Hyperspectral Manipulation for the Water Stress Evaluation of Plants
DOI:
https://doi.org/10.7251/COM1201018UAbstract
There are high demands for water content estimation in vegetation, e.g. water-stress control for sweet crops, forest disease monitoring and drought monitoring. In this paper, normalized difference-based and ratio-based water stress indices by means of hyperspectral information from NIR to SWIR, spectral ranges of InGaAs sensor, are introduced to facilitate realizing simple measurement system at reasonable cost. Regardless of the simple definition, sufficient estimation accuracies are realized in the proposed indices under the condition of laboratory observation. The experimental results based on airborne hyperspectral forest images showed that the water-stress indices are useful to detect oak wilt areas.References
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[13] D. Chen, J. Huang, and T. J. Jackson, Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near- and short-wave infrared bands, Remote Sensing of Environment, 98−2-3 (2005) 225–236.
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[18] N. Kamata, Outbreaks of forest defoliating insects in Japan, 1950-2000, Bulletin of Entomological Research, 92−2 (2002) 109–117.
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[2] S. Jacquemoud and F. Baret, Prospect: A model of leaf optical properties spectra, Remote Sensing of Environment, 34−2 (1990) 75–91.
[3] J. W. Rouse, R. H. Haas, J. A. Schell, and D. W. Deering, Monitoring vegetation systems in the great plains with ERTS, in Proceedings of the Third ERTS Symposium, 1 (1973) 317.
[4] B. Datt, Remote sensing of water content in Eucalyptus leaves, Australian Journal of Botany, 47−6 (1999) 909–923. [5] J. C. Price and W. C. Bausch, Leaf area index estimation from visible and near-infrared reflectance data, Remote Sensing of Environment, 52−1 (1995) 55–65.
[6] A. A. Gitelson, Y. Gritz , and M. N. Merzlyak, Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves, Journal of Plant Physiology, 160−3 (2003) 271–282.
[7] L. Kou, Refractive indices of water and ice in the 065- to 25, Applied Optics, 28−19 (1993) 1714–1714.
[8] D. M. Wieliczka, S. Weng, and M. R. Querry, Wedge shaped cell for highly absorbent liquids: infrared optical constants of water, Applied Optics, 28−9 (1989) 1714–1719.
[9] J. Penuelas, F. Baret, and I. Filella, Semiempirical indexes to assess carotenoids chlorophyll-a ratio from leaf spectral reflectance, Photosynthetica, 31−2 (1995) 221–230.
[10] E. R. Hunt and B. N. Rock, Detection of changes in leaf water content using near- and middle-infrared reflectances, Remote Sensing of Environment, 30−1 (1989) 43–54.
[11] B.-c. Gao, Ndwi–normalized difference water index for remote sensing of vegetation liquid water from space, Remote Sensing of Environment, 58−3 (1996) 257–266.[12] R. Fensholt and I. Sandholt, Derivation of a shortwave infrared water stress index from MODIS near- and shortwave infrared data in a semiarid environment,” Remote Sensing of Environment, 87−1 (2003) 111–121.
[13] D. Chen, J. Huang, and T. J. Jackson, Vegetation water content estimation for corn and soybeans using spectral indices derived from MODIS near- and short-wave infrared bands, Remote Sensing of Environment, 98−2-3 (2005) 225–236.
[14] M. A. Hardisky, V. Klemas, and R. M. Smart, The influences of soil salinity, growth form, and leaf moisture on the spectral reflectance of spartina alterniflora canopies, Photogrammetric Engineering and Remote Sensing, 49 (1983) 77–83.
[15] W. Collins, S. H. Chang, G. L. Raines, F. Canney, and R. Ashley, Airborne biogeophysical mapping of hidden mineral deposits, Economic Geology, 78−4 (1983) 737–749.
[16] B. N. Rock, T. Hoshizaki, and J. R. Miller, Comparison of in situ and airborne spectral measurements of the blue shift associated with forest decline, Remote Sensing of Environment, 24−1 (1988) 109–127.
[17] Y. Kosugi, K. Uto, H. Akbari, K. Kojima, and N. Tanaka, Hyperspectral manipulation for the detection of water-based biological abnormalities,” in Conference on Water and Nano-Medicine, Banja Luka, 2011.
[18] N. Kamata, Outbreaks of forest defoliating insects in Japan, 1950-2000, Bulletin of Entomological Research, 92−2 (2002) 109–117.
[19] K. Uto, Y. Kosugi, T. Ogata, and S. Odagawa, Normalized wilt index based on visible/near-infrared hyperspectral analysis of Japanese oak wilt, Journal of the Japan Society of Photogrammetry and Remote Sensing, 49−5 (2010) 294–309.
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2012-10-19
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