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MoistureMap: Mixed-pixel Retrieval . Ye Nan Master of research University of Melbourne Jeffrey Walker, Dongryeol Ryu, Christoph Rüdiger, Robert Gurney, Edward Kim, Yann Kerr. Heterogeneity in SMOS resolution pixel. NAFE’06 Study Area-Kyeamba catchment. Urban area. Bare soil. Standing water.

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slide1

MoistureMap: Mixed-pixel Retrieval

Ye NanMaster of researchUniversity of Melbourne

Jeffrey Walker, Dongryeol Ryu, Christoph Rüdiger, Robert Gurney, Edward Kim, Yann Kerr

heterogeneity in smos resolution pixel
Heterogeneity in SMOS resolution pixel
  • NAFE’06 Study Area-Kyeamba catchment

Urban area

Bare soil

Standing water

Forest

50km

Crops

Grass

50km

world wide problem
World-wide Problem

Xinjiang, China

South Paris, France

Pennsylvania, USA

effect of mixed pixels
Effect of mixed-pixels

The heterogeneity of pixels reduce the accuracy of SMOS soil moisture retrieval

  • “as little as 3% standing water coverage leads to more than 4%v/v error in derived soil moisture – the target accuracy for SMOS soil moisture retrieval“
  • [Walker et al., 2006]
project target and proposed approach
Project target and proposed approach
  • Simulating the surface types emission contributions on overall SMOS microwave response

Brightness temperature map

Area distribution pie map

proposed approaches
Proposed Approaches

Land-use

Forest

SMOS

Urban

Rocks

Water

LAI_max

Tau-Omega model

Klein, Stogryn, Debye

represents different surface

Bare soil, Crops and Grass

test field
Test field

Goulburn River catchment

NAFE’05 data set

test field8
Test field

Yanco area

NAFE’06 data set

test field9
Test field

Kyeamba catchment

NAFE’06 data set

research direction
Research direction
  • Develop the approaches to simulate microwave radiation of standing water, rocks and urban area.
  • Evaluate the effect of forest, standing water, rocks and urban area on overall brightness temperature.
  • Establish the mixed-pixel model to retrieve soil moisture from SMOS data.
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