Li Xin, Zhang Li-ming, Chen Hong-yao, Xu Wei-wei
Guang Pu Xue Yu Guang Pu Fen Xi. 2016 Mar;36(3):811-6.
The multispectral remote sensing technology has been a primary means in the research of biomass monitoring, climate change, disaster prediction and etc. The spectral sensitivity is essential in the quantitative analysis of remote sensing data. When the sensor is running in the space, it will be influenced by cosmic radiation, severe change of temperature, chemical molecular contamination, cosmic dust and etc. As a result, the spectral sensitivity will degrade by time, which has great implication on the accuracy and consistency of the physical measurements. This paper presents a characterization method of the degradation based on man-made spectral targets. Firstly, a degradation model is established in the paper. Then, combined with equivalent reflectance of spectral targets measured and inverted from image, the degradation characterization can be achieved. The simulation and on orbit experiment results showed that, using the proposed method, the change of center wavelength and band width can be monotored. The method proposed in the paper has great significance for improving the accuracy of long time series remote sensing data product and comprehensive utilization level of multi sensor data products.
多光谱遥感技术一直是生物质监测、气候变化、灾害预测等研究中的主要手段。光谱灵敏度在遥感数据的定量分析中至关重要。当传感器在太空中运行时,它会受到宇宙辐射、温度剧烈变化、化学分子污染、宇宙尘埃等影响。结果,光谱灵敏度会随时间下降,这对物理测量的准确性和一致性有很大影响。本文提出了一种基于人造光谱目标的退化表征方法。首先,本文建立了一个退化模型。然后,结合从图像中测量和反演得到的光谱目标的等效反射率,就可以实现退化表征。仿真和在轨实验结果表明,使用所提出的方法,可以监测中心波长和带宽的变化。本文提出的方法对于提高长时间序列遥感数据产品的精度和多传感器数据产品的综合利用水平具有重要意义。