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

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Use of Temporal Indicators for Invasive Plant
Species in the NASA/USGS Invasive Species
Forecasting System 

• Jeffrey T. Morisette, John L. Schnase, Jeffrey A.
  Pedelty, James A. SmithNASA Goddard Space
  Flight Center Thomas J. StohgrenUSGS National
  Institute of Invasive Species Science Catherine
  Crosier, Jim Graham, Mohammed A. Kalkhan, Robin
  ReichColorado State University
• ESA, August 2004

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Outline

• Background
• monitoring species richness
• monitoring Tamarisk

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Collaborators(potential Proposal team members)
USGS/CSU Stohlgren, lead ISFS
collaborator Kalkhan, Reich statiatical
modeling Evangelista/Graham/Newman/Crossier/Davern
field data to ingest Other Universities Umaine
spatio-temporal helix modeling George Mason
University statistical analysis U.Alabama,
Huntsville Graves, expertise of Earth Science
data/metadata Agencies/NGO USDA, ARS
Hyperspectral airborne imagery over Tamarisk,
Curruthers, Delfouse USDA Forest Service, RSAC
and Colorado mapping pilot project,
Czaplewski Colorado DNR Colorado mapping pilot
project Tamarisk Coalition Bill Cheatum,
Tamarisk modeling NASA GSFCs Invasive Species
Forecasting System Schnase, Pedelty,
Smith Application Division Scheffner and
Turner Code 586, Bob Lutz and Mike
Seablom Stennis Space Center, McKellip
applications program, Griffith Tamarisk with
ASTER EO-1 team, Steve Ungar, Tom Brakke, Ken
McGwire ASTER team, Leon Maldanado, Tim Gubbles
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Objectives of Work
careful observation of current patterns of the
invasion of nonnative plant species in natural
landscapes might provide a reasonable staring
point for the design of more realistic
experiments and mathematical models, and in the
search of a generalized theory of
invasion. Stohlgren- director of the National
Invasive Species Science Center Beyond Theories
of Plant Invasions Lesson From Natural
Landscapes, Comments on Tehoretical Biology, 7
355-379, 2002. So Our current need is to figure
out where Invasives are and how they got thereso
we can figure out where they are going.
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Invasive Species Forecasting SystemScience Plan
Cheatgrass/Thistle
Tamarisk
Native/Non-Nativegrass
WoodyEncroachment
Aquatics
SpeciesRichness
ESA presentation Manuscript
Contribute to Grand Challenge
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Invasive Species Forecasting SystemScience Plan
Cheatgrass/Thistle
Tamarisk
Native/Non-Nativegrass
WoodyEncroachment
Aquatics
SpeciesRichness
ESA presentation Manuscript
Contribute to Grand Challenge
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Plan for species richness effort

• Build on USGS spatial modeling
• Exploit new NASA Earth Observing System imagery
  and data products to improve predictions
• Extend results to larger areas

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Input data Soil properties

• Importance
• Species habitat requirement
• Determinant of species range boundaries,
  corridors of invasion, dispersal patterns
• Current Sources
• Type STATSGO, local soil maps Moisture
  passive microwave, radar, and NIR
• Sources
• USGS STATSGO
• http//water.usgs.gov/lookup/getspatial?ussoils
• Currently hold twenty soil properties raster
  layers at 30m spatial resolution for all of
  Colorado

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Input data Elevation, slope and aspect

• Importance
• Determinant of species range boundaries,
  corridors of invasion
• Influences hydrological, geological, and human
  processes
• Current Sources
• GTOPO 30 GLOBE 30 arcsec/100m USGS/European
  regional models US DEM
• Future Sources
• SRTM (global) 30m H/30m V High-resolution LIDAR
  Military DTED2 (global)
• Currently hold Shuttle RADAR Topography Mission
  (SRTM) digital elevation data, at 30m spatial
  resolution mosaicked and clipped to the Colorado.
• Source USGS
• http//seamless.usgs.gov/

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Input data Vegetation signal

• Importance
• Vegetation structure the habitat parameter for
  many species
• Structural complexity major driver of species
  richness in all environments
• Current Sources
• Visible/Infrared ETM, MODIS
• SAR - Estimates of canopy texture, biomass,
  geometry AVHRR NDVI
• Future Sources
• LIDAR
• Vis/IR - ASTER
• Currently hold 4 Tasseled-Cap NDVI layers from
  Landsat-7 ETM (2000) for Colorada

Airborne LIDAR
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Input data Phenology

