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Are NDVI Readings Sensors Dependent?. Tremblay, N., Z. Wang, B. Ma, C. Bélec and P. Vigneault St-Jean-sur-Richelieu, Quebec. Yara FieldScan (N-Sensor). Yara FieldScan (N-Sensor). GreenSeeker. Justifications. Variable N Rates Based on vegetation indices (e.g. NDVI) - PowerPoint PPT Presentation
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Are NDVI Readings Sensors Dependent?
Tremblay, N., Z. Wang, B. Ma, C. Bélec and P. VigneaultSt-Jean-sur-Richelieu, Quebec
Yara FieldScan (N-Sensor)
Yara FieldScan (N-Sensor)
TouchScreen
Card DriveSpreader Controller
Irradiance Sensor
Left Sensors Right Sensors
Cab Top Mounted
In Cab Section
PC
DGPS or GPS (optional)
S2S1
GreenSeeker
Justifications
• Variable N Rates– Based on vegetation indices (e.g. NDVI)– Algorithms under development
• Importance of univariate population statistics in the design of fertilization algorithms (Pena-Yewtukhiw et al., 2006)– Divide the population into classes, and then treat each class
with a particular rate of fertilizer N• Are NDVI readings (therefore, the algorithms) sensors
dependent?
Outfit For Devices Comparison v. 2007
Sensors Sampling Density on Summer Wheat 2005
Yara FieldScan GreenSeeker
Yara FieldScan Scanning Area as Compared to GreenSeeker Positions
Yara FieldScan NDVI and GreenSeeker NDVI in Wheat
0.0 0.2 0.4 0.6 0.8 1.0NDVI_Yara
0.0
0.2
0.4
0.6
0.8
1.0N
DV
I_G
S
0.0 0.2 0.4 0.6 0.8 1.0NDVI_Yara
0.0
0.2
0.4
0.6
0.8
1.0
ND
VI_
GS
0.0 0.2 0.4 0.6 0.8 1.0NDVI_Yara
0.0
0.2
0.4
0.6
0.8
1.0
ND
VI_
GS
ZG
S23
(30
DA
S)
ZG
S30
(33
DA
S)
ZG
S41
(40
DA
S)
2005
0.0 0.2 0.4 0.6 0.8 1.0NDVI_Yara
0.0
0.2
0.4
0.6
0.8
1.0
ND
VI_
GS
ZG
S33
(42
DA
S) 2006
0.77
0.41
0.86
0.47
0.90
0.46
Variability in Wheat Field 2006
Wheat
• CV of NDVI values decreased with growth stages and were lower with the Yara FieldScan
• Yara FieldScan saturated earlier• However, in 2006, for NDVI lower than 0.5:
– NDVI_Yara’s CV: 26 % – NDVI_GS’s CV: 31 %
• GreenSeeker showed no progression with growth stage
Yara FieldScan
• 50-100 m²/s• Scan at an
oblique view zenith angle (64° on average)
Oblique vs nadir views
• Plant Chl concentration better predicted from oblique-looking reflectance measurements (Demetriades-Shah and Court, 1987)– Soil reflectance is reduced
• Spot area of oblique angle (45°) greater by 50 % (Poss et al., 2006)
• Saturates at lower values than nadir directions (Myneni and Williams, 1994)
• Likely more sensitive to canopy conditions at early stages
Corn 2005
Yara FieldScan NDVI and GreenSeeker NDVI in Corn
0.0 0.2 0.4 0.6 0.8 1.0NDVI_Yara
0.0
0.2
0.4
0.6
0.8
1.0N
DV
I_G
S
0.0 0.2 0.4 0.6 0.8 1.0NDVI_Yara
0.0
0.2
0.4
0.6
0.8
1.0
ND
VI_
GS
0.0 0.2 0.4 0.6 0.8 1.0NDVI_Yara
0.0
0.2
0.4
0.6
0.8
1.0
ND
VI_
GS
Ear
ly V
5 (4
2 D
AS
) V
5 (4
8 D
AS
)
V4
(43
DA
S)
20062005
0.32
0.30
0.64
0.47
x1.6 x2.0
Yara Devices
• N-Sensor• FieldScan
– 550, 660, 700, 740, and 780 nm• N-Sensor ALS
Reusch et al., 2002
Vegetation Indices and Saturation
• GreenSeeker
• NDVI from Yara FieldScan tend to saturate because of geometry• Optimized vegetation index
– VIopt = 100*(lnR780-lnR740), Reusch (2005) – Larger CV than NDVI on wheat
• ZGS 23 (8 vs 6 %)• ZGS 30 (8 vs 3 %)• ZGS 41 (9 vs 1 %)
– Other version: VIopt = 100*(lnR760-lnR730), Jasper et al. (2006)
http://www.ntechindustries.com/lit/gs/DataSheet_GS_Sensor.pdf
Conclusions
• More similarities between sensors with corn than wheat• NDVI from Yara FieldScan saturated earlier
– Oblique view– Potentially more sensitivity at early stages; less at late stages– Let’s try GreenSeeker looking forward on small corn for more
sensitivity at early stages– Opportunities for more adapted indices from other bands
• Notably different NDVI population statistics depending on crop features and growth stages– Implications for algorithms development
Acknowledgements
• M.Y. Bouroubi• GAPS program (Agriculture and Agri-Food Canada)• Summer students• synAgri for aSEC data collection• Éric Thibault (Pleine Terre s.e.n.c.)• Growers Landry, Bieri and Martel
For more information: –Contact Nicolas Tremblay: [email protected] –web: http://res2.agr.ca/stjean/personnel/tremblay_e.htm
Thank You !