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NASA’s: Science Data Purchase

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NASA’s: Science Data Purchase

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NASA’s: Science Data Purchase

IKONOS, ETM, MODIS NDVI: comparison

Jeff Morisette, MODLAND, SSAI

Positive Systems for Appalachian Transect

Rob Sohlberb, MODLAND, UMd

Report from Stennis Space Center on SDP validation activities

Mary Pagnutti, SSC

One Ikonos DEM/Stereo Pair for Barton Bendish site

J. Peter Muller, MODLAND, ULC

One approach to scaling

Comparing

ETM+, IKONOS, and MODIS NDVI products

Framed in the context of statistical hypothesis testing

J. Morisette

Field data

“Tasked” acquisitions:

Airborne and high res. Satellite

Automatic acquisitions:

reference data and products to be validated

Point

Fine resolution

Fine resolution

Compare:

Need to consider all three elements as samples from unknown distributions, use each component to estimate the respective distribution, and compare distributions

- points to pixels
- parameters and distributions
- relationships
- surfaces

Spectral Bands, Red and NIR

AVHRR

grass reflectance*

MODIS

ETM+

IKONOS

Difference may be important: Gitelson and Kaufman, 1998; Bo-Cai Gao, 2000;

which compared MODIS to AVHRR and found large differences in NDVI

*ASD spectrum from grass area near GSFC

Study Area: Konza Prairie

Data:

MODIS daily products: Sept. 11

500m surface reflectance

500m pointer file

1km viewing geometry

LDOPE tools to combine

(available through EDC EDG)

ETM+, Sept. 11

IKONOS, Sept. 15

Aeronet (Meyer)

(available through Konza Prairie Core Site web page)

Vermote et al.’s Six S code

(for ETM+ and IKONOS)

IKONOS area on MODIS 500mand ETM+

Subset area in Sinusoidal Projection

Sampling with MODIS “Tile Mapper”

Done for both IKONOS and ETM+

ETM+

IKONOS (30m)

Comparison at Multiple-scales

ETM+

14, 16

n=224

Considering all three as variable and subject to errors, consider MODIS pixel relative to the distribution from the higher resolution data

MODIS

Pixel 1, 1

IKONOS

116, 120

n=13,920

IKONOS vs ETM+

Correlation = .5639

Reject hypothesis of zero correlation

Using standard Pearson method (p value ~0)

IKONOS vs MODIS

Correlation = .3114

Reject hypothesis of zero correlation

Using standard Pearson method (p value ~0)

ETM+ vs MODIS

Correlation = .3401

Reject hypothesis of zero correlation

Using standard Pearson method (p value ~0)

Do the data follow a normal distribution?

Null Hypothesis: Normally distributed

Test: Kolmogorov-Smirnov Goodness-of-Fit Test:

MODIS data: Reject (p = .0079)

ETM+ at 500m: Reject (p = .0004)

IKONOS at 500m: Reject (p ~ 0)

ETM+: Reject (p ~ 0)

IKONOS at 30m: Reject (p ~ 0)

So, should consider testing correlation with non-parametric methods.

Non-parametric correlation

Null Hypothesis: Zero Correlation

Test: Spearman's rank correlation

IKONOS vs ETM+:Reject (rho = .5791, p ~ 0) (corr = .5639)

IKONOS vs MODIS: Reject (rho = .3099, p ~ 0) (corr = .3114)

ETM+ vs MODIS: Reject (rho = .3362, p ~ 0) (corr = .3401)

But we still might want to question the hypothesis being tested.

Test for Paired Differences

Null Hypothesis: average paired difference is zero

Test: T test (assume normality and homogeneity of variance)

Test: Wilcoxon Rank Sum Tests

IKONOS vs ETM+

IKONOS vs MODIS Reject all three pair-wise combination

ETM+ vs MODIS based on either test.

So, for these data we are somewhere in the middle:

There is positive correlation,

but the average difference is not zero

Normalized differences to include variability in validation data

MODIS – IKONOS(average)

= “z score”

Std. Dev (IKONOS ave.)

Z score analysis

IKONOS vs ETM

Z score analysis

IKONOS vs MODIS

Z score analysis

ETM vs MODIS

Do the z-scores follow a normal distribution?

Null Hypothesis: Normally distributed

Test: Kolmogorov-Smirnov Goodness-of-Fit Test:

Z from IKONOS vs ETM+:Reject (ks = 0.1955, p ~ 0)

Z from IKONOS vs MODIS: Reject (ks = 0.0537, p = 0.0142)

Z from ETM+ vs MODIS: Reject (ks = 0.0538, p = 0.013)

So, should consider testing z-scoresw with at least both parameteric

and non-parametric methods

Test of z-score “centered” on zero

Non-Parametric

Null Hypothesis: Median value is zero

Test: Wilcoxon Signed Rank Sum Tests

Z from IKONOS vs ETM+:Reject (Z =-46.493, p ~ 0)

Z from IKONOS vs MODIS: Reject (Z = -9.9305, p ~ 0)

Z from ETM+ vs MODIS: Reject (Z = -6.2677, p ~ 0)

Parametric

Null Hypothesis: Mean value is zero

Test: T test

Z from IKONOS vs MODIS: Reject (t = -10.143, p ~ 0)

Z from ETM+ vs MODIS: Reject (t = -5.4727, p ~ 0)

Conclusions

- Assumption of normality is not always met
- Non-parametric methods are available
- Z-score method shows one possible way to scale up; which incorporates variability and considers the validation data with respect to its distribution
- There is a fundamental difference between the null hypothesis of the correlation being zero and the difference being zero
- There is closer statistical agreement between MODIS and either IKONOS and ETM+ than between IKONOS and ETM+
- There is a difference between statistical and practical difference

Comments

- ETM+, IKONOS, MODIS and Sun photometer data were easily available
- Major difficulty was ISIN projection and georeferencing – coordination of Jacqueline Le Moigne, GSFC might prove helpful.
- Results are planned to be communicated in the validation article in the Special Issue of RSE.