Spatio-temporal dynamics of perennial

energy crops in the U.S. Midwest

agricultural lands

Cuizhen (Susan) Wang

Associate Professor, Dept. of Geography, University of Missouri

E-mail: wangcu@missouri.edu; Tel: 1-573-884-0895

with co-authorsGary Stacey, Center for Sustainable Energy, MU

Felix B. Fritschi, Division of Plant Sciences, MU

Wyatt Thompson, FAPRI, and Dept. of Agricultural/Applied Economics, MU

Timothy C. Matisziw, Dept. of Geography, Dept. of Civil/Environmental Engineering, MU

Zhengwei Yang, USDA/NASS

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Introduction

Biomass exceeds 3% of energy supplies and is the largest source of renewable energy in the United States;

Upon an optimistic estimate, biomass feedstocks could replace 30% of domestic petroleum consumption by 2030 (Perlack et al. 2005);

Corn ethanol currently constitutes 99% of US biofuel(Farrel et al. 2006).

The US biofuel refiners budgeted 4.2 billion bushels of corn (1/3 of US corn production) in the 2009-2010 marketing year (Economic Research Service 2010).

Environmental

Ecological

socio-economic concerns2 / 18

Native prairie grasses are identified by DOE as a model cellulosic crop, an alternative of bioenergy feedstock.

3 / 18(Source: Oak Ridge National Lab)

Warm-season native grasses currently grow in mixed conditions with cool-season forage grasses, and have not been mapped in any published agricultural databases.

Current spatial

distributions and

temporal dynamics?

The Midwest agricultural region

Study area and data sets

Validation sites:

Flint Hills, KS

The largest unplowed

tallgrass prairie remn.

(>80% native grasses).

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Cherokee Plain, MO

Sandhills upland

prairie, NE

Satellite imagery and published maps

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• Cropland Data Layers (CDL)

- USDA NASS

- 12 states

- 2007

• Major crops in the Great Plains

- Grass (tall/short/cool-season);

- Corn+Soybean;

- Winter wheat

- Spring wheat

• 500-m, 8-day MODIS surface reflectance products (MOD09A1);

- 4 scenes;

-NDVI time series (46 scenes/year)

- 10-year period (00-09);

Time series analysis

Approach

• median filter spikes removal

• Savitzky-Golay filter curve smoothing

Source: Jonsson and Eklundh 2004.

• Asymmetric Gaussian simulation

• extracting phenology matrices

TIMESAT

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7 / 35

Corn Soybean Winter wheat

WSG grass CGS grass

(Source: Wang et al. 2011)

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Example time series:

Phenology metrics

• End of season: when NDVI decrease to 20% of amplitude;

• Growing length: number of dates in start-end of seasons;

• Cumulative growth (∑NDVI):NDVI integral in start-end of seasons;

• peak date: dates of peak NDVI;

• Summer dry-down (∆NDVI): decrease of NDVI in spring-summer if

peak NDVI falls in early stage (especially useful for winter wheat);

TIMESAT extracted (3 out of 11):

Self-identified:

- Early: peak date falls in DOY 1-161 (Jan – Mid June)

- Middle: peak date falls in DOY 145-193 (May - Mid July)

- Late: peak date falls in DOY 161-313 (Mid June – Mid Nov)

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Longitudal shifts

Source: Wang et al. 2011

Peak Date:

(2days/degree)

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Climate-induced shifts

100

150

200

250

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

Peak N

DV

I

Peak_date

0.3

0.4

0.5

0.6

0.7

0.8

0.9

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

Peak N

DV

I

Peak_NDVI

200

240

280

320

360

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

End D

ate

End_date

80

120

160

200

240

280

320

20

00

20

01

20

02

20

03

20

04

20

05

20

06

20

07

20

08

20

09

Seaon L

eng

thSeason Length

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Phenology metrics inventory (CART results)

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

PDatww 145 145 153 145 145 145 145 137 153 153

Lencorn_

sw

184 200 184 184 184 184 184 184 176 176

Endsw 261 261 269 261 261 261 261 261 269 269

Lentallgra

ss

252 252 236 244 260 244 236 260 236 236

PVALww

_sw

0.5 0.5 0.5 0.5 0.5 0.6 0.5 0.6 0.5 0.5

PVALtall

grass

0.6 0.6 0.6 0.6 0.6 0.6 0.5 0.6 0.6 0.6

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W. wheat

Short grs

Peak in

early spr.

Low peak value

Summer dry-

down

Y

Corn/SoyLate peak date

Y

CSG

Y

Y

Y

W. wheat;

CSG

Corn/Soy;

S. wheat;

Short grsEarly end

WSG;

CSG

Long grow

season

Short grow

seasonTime

seriesS. wheat

WSGShorter season

Phenology-based decision tree (concept framework)

13 / 18For more details, please refer to Wang et

al., Annuals of AAG, 101(4), 2011.

(thresholds

flowchart)

Results

The Midwest crop maps, 2000-2009

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Flint Hill, KS (2000-2009)

A 2-year MDC project

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Cherokee Plain, MO (with past studies)

DOY Date Sensor

52 2/21/2007 ASTER

73 3/14/2006 TM

92 4/2/2007 TM

106 4/16/2007 AWIFS (A)

111 4/21/2007 AWIFS (A)

134 5/14/2007 AWIFS (B)

140 5/20/2007 AWIFS (A)

153 06/02/2006 TM

172 06/21/2007 TM

188 07/07/2007 AWIFS (A)

192 7/11/2007 AWIFS (B)

202 7/21/2007 ASTER

220 8/8/2007 TM

228 8/16/2007 ASTER

240 8/28/2007 AWIFS (B)

271 9/27/2008 TM

292 10/19/2007 ASTER

303 10/29/2008 TM

313 11/9/2006 TM

Taberville

Pr.

WKT Pr.

Osage Pr..

Pr. State Park

Summary and future research

The 20+ million ha of native grasses (upon validation) in the Midwest indicates its high bioenergy potential;

Future investigation:

• region-wide validation!

• biomass quant. of energy crops;

• Bioenergy policy and LULC.

The spatially explicit energy crop map is a quantitative supplement to county-level biomass supplies.

17 / 18ORNL Switchgrass production.

Native warm-season grasses in the Midwest hold unique phenology metrics (time series analysis);

Next……?

Phenology metrics vary with inter-annual climate dynamics (phenology metrics inventory);

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Thanks!

Acknowledgement: This research is supported by the Mizzou Advantage

Project. We would like to thank Le T. Ngan, Wei Zhang, Qing Chang in

Dept. of Geography and D.J. Donahue at FAPRI in data process. Also our

thanks to USDA/NASS for providing the CDL data that serve as excellent

reference in this research.