Title: Integrating Remote Sensing in Precision Agriculture:
1Integrating Remote Sensing in Precision
Agriculture Lessons Learned and New Directions
Jim Schepers USDA-ARS Agronomy and Horticulture
Department University of Nebraska
2Satellites
Clouds Timeliness Turn Around Resolution
Clouds Timeliness
Platforms
3Spectral Opportunities
70 60 50 40 30 20 10 0
Photosynthesis
Reflectance ()
400 500 600 700 800 900 1000
Wavelength (nm)
4Spectral Opportunities
70 60 50 40 30 20 10 0
Bare Soil
Reflectance ()
400 500 600 700 800 900 1000
Wavelength (nm)
5Computer Generated Management Zones
6Sensor-based mapping
7Data Collection
Reality
8Regrouping
9Soil-based N Management
After Planting
Bare Soil Image
10Computer Generated Management Zones
Incorporating. . .
Bare Soil Image Elevation Slope EM-38
11Spectral Options
70 60 50 40 30 20 10 0
Color Film
Reflectance ()
400 500 600 700 800 900 1000
Wavelength (nm)
12Color IR
Soybean
Hail damage
Sprayer problems
Cultivation in progress
13UniformityConcerns (May Turn Into Huge Yield
Concerns)
End-gun OFF
14IrrigationDesign Flaws
Nozzle in canopy
15Irrigation Design Flaws
Corner unit ON
16September 1, 2003
1-foot resolution
17September 1, 2003
1-foot resolution
18Leaf Anatomy Spectral Interaction
Chlorophyll
Palisade Cells
Spongy Mesophyll
Lower Epidermis
Stoma
Air Space
1970 60 50 40 30 20 10 0
Young Plant
Reflectance ()
Bare Soil
400 500 600 700 800 900 1000
Wavelength (nm)
2070 60 50 40 30 20 10 0
Healthy Plant
Reflectance ()
Bare Soil
400 500 600 700 800 900 1000
Wavelength (nm)
21September 1, 2003
1-foot resolution
22Normalized Difference Vegetation Index
70 60 50 40 30 20 10 0
NDVI (NIR Red) / (NIR Red)
Near Infra-Red
Reflectance ()
GNDVI (NIR Green) / (NIR Green)
400 500 600 700 800 900 1000
Wavelength (nm)
23Sensitivity of Vegetation Indices To Various
Chlorophyll Levels
Adapted From Gitelson et al. (1996)
LAI gt2.0
24(No Transcript)
25Mosaic Approach to Variable Rate N
Maize
Imagery during grain fill (yield map
proxy) Bare soil image (estimate
OM) Residual N (field average)
Spatial yield goal
Spatial mineralization ??
26Correlation Coefficient
12-bit aircraft data 24 x 50 plots 1 spatial
resolution
27Green NDVI vs N Rate over Time
Irrigated Corn
kg N/ha
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29Field Calibration
Direction of travel
30Sufficiency Index (SI)
Unknown Reference
Response Index (RI)
Reference Unknown
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32Making In-Season nitrogen fertilizer
recommendations
33?
?
What information is needed ?
Are all approaches equally viable ?
34Building Blocks of N Recommendations
Field-scale yield goal provided by
producer Variable yield goal based on maps (MZ,
etc.) Predicted yield based on crop vigor
Dynamics of crop growth
35Dry Matter (Mg/ha)
?
GGD
36Irrigated Corn
What we know Weather in July and August has a
strong influence on yield. How can yield
estimates compensate for weather?
N Uptake
Dry Matter
Total N Uptake (kg/ha)
Dry Matter (Mg/ha)
37Relative Yield
Dry Matter (Mg/ha)
Mosaic Approach
GGD
38What we know about corn ? ? ?
3950 Sun-Screen
40V6 V8 Avoid all stresses
41(No Transcript)
42Influence of Seedling Emergence And Spacing on
Corn Yield
Planter Speed
Tillage
43(No Transcript)
44Effect of Plant Spacing On . . . . .
Leaf N Concentration SPAD Readings Yield
4524,000 plants/acre
46Conclusion Root exploration is extensive
47Conclusion For a given N rate, photosynthesis is
proportionate to light interception
48Conclusion For a given N rate, grain is
proportionate to light interception, which is
proportionate to distance between plants
49Extrapolated Yield Based on By-Plant Grain
Yield (bu/acre)
Conclusion Roots and leaves of closely spaced
plants explore considerably more area than is
proportionate to the allocated average distance
between adjacent plants
Average Distance (inches)
50Extrapolated Yield Based on By-Plant Grain
Yield (bu/acre)
Average Distance (inches)
51By-Plant Yield Variability
weighed grain from individual plants from 20
long sections of 10 rows from different
management zones and N treatments
Nobody told these plants that they couldnt share
above-ground spaces. They also share below-ground
living quarters.
Where do the nutrients come from that contribute
to yield? How about the assimilation of
carbohydrates?
52What are the causes of different ear
sizes? Emergence date Plant spacing Nutrients
53What is the appropriate spatial resolution for N
management ?
Field Strip Management Zone Few Plants
What is possible ? What is practical ?
54Managing N According To - - - -
Macro-heterogeneity
Landscape features
Management zones
Micro-heterogeneity
Individual or Group of Plants
55Yield
Relative SPAD
kg N/ha
GDD
56Yield
Relative SPAD
kg N/ha
GDD
57Yield
V6
V12
Relative SPAD
kg N/ha
GDD
58Irrigated Corn
What will work for producers? Risk Equipment Econo
mics Labor
N Uptake
Dry Matter
Total N Uptake (kg/ha)
Dry Matter (Mg/ha)
59Decision Aid Development
In-Season N Management
Calibration
Algorithm
60Congratulations . . .
You Survived !!!!
61Thank You
Jim Schepers 402-472-1513 jschepers1_at_unl.edu