Surface Analysis With Stepwise Multiple
Regression Using OLS, GLS, SAR, or Exhaustive
Regression
Input Variables (150) Remotely Sensed
data (ETM, SPOT, MTI, EO1, etc.) Derived Remote
Sensing (Vegetation Indices, PCA Tasseled Cap,
other) Biotic/Abiotic Data Topographic
Data Species Data Vegetation- Forest Data Soils
Characteristics Cryptobiotic Crusts Wildfire
Severity Biodiversity Air Pollution Geology,
Other Environmental Data
DSSProducts
Analysis Modeling
Hot spots of native biodiversity Distribution
of non-native species Potential spread
of invasive species. Barriers to rapid
invasions. Corridors that may accelerate
invasions. Economic and environmental risk
assessments, vulnerability of habitats to
invasion. Priorities for control and
containment.
Testing if There Is Spatial Auto-Correlation In
the Residuals
No
Final Trend Surface Map Large - Small Scale
Variability
Yes
Testing if Residuals Cross-Correlated with Other
Variables
Yes
Yes
Data Ingest
No
Model Residuals Using Co-Kriging
Regression Trees Classifications
Model Residuals Using Kriging (Universal,
Ordinary, other)
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Invasive Species Forecasting System
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Invasive Species Forecasting System
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Invasive Species Forecasting System

• OLS Regession Kriging
• Regression Tree Analysis
• GARP
• EcoNiche

• NIISS Tamarisk
• Phase 1 EOS
• NBII
• ESE

• T-Map

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Parallel Kriging
Goal 75 scaling efficiency on 200 node
cluster
http//ct.gsfc.nasa.gov/milestones.schnase.html
Analysis by Jeff Pedelty Jeff Morisette NASA
Goddard Space Flight Center
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MODIS NDVI Time SeriesCerro Grande Fire
Site(Spring 2000 Spring 2002)
Analysis by Jeff Morisette Jeff Pedelty NASA
Goddard Space Flight Center
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MODIS NDVI Time SeriesCerro Grande Fire
Site(Spring 2000 Spring 2002)
Red Average Green Amplitude Blue Phase Shift
Analysis by Jeff Morisette Jeff Pedelty NASA
Goddard Space Flight Center
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Current Statistical Modeling Array
Example Existing Model Array
Predictors f (observed values, satellite data
and/or anciallary data)
Field-measured variable of interest
GPS X and y coordinates used to extract
information from imagery and ancillary data
DEM Elevation, slope, Aspect
Landsat NDVI
Landsat Tasseled Cap bands 1-3
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Enhanced Statistical Modeling Array

• Predictor N

• Predictor 1

• response

• lon

• Lat

Example Proposed Model Array

• Xn1

• X11

• R1

• Y1

• X1

• Xn2

• X12

• R2

• Y2

• X2

Predictors f (observed values, satellite data
and/or anciallary data)
Field-measured variable of interest
Landsat NDVI
GPS X and y coordinates used to extract
information from imagery and ancillary data
DEM Elevation, slope, Aspect
Landsat Tasseled Cap bands 1-3
New explanatory variable
2001 2002
MODIS Summary Layers
MODIS Time series
Summary Method
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Satellite Coverage
Green 13 Landsat images covering the Colorado
River Blue 250m buffer on either side of the
Colorado River AREA Green 354K sq km Blue
3K sq km
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Use of Temporal Indicatorsfor Invasive Plant
Speciesin theUSGS/NASA Invasive Species
Forecasting System 
http//InvasiveSpecies.gsfc.nasa.gov

• Jeffrey T. Morisette, Jeffrey A. Pedelty, James
  A. Smith, John L. SchnaseNASA Goddard Space
  Flight Center Thomas J. Stohgren Catherine
  CrosierUSGS National Institute of Invasive
  Species Science Jim Graham,Greg Newman,
  Mohammed A. Kalkhan, Robin ReichColorado State
  University
• ESA August 2004