7/24/02 MODIS Science Meeting Seasonal Variability Studies Across the Amazon Basin with MODIS...

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7/24/02 MODIS Science Meeting Seasonal Variability Studies Across the Amazon Basin with MODIS Vegetation Indices Alfredo Huete 1 , Kamel Didan 1 , Piyachat Ratana 1 , Laerte Ferreira 2 , Yosio Shimabokuro 3 , Tomoaki Miura 1 Gao Xiang 1 MOD13 *Terrestrial Biophysics and Remote Sensing Lab University of Arizona 1 University of Arizona, Tucson, Arizona USA 2 Universidade Federal de Goiás – UFG [email protected] 3 Instituto Nacional de Pesquisas Espaciais - INPE [email protected]

Transcript of 7/24/02 MODIS Science Meeting Seasonal Variability Studies Across the Amazon Basin with MODIS...

Page 1: 7/24/02 MODIS Science Meeting Seasonal Variability Studies Across the Amazon Basin with MODIS Vegetation Indices Alfredo Huete 1, Kamel Didan 1, Piyachat.

7/24/02 MODIS Science Meeting

Seasonal Variability Studies Across the Amazon Basin with

MODIS Vegetation Indices

Alfredo Huete1, Kamel Didan1, Piyachat Ratana1, Laerte Ferreira2, Yosio Shimabokuro3, Tomoaki Miura1

Gao Xiang1

MOD13

*Terrestrial Biophysics and Remote Sensing Lab University of Arizona

1University of Arizona, Tucson, Arizona USA 2Universidade Federal de Goiás – UFG [email protected]

3Instituto Nacional de Pesquisas Espaciais - INPE [email protected]

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Validation

• Validation concerns the outputs or the intended uses of the VI’s so as to help the user community understand the reliability, credibility, and limitations of the products.

MOD09 (SR)--->MOD13(VI)

Phenology (seasonality)

Change detection (Interannual)

Biophysical (growth models)

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MODIS Vegetation Indices

ARVIAtmosphere

Resistance

)Re(Re*)1(

LdNIR

dNIRL+ρ+ρ

ρ−ρ+

SAVI

Canopy BackgroundCorrection

Soil-adjusted Vegetation Index

NDVINormalized DifferenceVegetation Index

dNIR

dNIR

Re

Re

ρρ

ρρ

+

EVI

Enhanced Vegetation Index

)Re(

Re*21 blueCdCNIRL

dNIRGρρρ

ρρ

−++

)(

,

ReRe dbluedrb

rbNIR

rbNIR

ρ−ργ−ρ=ρρ+ρρ−ρ

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Year

1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

NDVI

0.2

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0.8

Caatinga Cerrado Dense Forest

Long term, time series AVHRR-NDVI data

(Pathfinder 8km -yearly averaged)

• Accurate and stable time series data is needed for studies on interannual variation of vegetation in response to climate and for characterization of vegetation anomalies at continental and regional scales.

Pinatubu

Sensor degradation

El Niño

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MONTH

JAN FEB MAR ABR MAY JUN JUL AUG SEP OCT NOV DEC

NDVI

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Caatinga (-9.41, -41.13)Cerrado (-10.80,-44.1)Dense Forest (-2.78,-54.27)

*20 year averaged monthly AVHRR - NDVI in Brazil (Pathfinder 8 km)

Seasonality & Phenology Role

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Objectives˚ Evaluate the initial two years of MODIS Vegetation

Index (VI) time series data over the Amazon Basin and surrounding regions of Brazil,

˚ Examine the usefulness of MODIS data in characterizing seasonality along a climate-based ecological transect from the Brazilian cerrado to the seasonal tropical rainforests,

˚ Examine the usefulness of MODIS data in discriminating land use/conversion patterns and in characterizing the resulting changes in seasonality.

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QuickTime™ and aGIF decompressor

are needed to see this picture.

MODIS EVI

Seasonality (2000-2002)

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0

0 .0 5

0 . 1

0 .1 5

0 . 2

0 .2 5

0 . 3

0 0 .2 0 . 4 0 .6 0 .8 1

E V I

Percent (%)

1 k m E V I

5 0 0 m E V I

2 5 0 m E V I

0

0 .1

0 .2

0 .3

0 .4

0 .5

0 .6

0 0 .2 0 .4 0 .6 0 .8 1

N D V I

Percent (%)

1 k m N D V I

5 0 0 m N D V I

2 5 0 m N D V I

EVI

NDVI

Histograms of VI’s at 250 m, 500 m, and 1 km resolutions

South America (August 12 to August 27, 2000)

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QuickTime™ and aGIF decompressor

are needed to see this picture.

