[Winter wheat growth spatial variation study based on temporal airborne high-spectrum images].
Precision agriculture technology is defined as an information-and technology-based agriculture management system to identify, analyze and manage crop spatial and temporal variation within fields for optimum profitability, sustainability and protection of the environment. In the present study, push-broom hyperspectral image sensor (PHI) image was used to investigate the spatial variance of winter wheat growth. The variable-rate fertilization contrast experiment was carried out on the National Experimental Station for Precision Agriculture of China during 2001-2002. Three airborne PHI images were acquired during the wheat growth season of 2002. Then contrast analysis about the wheat growth spatial variation was applied to the variable-rate fertilization area and uniformity fertilization area. The results showed that the spectral reflectance standard deviation increased significantly in red edge and short infrared wave band for all images. The wheat milky stage spectral reflectance has the maximum standard deviation in short infrared wave band, then the wheat jointing stage and wheat filling stage. Then six spectrum parameters that sensitive to wheat growth variation were defined and analyzed. The results indicate that parameters spatial variation coefficient for variable-rate experiment area was higher than that of contrast area in jointing stage. However, it decreased after the variable-rate fertilization application. The parameters spatial variation coefficient for variable-rate area was lower than that of contrast area in filling and milking stages. In addition, the yield spatial variation coefficient for variable-rate area was lower than that of contrast area. However, the yield mean value for variable-rate area was lower than that of contrast area. The study showed that the crop growth spatial variance information can be acquired through airborne remote sensing images timely and exactly. Remote sensing technology has provided powerful analytical tools for precision agriculture variable-rate management.
Song
Xiao-yu
XY
National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China. Songxy@nercita.org.cn
Wang
Ji-hua
JH
Yan
Guang-jian
GJ
Huang
Wen-jiang
WJ
Liu
Liang-yun
LY
D000383:Agriculture; D002681:China; D058998:Remote Sensing Technology; D062206:Spatial Analysis; D014908:Triticum / Q000254:growth & development*