Medhavy Thankappan - Harmonic analysis of timeseries MODIS vegetation index data for monitoring winter crops in the Wimmera-Mallee region of Victoria

Harmonic analysis of time-series MODIS vegetation index data for monitoring winter

crops in the Wimmera-Mallee region of

14th Australasian Remote Sensing & Photogrammetry Conference, Darwin 29 Sep – 3 Oct 2008

crops in the Wimmera-Mallee region of Victoria

Medhavy Thankappan1, Kenton Lawson2, Shanti Reddy1 and Phil Kokic2

1Geoscience Australia2Australian Bureau of Agricultural and Resource Economics

Acknowledgments

Geoscience Australia

Lan-Wei Wang

Bill Levett

Anis Islam

Alan Forghani

APSRU DPIF-QLD

Andries Potgieter

NLR Netherlands

Wout Verhoef

Albert van der Kamp


Alan Forghani

ABARE

Chun Liang

Milly Lubulwa

Albert van der Kamp

Agricultural Statistics

• Crop type, area & production: Ag Census and Survey (ABS), Farm surveys (ABARE)

• NAMS, SPREAD II: regional ag. land use mapping with satellite derived information and ABS statistics (BRS)

• Pastures from Space (CSIRO, WA Agric,


• Pastures from Space (CSIRO, WA Agric, Landgate)

• RCFS: shire-wise yield model for wheat and sorghum (QDPI&F)

• GAP: near-real-time crop-specific area and pre-harvest or in-season production estimates not available

Method

Study Area• Mallee and Wimmera Statistical Divisions comprising 16 SLAs in north western Victoria

• Predominantly agricultural, cereal crops, legumes and oilseeds

RS / Ancillary Data


RS / Ancillary Data• 16-day composite MODIS EVI at 250 m (2000 – 2006)• Land-use and very limited ground truth

Approach• HANTS-Harmonic ANalysis of Time Series (each crop year)• Non-agricultural pixels (water bodies / forests) masked• Unsupervised classification of HANTS outputs (ISOCLASS)• Aggregation of crop class area at SD and SLA levels

Study Area (Mallee & Wimmera SDs)


Harmonic Analysis

• Decomposes periodic phenomena into a series of functions (terms)

• Each term is defined by a unique amplitude / phase value

• Identification of land cover types is possible using values of

Amplitude

Phase

002π2π

Seasonal VI series

Time


is possible using values of phase, amplitude & additive term

Am

plitu

de

Re

sc

ale

d V

I

0 + 1

0 + 1 + 2

0 + 1 + 2 + 3

Adding successive terms to produce final curves

Decomposition of VI series into component terms

Why Harmonic Analysis?

• Vegetation exhibits distinctive seasonal patterns of variation with periodic characteristics

• Potential for significant data reduction (time-series)

• Not biased by data set (size, range or


• Not biased by data set (size, range or dominance of spectral features

• Acts as a noise filter for non-periodic influences introduced by processing or cloud

• Has been applied successfully to land-use / land cover studies including crops

HANTS Outputs A1A1

A2A2 P2P2

P1P1

A0A0


P3P3A3A3

Raw versus HANTS VI Profiles

0

1000

2000

3000

4000

5000

6000

7000

1 3 5 7 9 11 13 15 17 19 21 23

EV

I

Wheat


1 3 5 7 9 11 13 15 17 19 21 23

16-day period

0

500

1000

1500

2000

2500

3000

3500

4000

4500

1 3 5 7 9 11 13 15 17 19 21 23

16-day period

EVI

Original

HANTS

Field Peas

HANTS Partial Variance 2004


Am

plitu

de

1st term 2nd term 3rd term

HANTS Partial Variance 2004


Am

plitu

de

1st term 2nd term 3rd term

Clustering HANTS outputs


Results : Statistical Divisions (2000 - 2005)Mallee Statistical Division

0

200

400

600

800

1000

1200

1400

1600

2000 2001 2002 2003 2004 2005

Win

ter

Cro

p A

rea (

'000 h

a)

Wimmera Statistical Division

0

200

400

600

800

1000

1200

1400

1600

2000 2001 2002 2003 2004 2005

Win

ter

Cro

p A

rea (

'000 h

a)

MODIS-HANTS

ABS (crops)

ABS (+ pasture)


Crop Year Crop Year

Relative deviations are generally higher in Mallee for all years

The largest RD for Mallee (22.9%) and Wimmera (16.7%) was observed in 2000 (smaller time series?)

0

50

100

150

200

250

300

350

400

SLA

Win

ter

Cro

p A

rea (

'000 h

a)

ABS Ag Census

MODIS-HANTS

400

450

500

Win

ter

Cro

p A

rea (

'000 h

a)

2000

Results : SLAs (2000 & 2005) • Relative deviations for SLAs are higher (than SD) for both 2000 and 2005


0

50

100

150

200

250

300

350

400

Bu

loke N

ort

h

Bu

loke S

ou

th

Gan

naw

arr

a

Hin

dm

ars

h

Ho

rsh

am

Bal

Ho

rsh

am

Cen

tral

Mild

ura

Pta

Mild

ura

Ptb

NG

ram

pia

ns S

tArn

au

d

NG

ram

pia

ns S

taw

ell

Sw

an

hill B

al

Sw

an

hill C

en

tral

Sw

an

hill R

ob

invale

West

Wim

mera

Yarr

iam

bia

ck N

ort

h

Yarr

iam

bia

ck S

ou

th

SLA

Win

ter

Cro

p A

rea (

'000 h

a)

2005

• MODIS HANTS crop area estimates higher than ABS for most SLAs

SD25 (Wimmera)1,346,793 ha 1,187,276 ha 13.4

SD30 (Mallee)1,260,091 ha 11.9

7.8

1,125,256 ha

1,168,633 ha*

Summary Results Winter Crop Area 2000

ABS Ag Census 2001 RD (%)


1,346,793 ha 1,187,276 ha

1,238,317 ha*13.48.7

SD30 + SD252,606,884 ha 12.7

8.3

*Crops for pasture and hay included

2,312,532 ha

2,406,950 ha*

SD25 (Wimmera)1,222,260 ha 1,125,041 ha 8.6

SD30 (Mallee)1,312,896 ha 7.6

3.7

1,220,517 ha1,265,171 ha*

Summary Results Winter Crop Area 2005

ABS Ag Census 2006 RD (%)


1,222,260 ha 1,125,041 ha1,201,299 ha*

8.61.7

8.12.8

2,345,558 ha2,466,470 ha*

SD30 + SD252,535,156 ha

*Crops for pasture and hay included

Summary of Key Findings

• Winter crop area results for Mallee and Wimmera SDs comparable to ABS estimates, potential of HA for time series applications involving crop monitoring

• Significant reduction of time-series data volumes


• Significant reduction of time-series data volumes and noise, better classification results using EVI compared to NDVI

• Application areas that could benefit from HA include land-use / land-cover mapping

Thank you Questions ?


Questions ?

Documents

Medhavy Thankappan - Harmonic analysis of timeseries MODIS vegetation index data for monitoring winter crops in the Wimmera-Mallee region of Victoria