Transcript Red-Edge - Nitrogen Use Efficiency

Louisiana State University
Sensor Research Updates
Yumiko Kanke, Dr. Brenda Tubana, Dr. Jasper Teboh, and Josh Lofton
Remote Sensor Studies
• Crops: sugarcane, rice, cotton and corn
• Application: improve midseason N fertilizer
recommendations
• Activities
– Update database
– Refinement algorithms
– Validation/calibration
Rice Updates
• Grain yield potential can be predicted at panicle
differentiation (1501-1900 cumulative GDD).
• Research in on-going
– To evaluate the impact of water reflectance
– To refine the algorithm
Rice Updates
• The water as a background may alter canopy reflectance
readings. This is most significant when plant biomass is
small and the stand is thin.
– Low N rate, NDVI could be from 0.44 to 0.58
– High N rate, NDVI could be from 0.62 to 0.66
Rice Updates
Nadir
Tilted (45o angle)
Poster Presentation
Check Plot
210 lbs/A
NDVI =0.168
0.725
0.438
0.757
Sugarcane Updates
Estimated optimal N rates for cane yield production fell within or below (majority of
the site-years) the recommended rates . *Sugarcane is a perennial crop. Plant cane
is fist year plant, stubble cane is 2nd or 3 rd year plant.
Optimum Nitrogen Rate, lbs/ac
120
Recommended N for stubble cane:
80-120 lbs N ac-1
100
80
60
40
20
Recommended N for plant cane:
60-100 lbs N ac-1
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Site-Year
2004 to 2009, different varieties
Sugarcane: Research Focus 1
988 2nd Stubble
• Crop age effect
• Refinement procedure
– cumulative growing
degree days
– Number of days from __ to
sensing
226 1st Stubble
Cane Yield, ton/acre
45
384 1st Stubble
40
540 1st Stubble
35
226 1st Stubble
233 1st Stubble
30
540 1st Stubble
25
226 Plant Cane
20
233 Plant Cane
15
10
cane yield potential = 11.162e1.5717*NDVI
r² = 0.4618
5
0
0.35
12000
0.45
0.55
0.65
0.75
0.85
10000
Sugar Yield, lbs/acre
• Sugarcane is a perennial
crop. It re-grows after
each harvest for multiple
years (4 years) without
annual reseeding.
128 2nd Stubble
50
8000
6000
4000
2000
sugar yield potential = 2354.4e 1.7915*NDVI
r² = 0.5012
0
0.35
0.45
0.55
0.65
NDVI
0.75
0.85
Sugarcane: Research Focus 2
• Varietal diversification is an essential program
in Louisiana’s sugarcane industry.
• Canopy structure effect
• Refinement procedure
-categorize by canopy structure (droopy and erect leaf)
or plant height
Sugarcane: Research Focus 2
• Categorize by canopy structure (droopy and erect
leaves)
y = 2217e1.4327x
226
R² = 0.23
8000
6000
All data
4000
y = 2827.5e1.2186x
10000
Sugar yield (lbs/ac)
9000
R²
8000
= 0.21
2000
0.5
0.6
0.7
y = 2278e1.5173x
384
7000
226
6000
384
R² = 0.42
8000
5000
6000
4000
4000
3000
0.8
2000
540
2000
0.4
0.5
0.6
0.7
0.4
0.5
0.6
0.8
540
NDVI
0.7
0.8
y = 3280.5e1.1997x
R² = 0.23
8000
3000
0.4
0.5
0.6
0.7
0.8
Sugarcane: Research Focus 3
• Nitrogen fertilization is done early in spring
(one time application)
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Tall stature – challenge when collecting data
How early we can put our N reference strip?
How late can we apply N fertilizer?
Small biomass is an issue early in the spring. Three weeks after growth
recommenced in spring, height may become an issue.
Rice and Sugarcane: Research Focus 4
• Evaluate spectral reflectance based on leaf element
and plant canopy structure using red-edge.
Red-edge
 Wavelength between RED and NIR wavelengths
 670 nm to 780 nm (Meer and Jong, 2006)
 700 and 750 nm (Seager, 2005)
 The first or second derivative of reflectance between 690
to 740 nm, depending on the sensor (Dixit, 1985)
Index
• Reflectance
Reflectance between 680-740 nm. Index could be
described as ratio of reflectance.
