A Project Linking In-situ and Satellite Measurements

A Project Linking In-situ and Satellite Measurementsto Validate MODIS Terrestrial Ecology Products

Warren B. Cohen, US Forest Service; Stith T. Gower, University of Wisconsin;

David P. Turner, Oregon State University; Peter B. Reich, University of Minnesota;

Steven W. Running, University of Montana

Objectives

• Develop better understanding of the climaticand ecological controls on total net primaryproduction and carbon allocation within andamong biomes

• Learn how flux tower-measured NEE andfield-measured NPP co-vary in time & how totranslate between them using ecological models

• Explore errors and information losses thataccrue when extrapolating field data to coarse-grained (1 km) surfaces

• Provide high quality site-specific data layersat four sites that can be compared to MODISand other sensor products

Technical

Scientific

Sites

BOREAS Northern Old Black Spruce (NOBS)

Muskeg (open black spruce),“Closed” black spruce, Aspen,Wetlands, Jack pine

Harvard Forest (HARV) LTER

Mixed hardwoods, Eastern hemlock,Red pine, Old-field meadow

Konza Prairie Biological Station (KONZ) LTER

Tallgrass, Shortgrass, Shrub, Gallery forest; grazing and burning regimes

Bondville Agricultural Farmland (AGRO) Corn, Soybeans, Fallow

Field-BasedSampling Design

100 25m2 plots

80 in a nested spatial series

20 plots broadly distributed

Plot measurements

Vegetation cover

LAI, fPAR

Aboveground biomass

Aboveground productivity

Belowground productivity

AGRO (29 July 99)

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0-1 2-3 4-5 6-7 8-9 10-11 12-13

LAI

Frac

tion

of O

bser

vatio

ns

Corn Soybeans

27 July 99

P vs. O r^2 = 0.72

LAI

98 % accurate(cross validation)

3.0

3.5

4.0

4.5

5.0

0 2 4 6 8 10 12

LAI

TM1

Ref

lect

ance

(%)

Corn Soybeans

3.0

3.5

4.0

4.5

5.0

5.5

6.0

0 2 4 6 8 10 12

LAI

TM2

Ref

lect

ance

(%)

Corn Soybeans

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

0 2 4 6 8 10 12

LAI

TM3

Ref

lect

ance

(%)

Corn Soybeans

30

35

40

45

50

55

60

0 2 4 6 8 10 12

LAI

TM4

Ref

lect

ance

(%)

Corn Soybeans

14.0

14.5

15.0

15.5

16.0

16.5

17.0

0 2 4 6 8 10 12

LAI

TM5

Ref

lect

ance

(%)

Corn Soybeans

4

5

6

7

8

9

10

0 2 4 6 8 10 12

LAI

TM7

Ref

lect

ance

(%)

Corn Soybeans

0.75

0.80

0.85

0.90

0.95

0 2 4 6 8 10 12

LAI

ND

VI

Corn Soybeans

-2.5-2.0-1.5-1.0-0.50.00.51.01.52.0

0 2 4 6 8 10 12

LAI

Spec

tral

Inde

x

Corn Soybeans

Combined Spectral Inde x

0

5

10

15

0 5 10 15

Observed LAI

Pre

dict

ed L

AI

Corn

Soybeans

Indiv idual Spe ctral Index, Inve rse

0

5

10

15

0 5 10 15

Observed LAI

Pre

dict

ed L

AI

Corn

Soybeans

Indiv idual NDVI, Inverse

0

5

10

15

0 5 10 15

Observed LAI

Pre

dict

ed L

AI

Corn

Soybeans

Indiv idual Spectral Inde x

0

5

10

15

0 5 10 15

Observed LAI

Pre

dict

ed L

AI

Corn

Soybeans

SoybeanTM1 0.867TM2 1.070TM3 0.240TM4 0.154TM5 -1.496TM7 0.399

CornTM1 -1.770TM2 0.268TM3 -0.480TM4 0.491TM5 1.633TM7 -0.703

ETM+ band 3

ETM+ band 3

ET

M+ band 4

ET

M+ band 5

ET

M+ band 5

NOBS57 % accurate(cross validation)

Spectral Index

0

4

8

12

0 4 8 12

Predicted LAI

Obs

erve

d LA

I

ETM+ band 4r = 0.422

7

0

2.5

3.0

3.5

4.0

4.5

0 2 4 6 8 10 12

LAI

TM1

Ref

lect

ance

(%)

3.0

3.5

4.0

4.5

5.0

5.5

0 2 4 6 8 10 12

LAI

TM2

Ref

lect

ance

(%)

3.0

3.5

4.0

4.5

5.0

0 2 4 6 8 10 12

LAI

TM3

Ref

lect

ance

(%)

14

16

18

20

22

24

26

28

0 2 4 6 8 10 12

LAI

TM4

Ref

lect

ance

(%)

8

10

12

14

16

18

20

22

0 2 4 6 8 10 12

LAI

TM5

Ref

lect

ance

(%)

5

6

7

8

9

10

11

12

0 2 4 6 8 10 12

LAI

TM7

Ref

lect

ance

(%)

0.60

0.65

0.70

0.75

0.80

0 2 4 6 8 10 12

LAI

ND

VI

-3

-2

-1

0

1

2

3

0 2 4 6 8 10 12

LAI

Spe

ctra

l Ind

ex

TM1 -0.086TM2 0.108TM3 -0.256TM4 -0.102TM5 -0.221TM7 1.466

Vegetation Cover Component Characterization System (3CS):

• Quantitative measurements of cover proportions• Basic building blocks for variety of classification systems• Improved LAI mapping?

