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Proceedings Paper

Nitrogen content estimation using Hyperion hyperspectral image based on normalized band depth method
Author(s): Jinguo Yuan; Zheng Niu; Limin Long; Shihua Li
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Paper Abstract

Canopy nitrogen content has strong relationship with net primary productivity, litter nitrogen and nitrogen mineralization rate, so the estimation of nitrogen content can provide valuable understanding of large-scale terrestrial carbon and nitrogen cycle. Hyperspectral remote sensing technology demonstrates the capacity for accurate biochemical component estimation of vegetation. This paper employed Hyperion hyperspectral data acquired over Xishuangbanna tropical area in Yunnan province, China to estimate nitrogen content based on normalized band depth (BNC) method. Hyperion data geometric and radiometric corrections were first made, and then Hyperion reflectance of 56 samples in 35 plots was extracted. Continuum removal was applied to the selected absorption features related to nitrogen. The BNC of 56 samples were calculated. Relationships between BNC values in Hyperion image and in situ field measured nitrogen content were analyzed using stepwise multiple linear regression. Results showed that central wavelengths in the model predicting nitrogen were 650.67nm, 2213.93nm, 2173.53nm and 671.02nm, and coefficient of determination (R2) was 0.505. Bands 650.67nm and 671.02nm coincided with chlorophyll absorption features highly related to nitrogen; 2213nm and 2173nm corresponded to protein and nitrogen absorption features. Correlation analysis showed that the biggest correlation coefficient between nitrogen and BNC was -0.573, which was at 650.67nm.

Paper Details

Date Published: 15 November 2007
PDF: 7 pages
Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678728 (15 November 2007); doi: 10.1117/12.751547
Show Author Affiliations
Jinguo Yuan, Hebei Normal Univ. (China)
Institute of Remote Sensing Applications (China)
Zheng Niu, Institute of Remote Sensing Applications (China)
Limin Long, Hebei Normal Univ. (China)
Shihua Li, Institute of Remote Sensing Applications (China)

Published in SPIE Proceedings Vol. 6787:
MIPPR 2007: Multispectral Image Processing

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