1. Are NDVI Readings Sensors Dependent? Tremblay, N., Z. Wang, B. Ma, C. Bélec and P. Vigneault St-Jean-sur-Richelieu, Quebec

2. Yara FieldScan (N-Sensor)

4. GreenSeeker

5. 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?

6. Outfit For Devices Comparison v. 2007

7. Sensors Sampling Density on Summer Wheat 2005 Yara FieldScan GreenSeeker

8. Yara FieldScan Scanning Area as Compared to GreenSeeker Positions

9. Yara FieldScan NDVI and GreenSeeker NDVI in Wheat ZGS23 (30 DAS) ZGS30 (33 DAS) ZGS41 (40 DAS) 2005 ZGS33 (42 DAS) 2006 0.77 0.41 0.86 0.47 0.90 0.46

10. Variability in Wheat Field 2006

11. 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

12. Yara FieldScan 50-100 m²/s Scan at an oblique view zenith angle (64° on average)

13. 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

14. Corn 2005

15. Yara FieldScan NDVI and GreenSeeker NDVI in Corn Early V5 (42 DAS) V5 (48 DAS) V4 (43 DAS) 20062005 0.32 0.30 0.64 0.47 x1.6 x2.0

16. Yara Devices N-Sensor FieldScan –550, 660, 700, 740, and 780 nm N-Sensor ALS Reusch et al., 2002

17. 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

18. 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

19. 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

20. An Invitation to St-Jean-sur-Richelieu 2008

21. For more information: –Contact Nicolas Tremblay: tremblayna@agr.gc.ca –web: http://res2.agr.ca/stjean/personnel/tremblay_e.htm Thank You !