Ground Cover - NormalizedPlot 2

45%

5%8%

11%

7%

16%

8% 0%

Moss

Lichen

Herb

Shrub

Litter

Tree Regen

CWD

Water

Ground Data - NormalizedPlot 4

1%

34%

19%

6%

11%

10%4% 15%

Moss

Lichen

Herb

Shrub

Litter

Tree Regen

CWD

Water

Plot 4 Canopy Cover

18%

3%

7%

72%

ConiferHardwoodSnagSky

Plot 2 Canopy Cover

52%

2%

3%

43%ConiferHardwoodSnagSky

sphagnum

feathermoss

n=48

All Plots Moss Lichen Herb Shrub Litter Tree Dead Water Conifer Hardwood DeadMoss 1.000Lichen -0.041 1.000Herb -0.334 -0.197 1.000Shrub -0.296 -0.045 -0.031 1.000Litter 0.102 -0.016 -0.003 -0.049 1.000Tree Regen. -0.174 -0.144 -0.323 -0.275 -0.229 1.000Dead Wood -0.101 -0.135 -0.282 -0.176 -0.149 0.008 1.000Water -0.179 -0.118 0.048 -0.104 0.063 -0.119 0.115 1.000Confier Canopy 0.343 0.011 -0.238 -0.214 -0.108 0.117 0.144 -0.176 1.000Hardwood Canopy -0.043 0.019 0.117 -0.003 0.101 -0.050 -0.099 -0.057 -0.200 1.000Dead Canopy -0.055 -0.045 -0.011 -0.174 0.139 0.004 0.047 0.293 -0.163 -0.023 1.000

Plot 1Mean and Standard Deviation

-20

0

20

40

60

80

100

1

cove

rMossLichenHerbShrubLitterTree RegenCWD WaterUnknownConiferHardwoodSnag

Plot 3Mean and Standard Deviation

-20

0

20

40

60

80

100

1

cove

r

MossLichenHerbShrubLitterTree RegenCWD WaterUnknownConiferHardwoodSnag

Correlations

n=48

n=192

Meeting Our Land Cover Mapping NeedsAGRO• corn (class--label fields in-situ)• soybean (class--label fields in-situ)• other (classes--label clusters in-situ & HD imagery)

HARV• hardwood/conifer (relative proportions--from HD imagery)• other (classes--label clusters in-situ & HD imagery)

KONZ• grass (short/tall combined class--labels from plots & HD imagery)• forest (one class--labels from plots & HD imagery)• shrub (percent--from HD imagery calibrated with camera observations, plots)• other (classes--label clusters in-situ & HD imagery)

HD (high definition) imagery: ADAR, IKONOS, AVIRIS mission photos, MQUALS

NOBS• conifer/hardwood/standing dead (relative proportions--from camera observations, HD imagery)• “ground” cover (relative proportions--from camera observations, moss classes from ocular estimate)• other (classes--label clusters in-situ, camera observations, & HD imagery)

“ground” cover classes: moss, lichen, herbaceous, shrub, fine litter, tree regeneration, coarse wood debris, water

Leaf-off HARV

Capturing seasonalityWith ETM+ is important to both landcover and LAI mapping

Leaf-on

JulyApril September

HARV

KONZ

0

1

2

3

4

5

6

7

8

27-May-99 22-Jun-99 27-Jul-99 11-Sep-99

Sample Date

LAI

Corn No Till Corn Conventional Till

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0-1 2-3 4-5 6-7 8-9 10-11 12-13

LAI

Frac

tion

of O

bser

vatio

ns

Corn Soybeans

27-Jul-99

LAI0 - 1 1 - 2 2 - 3 3 - 4 4 - 5 5 - 6 6 - 7 7 - 8

Frac

tion

of O

bser

vatio

ns

0.0

0.1

0.2

0.3

0.4

NO TILL CONV. TILL

Range of LAI for the 108 BigFoot Plots

LAI0 -

11 -

22 -

33 -

44 -

55 -

66 -

77 -

8

Frac

tion

of O

bser

vatio

ns

0.00

0.05

0.10

0.15

0.20

0.25

AVG. for 4 BOREAS tower plots = 4.2

27-Jul-99

Preliminary calculations

Preliminary calculations

Regression

Kriged residualsKriging

IGPB: Cropland

UMD: Cropland

Biome: Broadleaf Crops

Percent Tree Cover: 0

MODLand/BigFoot Comparisons

Land cover (e.g.,…)• aspatial: compare frequency distribution of translated site-specific classes with same from MODLand• spatially explicit: summaries of site-specific cover proportions within MODLand- labeled cells

LAI/fPAR (e.g.,…)• mean 1 km cell values vs. MODLand values• distributions of fine-grained values within MODLand cells

NPP (e.g.,…)• integrated 1 km cell values vs. MODLand values• distributions of fine-grained values within MODLand cells• spatially degrade land cover and LAI, repeat modeling, redo above NPP comparisons• informationally degrade land cover, repeat modeling at fine grain, redo comparisons