Signal decomposition of hypertemporal Sentinel-1 time series to optimize the information gain for land applications

随着欧洲哥白尼计划的启动和Sentinel-1A和B卫星的发射，首次获得了可靠的、免费的密集c波段时间序列。结合两颗卫星的数据，6天的重复率是可行的，这为SAR数据的获取引入了一个新的时间维度。这个新的维度允许并需要创新的数据分析策略，以优化SAR数据处理和信息获取。该项目的总体目标是开发和验证适合Sentinel-1的数据分析策略。该方法旨在对这些密集SAR时间序列进行时间分解。所获得的时空信息将根据其作为特定应用数据库的适用性进行分析。同时提出了一种基于时间分解方法的散斑滤波器。该滤波器具有只在时域内滤波的特点。从而保持原始数据的原始几何分辨率。此外，还将对该滤波器进行扩展，使其在时空域中运行。时间信号将被分解成不同频率的分量。高频分量表示由散斑或降水效应引起的随机后向散射变化。中低频分量与土壤湿度变化或植物生长等生物物理过程有关。研究哪个成分与哪个生物物理过程相关是这个项目的范围。此外，将研究关于时间采样率的最低要求，以便检测生物物理过程的影响。此外，还分析了c波段相位相关参数InSAR相干性和相位闭合误差作为土壤水分指标的潜力。根据结果，将研究时间分量在几种应用中的可用性。重点是土地覆盖制图，包括REDD+请求、土地覆盖变化检测、湿地动态分析和土壤水分指标的划定。

With the launch of the European Copernicus Program and the related launch of the satellites Sentinel-1A & B for the first time dense C-band time series are available reliably and free of charge. By combining the data of both satellites repetition rates of six days are feasible, which introduces a new temporal dimension to the SAR data acquisitions. This new dimensions allows and requires innovative data analysis strategies that optimize the SAR data processing as well as the gain of information.Overall aim of this project is the development and the validation of a suited Sentinel-1 data analysis strategy. The proposed approach aims at the temporal decomposition of these dense SAR time series. The gained spatiotemporal information will be analyzed in terms of its suitability as database for specific applications. At the same time a novel speckle filter will be developed based on the temporal decomposition approach. This novel filter has the characteristic to filter only in the time domain. Thus, the original geometric resolution of the original data will be maintained. Additionally, an extension of this filter which operates in the spatiotemporal domain will be developed as well.The temporal signal will be decomposed into components of different frequencies. High frequency components represent random backscattering variations caused by speckle or precipitation effects. Medium and low frequency components are related to biophysical processes such as soil moisture changes or plant growth. The investigation of which component is related to which biophysical process is scope of this project. Furthermore, the minimum requirements with regard to the temporal sampling rate to allow for the detection of the impact of biophysical processes will be investigated. Additionally the potential of the C-band phase related parameters InSAR coherence and phase closure error as soil moisture indicators will be analyzed.According to the results the usability of the temporal components will be investigated for several applications. Major focus is put on landcover mapping including REDD+ requests, the detection of landcover change, the analysis of wetland dynamics and the delineation of soil moisture indicators.