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Brasilia National Park

• Blue = ASD

•Yellow = DigitalImages

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MQUALS and MODIS(Global)

MQUALS Reflectances

0.0 0.1 0.2 0.3 0.4

MODIS Composite Reflectances0.0

0.1

0.2

0.3

0.4

JornadaWalnut GulchCerradoTapajos

Blue Red NIR

MQUALS VI

0.0 0.2 0.4 0.6 0.8 1.0

MODIS Composite VI

0.0

0.2

0.4

0.6

0.8

1.0

JornadaWalnut GulchCerradoTapajos

NDVI EVI

MO

DIS

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EVI

EVI Histogram of Brasilia Tile (Cerrado + conversions)

Dry

8/00

8/01

Wet

3/02

4/01

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Cerrado physiognomies

0.0000

0.1000

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0.6000

8/29/009/29/0010/29/0011/29/0012/29/00

1/29/012/28/013/29/014/29/015/29/016/29/017/29/018/29/019/29/0110/29/0111/29/0112/29/01

1/29/02

DOY

EVI

Cerrado grass1

Shrub cerrado1

Wood Cerrado2

Cerrado wood3

Gallery Forest1

Pasture1

Cerrado Physiognomies

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Cangaçu & Santana do Araguaia

• Red = ASD

•Yellow = DigitalImages

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MODIS VI Seasonal Profiles of Land Converted Areas

biomass: 147.16 to 205.29 t / haLAI: 5.61 to 7.06

biomass: ~1.3 t / haLAI: ~2.82

biomass: 6.85 to 134.94 t / haLAI: 4.11 to 6.27

Primary Forest (“High”) Pasture site

Regeneration site

MODIS 250m EVI

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0

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Cerrado

Forest

Converted Pastures

Land Conversion at Santana do Araguaia & Cangaçu (Forest - Cerrado

Transition)

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Dry

11/00

11/01

Wet

7/01

4/02

0.00 0.20 0.40 0.60 0.80 1.00

EVI

EVI Histogram of Tapajos Tile (Seasonal Forest)

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Forest (Tapajos) 3x3

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Mar-00 Jun-00 Sep-00 Dec-00 Apr-01 Jul-01 Oct-01 Jan-02

EVI

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Litterfall Seasonal Dynamics (Tapajos)

(Woods Hall/ LBA/ <ftp://ftp.as.harvard.edu/pub/tapajos/>)

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Pasture sites near Tapajos

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23-Jun-00 1-Oct-00 9-Jan-01 19-Apr-01 28-Jul-01 5-Nov-01 13-Feb-02 24-May-02

Vegetation Index

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0.00

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0.60

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0.80

0.90

1.00

Mar-00 Jun-00 Sep-00 Jan-01 Apr-01 Jul-01 Oct-01 Feb-02

NDVI

Tapajos Forest BNP-allANP-Forest ANP-Cerrado

Forest

Cerrado

open

closed

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0.00

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0.60

0.70

Mar-00 Jun-00 Sep-00 Jan-01 Apr-01 Jul-01 Oct-01 Feb-02

EVI

Tapajos Forest BNP-allANP-Forest ANP-Cerrado

Forest

Cerrado

open

closed

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VI Ratio (Tapajos/ BNP)

0.5

1

1.5

2

2.5

3

3.5

6-Feb-00

16-May-00

24-Aug-00

2-Dec-00

12-Mar-01

20-Jun-01

28-Sep-01

6-Jan-02

16-Apr-02

25-Jul-02

Forest- Cerrado Ratio

NDVI

EVI

August Dry Peak

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Conclusions (Brazil)

• We found MODIS to be useful in characterizing the spatial and temporal dynamics of the Amazon Basin,

• Multitemporal profiles of the MODIS data revealed well-defined seasonal patterns in the cerrado region with decreasing dry-wet seasonal patterns in the transitional areas near Santana do Araguaia,

• Seasonality was observed to a small and uncertain extent at the Tapajos National Forest site, however, it was unclear whether this was associated with seasonal changes in forest leaf area or temporal changes in understory vegetation,

• We further found MODIS VI seasonal patterns to significantly vary in land converted areas.

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Algorithm summary

Composite result

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Clouds, cloud shadow, and BRDF induce the largest uncertainties.

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Snow Problem in VI’sNDVI EVI

Snow effects: • Blue > Red > NIR• NDVI gives false negative signal• EVI gives false positive signal

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SAVI0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

EVI

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

Cereal Crop / GrasslandBroadleaf ForestNeedleleaf ForestBroadleaf Forest

EVI & SAVI Relationships for Snow

EV

I

RT-Model

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 0.1 0.2 0.3 0.4 0.5 0.6

SAVI

Sevilleta

Jornada

Walnut Gulch

Konza

Harvard Forest

Cascades

MODIS Data (2000-2001)

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EVI0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

NDVI

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Cereal Crop / GrasslandBroadleaf CropNeedleleaf ForestBroadleaf Forest

North America Sites

0

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1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

EVI

NDVIYuma Sands

Sevilleta

Jornada

Walnut Gulch

Konza

Harvard Forest

Cascades

NDVI & EVI Relationships

RT-Model MODIS Data (2000-2001)

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Biophysical Validation

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Mongu NDVI and Fpar (2000-2002)

0

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0.7

0 60 120 180 240 300 360 420 480 540 600 660 720 780

Cumulative Days

Trac Fpar

MODIS NDVI

Trac SZA 10° to 30°

Trac SZA 30º to 50º

Trac SZA 50º to 75º

Huemmrich and Privette

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Conclusions• VI products are provisionally validated from

radiometric, seasonal, interannual and biophysical perspectives,

• product accuracy has been assessed by a number of independent measurements, at a number of locations or times representative of conditions portrayed by the product.

• Residual cloud, cloud shadow, BRDF, topography, and snow induce the largest uncertainties in the VI’s,• Assessment of feasibility of using snow product and BRDF products.

• VI product accuracy varies with QA.