CHRISPROBA Workshop Noordwijk, Netherlands, April 34, 2003

1
CHRIS/PROBA Workshop Noordwijk, Netherlands,
April 3-4, 2003

• Estimating land surface variables from CHRIS at
  Arizona, USA
• Shunlin Liang, Ph.D
• Department of Geography
• University of Maryland at College Park, USA

2
Funded Project

• Establising a basis for carbon management policy
  at the sate level Carbon dynamics at site,
  landscape, and regional scales for arizona sate
  lands led by Prof. C. Hutchinson
• Funded by NASA Carbon Cycle Program

3
Objectives

• assess carbon sequestration potential on state
  trust lands, as well as how that potential might
  vary under different management regimes, and
  during periodic climate variations
• assess potential economic return to the state
  that might derive from a carbon sequestration
  program, and a comparison of those to current
  returns
• assess potential monitoring systems that might be
  implemented by Arizona State Land Department
  (ASLD) for contract performance verification on
  any carbon sequestration project.

4
Calibrated TOA radiance
Atmospheric correction

Surface spectral reflectance
Inversion algorithms
Broadband albedos
LAI
5
Atmospheric correction

• Liang S., H. Fallah-Adl, S. Kalluri, J. JaJa, Y.
  Kaufman, and J. Townshend, Development of an
  Operational Atmospheric Correction Algorithm for
  TM Imagery, Journal of Geophysical Research -
  Atmosphere, 10217173-17186, 1997.
• Liang, S., H. Fang, M. Chen, Atmospheric
  correction of Landsat ETM imagery, I. Method,
  IEEE Trans. Geos. Remote Sens.,392940-2948, 2001
• Liang, S., H. Fang, J. Morisette, M. Chen, C.
  Walthall, C. Daughtry, and C. Shuey, Atmospheric
  correction of Landsat ETM imagery, II.
  Validation and applications, IEEE Trans. Geos.
  Remote Sens., 402736-2746, 2002

6
ETM atmospheric correction
7
MODIS imagery of Chinese northeastern coast, May
7, 2000
8
Broadband albedo estimation
Atmospheric correction
BRDF modeling
Raw data
Narrowband to broadband albedo conversion
Broadband albedos
Conventional
Alternative
9
broadband albedo

• Conventional Method
• Liang, S., Narrowband to Broadband Conversions of
  Land Surface Albedo. I.Algorithms, Remote Sensing
  of Environment,76,218-238, 2001
• Liang, S., C. Shuey, A. Russ, H. Fang, M. Chen,
  C. Walthall, C. Daughtry, and R. Hunt, Narrowband
  to broadband conversions of land surface albedo.
  II. Validation, Remote Sensing of Environment,
  84(1)25-41, 2003.
• An alternative solution
• Liang, S., A direct algorithm for estimating land
  surface broadband albedos from MODIS imagery,
  IEEE Trans. Geosci. Remote Sen., 41(1)136-145,
  2003.

10
LAI Inversion algorithms

• Liang, S., H. Fang, M. Kaul, T. Van Niel, T.
  McVicar, J. Pearlman, C. Walthall, C. Daughtry,
  F. Huemmerich, (2003), Estimation of land surface
  broadband albedos and leaf area index from EO-1
  ALI data and validation, EO-1 special issue of
  IEEE Transactions on Geoscience and Remote
  Sensing, in press.
• Fang, H. and S. Liang, (2002), "Retrieve LAI from
  Landsat 7 ETM Data with a Neural Network Method
  Simulation and Validation Study," IEEE
  Transactions on Geoscience and Remote Sensing, in
  press.
• Fang, H. and S. Liang, (2002), Retrieving Leaf
  Area Index (LAI) Using a Genetic Algorithm with a
  Canopy Radiative Transfer Model, Remote Sensing
  of Environment, in press.

11
Hybrid inversion algorithm
Canopy radiative transfer simulations
Remote sensing data
Canopy soil parameters(e.g., LAI)
Canopy spectral reflectance
Atmospheric correction
Nonparametric regression
Surface reflectance
LAI products
12
(No Transcript)
13
Two test sites

• These two sites selected to document the impact
  of differing intensities of grazing and climate
  variability that can be linked to changes in
  carbon storage rates are in different rangeland
  settings (1) Sonoita plains grassland, and (2)
  Santa Rita semidesert grassland.
• These two settings differ considerably and
  represent a range of conditions typical of lands
  managed by ASLD. Both have areas that have been
  protected for at least 25 years. At each
  location, we have established one site within a
  protected area, and another on an adjacent area
  that has been grazed.

14
(No Transcript)
15
Santa Rita Semidesert Grassland Sonoita
Plains GrasslandSouthern Arizona
16
Santa Rita Semidesert Grassland Sonoita
Plains GrasslandSouthern Arizona
17
Santa Rita Semidesert Grassland Sonoita
Plains GrasslandSouthern Arizona
18
Santa Rita Semidesert Grassland Sonoita
Plains GrasslandSouthern Arizona
19
Thank you !