• Derivative analysis (Red-edge position)
The wavelength of maximum slope in the red edge
reflectance . The wavelength which has a maximum point
of the first derivative reflectance. Index could be described
as the specific wavelength . (Cho and Skidmore)
For example
- Chlorophyll content can be explained by red-edge index
Red Edge Position
The maximum point of the first derivative
reflectance
Red-Edge (Reflectance Ratio)
(R734-747nm)/(R715-726nm)
(Moss, 1991)
Derivative Analysis
Not only points but area and shape
High N rate
• Maximum point
– Longer wavelength (approx. 750 nm)
– Peak of the reflectance pattern
• Large total area
Low N rate
• Maximum point
-Shorter wavelength
-Between 720 to 740 nm
• Small total area
(Filella, 1994)
Red-Edge Points
• Highly correlated with
- chlorophyll content (Meer, 2007)
- plant biomass (Mutanga, 2004)
• Less affected by soil background (Jong, 2007)
• Very narrow bands needed to be observed
• Complicated method to determine REP
-The simple maximum derivatie
-Linear interpolation (Guyot and Baret, 1988)
-Inverted Gaussianmodelling (Miller et al., 1990)
-High orderpolynomial fitting (Pu et al., 2003)
-Linear extrapolation techniques (Cho and Skidmore )
-Lagrangian interpolation technique (Dawson and Curran, 1998)
Potential to be a new index for determine N rate?
• Yes, especially biomass completely covers ground
NDVI at Different Biomass Level
1
NIR
780nm
0.9
0.8
0.7
NDVI
0.6
Feekes 4
0.5
Feekes 5
Red
650nm
0.4
0.3
Feekes 7
Feekes 10
0.2
0.1
0
0
0.05
0.1
0.15
0.2
0.25
0.3
Degree of Plant Biomass
• However, need to be discussed
- Red-edge, What are you looking for? Red-edge
reflectance, point, shape, or area?
- Looking at very narrow bands, work in practical fields?
Thank you
References
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Meer, F.V.D., and S.M. de Jong. 2006. Imaging spectrometry for agriculture applications. In: Imaging
spectrometry: Basic principal and prospective application, eds. Clevers, J. G. P. W. and R. Jongschaap,
pp.157-197. Dordrecht, Netherlands : Springer.
Seager, S., E.L. Turner, J. Schafer, and E.B. Ford. 2005. Vegetation’s Red edge: a possible spectroscopic
biosignature of extraterrestrial plants. Astrophysics. 5: 372-390.
Dixit, L. and S. Ram. 1985. Quantitative analysis by derivative electronic spectroscopy. Appl. Spectr.
Rev. 21:311-418.
Cho, M.A, A.K. Skidmore, C. Atzberger.. Towards red-edge positions less sensitive to canopy
biophysical parameters using prospect-sailh simulated data.
http://www.isprs.org/proceedings/XXXVI/part7/PDF/115.pdf
Cho, M.A. and Skidmore, A.K., In Press. A new technique for extracting the red edge position from
hyperspectral data: The linear extrapolation method. Remote Sensing of Environment.
Guyot, G. and Baret, F., 1988. Utilisation de la haute resolution spectrale pour suivre l'etat des
couverts vegetaux, Proceedings of the 4th International colloquim on spectral signatures of objects in
remote sensing. ESA SP-287, Assois, France, pp. 279-286.
Miller, J.R., Hare, E.W. and Wu, J., 1990. Quantitative characterization of the red edge reflectance. An
inverted- Gaussian reflectance model. International Journal of Remote Sensing, 11(10): 1755-1773.
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Pu, R., Gong, P., Biging, G.S. and Larrieu, M.R., 2003. Extraction of red edge optical parameters from Hyperion
data for estimation of forest leaf area index. IEEE Transactions on Geoscience and Remote Sensing, 41(4):
916-921.
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Dawson, T.P. and Curran, P.J., 1998. A new technique for interpolating red edge position. International
Journal of Remote Sensing, 19(11): 2133-2139.