Xin Li (PI), Yong Ge, Rui Jin, Shaomin Liu, Mingguo Ma, Wenzhong Shi, Rongxing Li, Qinhuo Liu, Shuguo Wang

CAREERI/CAS, IGSNRR/CAS, IRSA/CAS, BNU, WHU, TJU

Presented by Tao Che

January 30, 2014LPVE, ESRIN

Development and Experimental Verification

of Key Techniques to Validate Remote

Sensing Products

Why new validation techniques ? Introduction of the project on the vali

dation of remote sensing products Validation experiment in HiWATER

Outline

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1 Why new validation techniques ?  

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西西西 西西西西 西西 西西 西西 西西 西西0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.12

0.05

0.36

0.06 0.05

0.15

0.05

AMSR-E soil moisture products

de Jeu, et al., 2008; Su, et al., 2011

Considerable uncertainties in remote sensing products

Region Land typeUncertainties of MODIS

LAI products

IGBP Kalaharisampling strips

Woodland Fairly consistence

Savanna Fairly consistence

Finland Coniferous forest Accuracy is 48%

France Agriculture 20% error

Africa Savanna 2-15% overestimation

India AgricultureBhopal, RMSE 0.92-1.26;

Indore, RMSE 0.20-0.33

BOREAS Coniferous forest 33% overestimation

Hanjiang River Basin

Agriculture, broad-leaved forest, coniferous forest, grassland

10% underestimation

Heihe River Basin

Broad-leaved forest, shrub, coniferous forest

58% underestimation

RM

SE

(m3/

m3

)

Crop

Crop

GrasslandCrop Crop

Grassland

Grassland

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First example: LAI

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LAI is defined as the one-sided green leaf area per unit ground surface area (LAI = leaf area / ground area, m2 m-2) in broadleaf canopies.

Is sampling of LAI easy?(Hufkens et al., 2008, validation experiment in Ejin, northwest China)

Assume point measurement of LAI is reliable (unbiased).Quasi-homogeneous surface: LAI = 0.3

First sampling: FVC = ~0.40 LAI = ΣLAIi / (number of samples) = 0.069 LAIf = LAId × FVC = 0.12

Heterogeneous surface LAI = ΣLAIi / (number of samples) = 0.31if we know the coverage of vegetation (FVC) FVC = ~0.06 LAIf = LAId × FVC = 0.24

Second sampling: FVC = ~0.35 LAI = ΣLAIi / (number of samples) = 0.18 LAIf = LAId × FVC = 0.105

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What are the implications ?

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• Sampling and scaling strategies have great impacts on the estimation of ground truth.

• We were using existing sampling protocol such as VALERI, which could be wrong and ambiguous.

• For heterogeneous land surface, pattern plays an important role. It must be considered in designing sampling.

• More reliable, robust, and rigorously mathematically defined sampling protocol should be developed.

Sampling strategy used in VALERI

Second example: soil moisture

Volumetric water content, is defined mathematically as:

Vw: volume of water; Vs: soil volume; Va: air space.

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Is sampling of soil moisture easy?

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Tibetan Plateau

Yang et al., BAMS, 2013

What are the implications ?

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• Point observation is most likely not a

representative value of pixel/footprint scale truth.

• Sampling for a coarse-scale pixel is a very

challenging work. It may cost a lot of labor and

money so more efficient method is needed.

• Representativeness error should be quantified.

• More reliable, robust, and rigorously

mathematically defined sampling protocol should

be developed.

We need new specifications and techniques for the validation of remote sensing product

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2 The project  on the val idation of remote sensing products  

Validation project

• Ministry of Science and Technology of China

(MOST) launched a high-tech R&D Program

(863) named ‘Development and experimental

verification of key techniques to validate rem

ote sensing products’ in 2011.

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Objectives

• To build technical specifications for the validation o

f remote sensing products.

• To carry out comprehensive remote sensing experim

ents on ‘truth’ collecting and new validation techniq

ue testing and to verify the applicability of the techn

ical specifications.

• To establish a network in China for routine validatio

n of remote sensing products.

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Targeting variables/products

• Ecology and carbon cycle (9): vegetation type, vegetation index, LAI, FPAR,

fraction of vegetation coverage, leaf chlorophyll content, phenology, GPP,

NPP

• Water cycle (5): precipitation, ET, soil moisture, snow water equivalent, snow

cover area

• Radiation and energy balance (11): aerosol optical depth, albedo, land

surface temperature, reflectivity, downward shortwave radiation, downward

longwave radiation, PAR, net radiation, sensible heat flux, soil heat flux,

aerodynamic roughness.

• Remote sensing image: Geometric accuracy of ZY-3 and other super high

resolution images.

• Polar remote sensing products: grounding line, ice edge, mass balance of ice

sheet.

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Best unbiased prediction of ground truth at pixel scale

Objective function

ℜ

yi

ℜ

yhi

ℜh=1

ℜh=2

ℜh=3

To obtain best and unbiased pixel-scale ground truth in terms of spatial representativeness ba

sed on the mean of surface with non-homogeneity (MSN) spatial sampling optimization schem

e.

Key scientific question: sampling and estimation for heterogeneous surface 

Weighted sample value

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∫ℜ

−ℜ ℜ= dssyY )(1

)()( st. ][)(min 2ℜℜℜℜℜ =−= YEyEYyEyv

∑=

ℜ =n

iii ywy

1

∑ ∫=

ℜ

−−

ℜℜℜ=

H

hhh

h

dssy1

11 )( ∑ ∑= =

=H

h

n

ihihih

h

ywa1 1

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Proposed network for the validation of remote sensing products

3 Testing new techniques and new specif ications  in HiWATER

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Hi-WATER

An observation matrix to capture the land surface heterogeneity

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SoilNet

WATERNet

LAINet

Li et al. BAMS, 2013

More information: hiwater.westgis.ac.cn/english/Li et al., 2013. HiWATER: Scientific objectives and experimental desig

n. BAMS.

Summary

Currently most of the validation protocols are intuitional, lacking of theoretic foundation.

Obtaining pixel/footprint scale truth is a great challenge. True value is defined as a best unbiased estimation at footprint scale.

New specifications, new sampling and scaling transformation methods should be developed.

Large scale ground observation techniques such as WSN, LAS, eddy covariance system, cosmic ray probe are emerging new hard techniques in the validation of remote sensing products.

More reliable, robust, and rigorously mathematically defined sampling protocol should be developed.

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Thank you !

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