Assessment of spectral variation between rice canopy components using spectral feature analysis of near-ground hyperspectral imaging data
- Resource Type
- Conference
- Authors
- Zhou, Kai; Cheng, Tao; Deng, Xinqiang; Yao, Xia; Tian, Yongchao; Zhu, Yan; Cao, Weixing
- Source
- 2016 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS) Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2016 8th Workshop on. :1-4 Aug, 2016
- Subject
- Aerospace
Computing and Processing
Geoscience
Signal Processing and Analysis
Absorption
Reflectivity
Hyperspectral imaging
Agriculture
Nitrogen
Spatial resolution
continuum removal
hyperspectral images
paddy rice
absorption feature
panicle
leaf
- Language
- ISSN
- 2158-6276
Near-ground imaging spectroscopy is emerging as a promising sensing technique that can provide us with very fine spatial resolution imaging data for observing individual canopy components. It is an efficient tool to understand the within-canopy variation in spectral properties of paddy rice and resolve uncertainty sources in the spectroscopic estimation of rice chemistry. Many studies have use the spectral reflectance of the whole canopy for estimating foliar chemical properties (e.g., nitrogen content) but few of them have paid attention to the spectral difference between leaves and panicles. In addition, shaded and sunlit leaves or panicles coexist in the canopy but how their spectral properties differ and the differences change with growth stage are unknown. In this paper, continnum-removed (CR) reflectance spectra of different canopy components and background materials for the whole growing season of paddy rice were examined in the blue and red absorption regions. The results demonstrated that shaded components always showed lower reflectance amplitude but deeper absorption depth than their sunlit counterparts. Leaves exhibited different shapes in the blue absorption region from panicles and duckweeds. The findings are useful for resolving the photosynthetic signals of sunlit and shaded leaves and have great potential for improving the estimation of foliar chemistry from canopy spectral reflectance.