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Using Landsat TM Imagery to Predict Wheat Yield and to Define Management Zones. Landsat TM Imagery. How can we use Landsat TM imagery to predict wheat yield? How accurately can imagery collected in near flowering (April 1 to May 15) predict wheat yields?

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Presentation Transcript
landsat tm imagery
Landsat TM Imagery
  • How can we use Landsat TM imagery to predict wheat yield?
  • How accurately can imagery collected in near flowering (April 1 to May 15) predict wheat yields?
  • Can satellite wheat yield estimates be used to prescribe management zones?
slide5

ImageProcessing and NDVI Computation

Clear-sky Thematic Mapper (TM) scenes of north-central Oklahoma, spanning the period 1991 to 1999, were obtained from Space Imaging with radiometric and geometric corrections.

The TM scenes were chosen so that the satellite overpasses occurred at or near the heading stage of winter wheat in the area (mid April to early May).

dates and tm scenes used in the study
April 4, 1991

May 9, 1992

April 25, 1993

March 27, 1994

April 2, 1996

April 20, 1997

April 23, 1998

May 12, 1999

Dates and TM scenes used in the study:
slide7

OSU Wheat Pasture Research Unit Overlaid on top of April 23,1998 False Color TM Image (Green, Red, and NIR bands).

N

Grain wheat

Grazed out wheat

slide9

Calibration curve of wheat grain yield as a function of Landsat TM NDVI. Oklahoma State University Wheat Pasture Research Unit, Marshall, OK.

90

TM 93 (April 25)

TM 97 (April 20)

75

TM 98 (April 23)

TM 99 (May 12)

60

Predicted Yield

95% Pred. Lim.

45

Wheat Yield (bu/ac)

30

15

0

0.3

0.4

0.5

0.6

0.7

0.8

0.9

NDVI

slide10

Relative Locations of Test Farms and OSU Wheat Pasture Research Unit

Cherokee

Pond Creek

OSU WPRU

Marshall

slide11

Field-average wheat grain yield, as predicted from NDVI and measured by farmer cooperators.

75

Cherokee, OK

98

Pond Creek,

60

98

97

98

OK

93

94

Pond Creek-2,

99

98

93

93

OK

Marshall, OK

96

45

9

Predicted Yield (bu/ac)

91

96

96

94

97

30

91

91

92

96

15

92

0

15

30

45

60

75

0

Measured Yield (bu/ac)

slide12

Field-average wheat yield as a function of field-average NDVI, compared with the OSU WPRU prediction equation.

90

Cherokee, OK

Pond Creek, OK

75

Pond Creek-2, OK

Marshall, OK

60

Predicted Yield

95% Pred. Lim.

45

Field-Average Yield (bu/ac)

30

15

0

0.4

0.5

0.6

0.7

0.8

0.9

Field-Average NDVI

normalizing satellite estimated yield
Normalizing Satellite Estimated Yield
  • Normalization tends to remove the effect of weather, disease and other factors on the average yield.
  • This minimizes the effect of abnormally high or yields when yield variability is compared between years or averaged over years.
  • Yields can be normalized by dividing by the average yield for the field.
aerial image vs average yields
Aerial Image vs. Average Yields

Linn Aerial Image

Terrace

Effects

red rock ok 7 year average estimated yield and coefficient of variation

NorgeC2

KirklandB2

PortA

NorgeB

KirklandB

Misclassified

Red Rock, OK - 7 Year Average Estimated Yield and Coefficient of Variation

Floods

pond creek oklahoma
Pond Creek, Oklahoma

Dale Silt Loam

McLain Silt Loam

Owner Identified Soil

slide20

Pond Creek, OK - Normalized Estimated Yield and Temporal Coefficient of Variation for Seven Years of Data

Water and Hay for Calves

Field Drainage

cherokee oklahoma
Cherokee, Oklahoma

Reinach Very Fine Sandy Loam

McLain Silt Loam

Dale Silt Loam - SALINE

cherokee oklahoma22
Cherokee, Oklahoma

Drainage problem from moldboard dead furrow

Hayed for Demonstration Plots

Salt Slick

hitchcock ok

Average Normalized Yield

  • < 0.85
  • 0.85 – 0.95
  • 0.65 – 1.05
  • 1.05 – 1.15
  • 1.15
  • Field Boundary
Hitchcock, OK
hitchcock ok28
Hitchcock, OK

Farm since homesteaded

Average Normalized Yield

  • < 0.85
  • 0.85 – 0.95
  • 0.65 – 1.05
  • 1.05 – 1.15
  • 1.15
  • Field Boundary

Broken out of native grass pasture in 10 ac increments in the 1970’s

Low pH in 2001

disease effect on estimated yield enid ok
Disease Effect on Estimated Yield -Enid, OK

5% Set-Aside Ground

2180

Chisholm

tonkawa ok
Tonkawa, OK

Sprayed with Metribuzin for Cheat

Not sprayed for cheat

Area was intensively grazed by 105 calves. Wheat yield was about 3 times greater than estimated

Saline Soil

slide33

What may be gained by even higher resolution sensing?

25 m Resolution (Re-sampled) Landsat TM

1m Resolution NDVI

conclusions
Conclusions
  • Satellite imagery can be used to predict yields.
  • Normalized estimated yield can be used for management decisions:
    • Define average relative yield
    • Identify regions of high and low yield whose cause changes slowly over time
      • Drainage
      • Soil type
      • Organic matter
      • pH
conclusions35
Conclusions
  • Images can be used to define management zones for the purpose of managing these variables.
  • Imagery can complement yield monitor data or when yield data are not available can serve as a surrogate.
  • Currently, Landsat TM images are the only source of historical data for the entire United States, and, despite the coarse resolution provides, a means to begin managing less than field size areas.
conclusions36
Conclusions
  • Potentially, with sufficient data, harvester yield measurements can be used to obtain the same management data as satellites.