• Importance
• Plant phenology an important driver for animal
  species
• Many change habitats to track available resources
• Current Sources
• Multispectral imagery
• 30m resolution several times per year250m
  resolution daily
• Future Sources
• Higher temporal resolution multi-spectral
• Satellite-borne hyperspectral
• Meterological data
• Currently hold MODIS Vegetation Index (VI)
  product (MOD13--16-day composite with 250m
  spatial resolution, ver. 004) for four years
  (Feb. 2000 to present) for three study sites and
  all of Colorado

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Graphic provided by NASAs Scientific
Visualization Studio
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Statistical modeling results

• Preliminary, yet
• for all three initial study areas
• Rocky Mountain National park
• Cerro Grande Fire site
• Grand Staircase/Escalante National Monument
• considering a suite of regression modeling
  techniques
• Ordinary least squares Generalize least squares
• Quadratic terms
• Interaction terms
• Stepwise regression selection
• MODIS summary variables are statistically
  significant and contribute to the model.

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Preliminary conclusions on Species Richness

• The temporal patterns observed by the MODIS times
  series make a statistically significant
  contribution to the prediction of total plants
• Existing data sets within the ISFS can be used to
  extend the results to larger areas

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Invasive Species Forecasting SystemScience Plan
Cheatgrass/Thistle
Tamarisk
Native/Non-Nativegrass
WoodyEncroachment
Aquatics
SpeciesRichness
ESA presentation Manuscript
Contribute to Grand Challenge
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Brief Background Tamarisk

• deep root system (up to 100 feet)
• increases soil salinity
• displace native cottonwoods and willows as well
  as adjacent upland plant communities
• degrades habitat for livestock, animals, and
  birds
• increases fire hazards
• limits human use of the waterways
• STEALS WATER by using more water than native
  vegetation that it displaces
• limited water resources dries up springs,
  wetlands, and riparian areas by lowering water
  tables
• non-beneficial consumption of water by tamarisk
  throughout the West ranges from 2.0 to 4.5
  million acre-feet of water per year, above and
  beyond what the native riparian vegetation would
  have consumed, representing enough water to
  supply upwards of 20 million people or the
  irrigation of over 1,000,000 acres of land. And
  every year, the problem only continues to get
  worse
• http//www.tamariskcoalition.org

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Plan of work for Tamarisk(in progress)

• Build on existing remote sensing Tamarisk
  monitoring
• Collect hand held spectra, weekly digital photos,
  and multi-resolution, multi-temporal observation
  for large Tamarisk stands through the 2004
  growing season
• Determine most efficient operational monitoring
  of Tamarisk infestation which may be a specific
  airborne sensor flown during one or more specific
  phenological conditions

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Existing Hyperspectral Results

• Results from Ken McGwire/EO-1 Validation team
• Discriminate Function Analysis worked best
• Selective Use of Spectral Bands is possible,
  but specific band TBD

AVIRIS Hyperion

• Source www.eoc.csiro.au/hswww/oz_pi/svt_hilo/kcmc
  guire.pdf

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Existing Airborne Multi-spectral Results
Crossing line Indication of temporal
signature
Reflectance of Riparian Vegetation at 550nm
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10
8
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Reflectance
4
2
0
June
May
Sept
August
Jan-Feb
November
Green
Red
Near Infrared
From Everitt, J. H., C. J. Deloach. 1990.
Remote Sensing of Chinese Tamarisk (Tamarix
chinensis) and Associated Vegetation. Weed
Science. 38273-278.
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Current StudyFour Tamarisk study sites
Water 0 - .1 .1 - .2 .2 - .5 .5 - .7 .7 1.0

• Background image June 26, 2003 MODIS Enhanced
  Vegetation Index taken from 4 year contiguous US
  coverage created by MODAPS and stored in the ISFS

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Field spectrum Sept 03 July 04
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Weekly photos Mid June 2004
Water 0 - .1 .1 - .2 .2 - .5 .5 - .7 .7 1.0
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Imagery

• ASTER(imagery and DEMs)
• EO-1
• Ikonos
• HyperspectralAirborne

May 18th, 2004 Debeque ASTER scenefalse color
NIR, 3x DEM vertical exaggeration
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Satellite Coverage issue
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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Preliminary conclusions on Tamarisk

• Temporal and Spatial resolution is critical
• Need to catch infestation early (small stands)
• Detectability influenced by phenology and stand
  size
• Multi-spectral imagery should suffice, but with
  specific bands (optimal bands need to be
  selected)
• Synoptic, watershed-wide, image acquisition is
  difficult with satellite imagery
• Tamarisk airborne sensing system may be worth
  exploring