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Proceedings Paper

Estimating foliar water content of winter wheat with hyperspectral image
Author(s): Xia Zhang; Quanjun Jiao; Di Wu; Bing Zhang; Lianru Gao
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Paper Abstract

Estimates of vegetation water content are of great interest for assessing vegetation water status in agriculture and forestry, and have been used for drought assessment. This study focuses on the retrieval of foliar water content with hyperspectral data at canopy level. The hyperspectral image used in this study was acquired by the airborne operative modular imaging spectrometer (OMIS) at Demonstration Site for Precision Agriculture in Xiaotangshan area, Beijing, on April 26th, 2001. 40 image spectra were extracted to correspond to the quasi-synchronous meansurements of foliar water content (FWC). The image spectra of winter wheat were utilized to validate the sensitivity of the existing and novel water indices and parameters of three water absorption features in NIR and SWIR regions. Correlation analysis showed that, NDWI(860,1241) and NDWI(860,1200) both had significant linear relationships with FWC (R2 were 0.4124 and 0.4042 respectively). Red edge position (REP) could reflect indirectly the variations of wheat FWC to some extent. Significant linear relationships were also found between WI(820,1600) and FWC, and between WI(900,1200) and FWC, while no relationship was shown between the traditional WI(900,970) and FWC. The derived depth of water absorption centered around 2078nm, namely AD2078, had the highest linear correlation with FWC (R2 is 0.4551) , much higher than those parameters derived from the two water absorption around 1175 and 1409. In the end, AD2078 was applied to OMIS image to map the foliar water content. The value range of the inverted foliar water content ranged from 69.39 to 78.35%, which was quite close to that of the field measurements (70.72-78.12%). The distribution of the FWC map was quite consistent with growth status of winter wheat.

Paper Details

Date Published: 15 November 2007
PDF: 8 pages
Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 678718 (15 November 2007); doi: 10.1117/12.749316
Show Author Affiliations
Xia Zhang, Institute of Remote Sensing Applications (China)
Quanjun Jiao, Institute of Remote Sensing Applications (China)
Di Wu, Institute of Remote Sensing Applications (China)
Bing Zhang, Institute of Remote Sensing Applications (China)
Lianru Gao, Institute of Remote Sensing Applications (China)


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

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