Title :
Estimation of rice canopy nitrogen concentration by hyperspectral remote sensing
Author :
Jingjing Wang ; Ling Sun ; Chunlin Shi ; Qingjiu Tian
Author_Institution :
Inst. of Agric. Econ. & Inf., Jiangsu Acad. of Agric. Sci., Nanjing, China
Abstract :
Real-time monitoring the change of rice canopy nitrogen concentration can help us acquire the rice growth status, improve fertilization efficiency and reduce farmland contamination. In our experiment, canopy spectra with different fertilization levels were measured by an ASD Fieldspec FR spectrometer in three different growths periods, and the related rice samples were collected. Through red edge characteristic and absorption characteristic analysis, the best wavelength and spectral variation for rice nitrogen concentration estimation were obtained based on the results of experimental plots data analysis. The depth of absorption feature centered at 670nm based on Band Normalized to Center (BNC) was found to be strongly correlated with the nitrogen concentration of jointing, heading and filling periods. It was validated by EO-1 Hyperion image and the results showed that the depth of absorption feature centered at 670nm based on BNC calculated from image spectra also had significant correlation with nitrogen concentration, which was chosen to build rice canopy nitrogen concentration estimation model based on Hyperion image.
Keywords :
correlation methods; fertilisers; geophysical image processing; remote sensing; ASD Fieldspec FR spectrometer; BNC; Band Normalized to Center; EO-1 hyperion image; absorption characteristic analysis; canopy spectra; correlation; farmland contamination reduction; fertilization efficiency improvement; filling periods; growths periods; heading periods; hyperspectral remote sensing; image spectra; jointing periods; real-time monitoring; red edge characteristic; rice canopy nitrogen concentration estimation; rice growth status; rice samples; spectral variation; wavelength variation; Correlation; Estimation; Hyperspectral imaging; Nitrogen; Reflectivity; Vegetation mapping; Hyperion; hyperspectral remote sensing; nitrogen concentration; rice;
Conference_Titel :
Agro-Geoinformatics (Agro-Geoinformatics), 2013 Second International Conference on
Conference_Location :
Fairfax, VA
DOI :
10.1109/Argo-Geoinformatics.2013.6621878