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Proceedings Paper

Use of airborne hyperspectral imagery to investigate the influence of soil nitrogen supplies and variable-rate fertilization to winter wheat growth
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Paper Abstract

Advanced technology in airborne detection of crop growth can help optimize the strategies of fertilization, and help maximize the grain output by adjusting field inputs. In this study, Push-broom Hyperspectral Image sensor (PHI) was used to investigate the influence of soil nitrogen supplied and variable-rate fertilization to the growth of winter wheat. The objective was to determine to what extent the reflectance obtained in the 80 visible and near-infrared (NIR) wavebands (from 410nm to 832nm) might be related to differences of variance of soil nitrogen and variable-rate fertilization. Management plots were arranged at Beijing Precision Farming Experimental Station. Three flights were made during the wheat growing season. Several field experiments, including the crop sampling, soil sampling and variable-rate fertilization were carried out in the field. Data were analyzed for each flight and each band separately. Some spectrum indices were derived from PHI images and statistical correlation analysis were carried out among the spectrum indices and soil nitrogen, variable-rate fertilization amount. In addition, the spectrum indices difference between elongation stage and grain filling stage are calculated and the correlation analysis was also carried out. The analysis results indicated that the reflectance of winter wheat is significantly influenced at certain wavelength by the soil nitrogen and the variable-rate fertilization. The soil nitrogen effect was detectable in all the three flights. Differences in response due to soil nitrogen variance were most evident at spectrum indices, such as red, INFLEX, Green/Red, NIRness, DVI and RDVI. Furthermore, analysis results also indicated that the variable fertilization can reduce the growth difference of winter wheat caused by spatial distribution difference of soil nitrogen.

Paper Details

Date Published: 11 October 2007
PDF: 10 pages
Proc. SPIE 6742, Remote Sensing for Agriculture, Ecosystems, and Hydrology IX, 67420M (11 October 2007); doi: 10.1117/12.736116
Show Author Affiliations
Xiaoyu Song, Beijing Academy of Agriculture and Forestry Sciences (China)
National Engineering Research Ctr. for Information Technology (China)
Guangjian Yan, Beijing Normal Univ. (China)
Jihua Wang, National Engineering Research Ctr. for Information Technology (China)
Liangyun Liu, National Engineering Research Ctr. for Information Technology (China)
Xuzhang Xue, Beijing Academy of Agriculture and Forestry Sciences (China)
Cunjun Li, Beijing Academy of Agriculture and Forestry Sciences (China)
Wenjiang Huang, Beijing Academy of Agriculture and Forestry Sciences (China)


Published in SPIE Proceedings Vol. 6742:
Remote Sensing for Agriculture, Ecosystems, and Hydrology IX
Christopher M. U. Neale; Manfred Owe; Guido D'Urso, Editor(s)

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