Inversion of vegetation biochemical material contents by remote sensing

Haiyan Ji; Pengxin Wang; Tailai Yan

doi:10.1117/12.668032

2 February 2006 Inversion of vegetation biochemical material contents by remote sensing

Haiyan Ji, Pengxin Wang, Tailai Yan

Proceedings Volume 6031, ICO20: Remote Sensing and Infrared Devices and Systems; 60310U (2006) https://doi.org/10.1117/12.668032
Event: ICO20:Optical Devices and Instruments, 2005, Changchun, China

Abstract

With remote sensing techniques, we could relate remote sensing measurements to the biochemical characteristics of the Earth surfaces in a reliable and operational way. It plays an important role in the estimate of the biochemical contents. The spectroscopic estimation of vegetation biochemical concentration was welcoming a new dawn with the developments of high spectral remote sensing technologies. Leafs of wheat at different grow period were used to measure reflectance spectra and biochemical components concentration. Reflectance spectra of leaf were measured by ASD field spectrometer in the spectra range of 350nm ~ 1650nm. Two kinds of statistical methods were used to inversion the biochemical concentrations: Stepwise regression analysis and partial least-squares regression, which were applied to established models of biochemical components concentrations (chlorophyll and water) with reflectance spectra of wheat's leaf at different grow period. The inversion results of two methods are: For chlorophyll, the correlation coefficient is 0.894, 0.898, and the relative standard deviation is 13.8%, 13.6% respectively; For water, the correlation coefficient is 0.983, 0.999, and the relative standard deviation is 2.3%, 0.3% respectively. Stepwise regression analysis method and partial least-squares regression method may inversion the chlorophyll and water of wheat leaf at different grow periods.

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Haiyan Ji, Pengxin Wang, and Tailai Yan "Inversion of vegetation biochemical material contents by remote sensing", Proc. SPIE 6031, ICO20: Remote Sensing and Infrared Devices and Systems, 60310U (2 February 2006); https://doi.org/10.1117/12.668032

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KEYWORDS

Biological research

Remote sensing

Reflectivity

Vegetation

Spectroscopy

Calibration

Statistical analysis

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