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Estimated Moisture
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Figure 7: Estimation Maps based on HyMap Imagery
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
6. CONCLUSION
Estimation methods for the wheat yield, quality, and growth
conditions were evaluated using both the ground-based and
airborne hyperspectral data of the suburbs of Mullewa, Western
Australia. This study revealed that the head moisture was well
estimated by the multi regression analysis using the
hyperspectral data of the later grain filling stage. This also
indicated that the grain weight was well estimated by the PLS
regression analysis, and the grain nitrogen content rate and ash
content were well estimated by the multi regression analysis
using the hyperspectral data of the heading stage. To sum up,
this study achieved certain results of the development of the
monitoring method for the wheat yield, quality, and growth
conditions using hyperspectral data of the later grain filling and
heading stages. For the future, the estimation accuracy will be
improved by modifying the estimation methods. It is also
possible that the estimation methods will be examined in
different regions.
7. ACKNOWLEDGEMENT
This study was conducted as part of the project, "The 2009 and
2010 Research and Development of the Fundamental
Technology for Next-generation Satellite Utilizations, of the
former Earth Remote Sensing Data Analysis Center (ERSDAC).
We sincerely thank Dr. Tom Cudahy and Dr. Ian C Lau at the
Commonwealth Scientific and Industrial Research Organization
(CSIRO) and Mr. Buddy Wheaton and Dr. Daniel Carter at the
Department of Agriculture and Food, Western Australia
(DAFWA) for their help in the field study and airborne
observations.
8. REFERENCES
Imai, Y., Morita, T., Akamatsu, Y., Odagawa, S., Takeda, T.,
and Kashimura, O., 2011. Evaluation of wheat growth
monitoring methods based on hyperspectral data in western
Australia. In: IGARSS 2011: IEEE International Geoscience
and Remote Sensing Symposium Proceedings, pp. 3338-3341.
Inoue, Y., Pefiuelas, P., Miyata, A., and Mano, M., 2008.
Normalized difference spectral indices for estimating
photosynthetic efficiency and capacity at a canopy scale
derived from hyperspectral and CO2 flux measurements in rice.
In: Remote Sensing of Environment, vol. 1112, pp. 156-172.
Shibayama, M. and Akiyama, T., 1989. Seasonal visible, near-
infrared and mid-infrared spectra of rice canopies in relation to
LAI and above-ground dry phytomass. In: Remote Sensing of
Environment, vol. 27, pp. 119-127.
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