【摘要】 长时间序列遥感数据集被广泛应用于全球或区域环境变化、植被动态变化、土地覆盖变化和植物生物物理参数反演等研究,受云、气溶胶、太阳高度角和地物二向反射等因素的影响,这些数据集本身存在很多噪声,限制了数据的深入分析和应用,因此,数据重建是应用前的重要工作。在总结归纳现有时间序列重建方法的基础上,综述了重建方法比较研究的成果,深入比较了常用重建方法对参数的设置要求,分析了目前对重建效果的评价方法以及存在的问题,同时对时间序列数据重建通用软件及其发展作了详细介绍。最后提出了时间序列重建以后的研究重点和发展方向,以期为长时间数据重建研究和应用提供帮助。更多还原

【Abstract】 Long time series of remote sensing data products have been widely applied in various fields,such as monitoring environment system on global or regional scales,analyzing vegetation and land cover dynamics,and extracting information of vegetation phenology.However,due to the effects of cloudy,aerosols,solar angle and bidirectional reflectance etc.,serious residual noise exists in the long time series data sets which hinder their future use.Therefore,reconstruction of long time series data sets is the most important work before application.In this paper,common used data reconstructing methods were reviewed firstly. Then the comparison works of the time-series reconstructing methods were summarized in detail.The parameter definition was also discussed for common used reconstructing methods.Assessment methods for reconstructing results with their problems were analyzed.A detailed introduction for the softwares used for time series and their development were made.Finally,the research focus and developing direction were proposed for the future work based on a comprehensive analysis of the available literature.更多还原