Mhangara Paidamwoyo, Mapurisa Willard
Earth Observation Directorate, South African National Space Agency (SANSA), The Enterprise Building, Mark Shuttleworth Street, Pretoria 0002, South Africa.
Sensors (Basel). 2019 Sep 4;19(18):3831. doi: 10.3390/s19183831.
The surge in the number of earth observation satellites being launched worldwide is placing significant pressure on the satellite-direct ground receiving stations that are responsible for systematic data acquisition, processing, archiving, and dissemination of earth observation data. Growth in the number of satellite sensors has a bearing on the ground segment payload data processing systems due to the complexity, volume, and variety of the data emanating from the different sensors. In this paper, we have aimed to present a generic, multi-mission, modularized payload data processing system that we are implementing to optimize satellite data processing from historical and current sensors, directly received at the South African National Space Agency's (SANSA) ground receiving station. We have presented the architectural framework for the multi-mission processing system, which is comprised of five processing modules, i.e., the data ingestion module, a radiometric and geometric processing module, atmospheric correction and Analysis Ready Data (ARD) module, Value Added Products (VAPS) module, and lastly, a packaging and delivery module. Our results indicate that the open architecture, multi-mission processing system, when implemented, eliminated the bottlenecks linked with proprietary mono-mission systems. The customizable architecture enabled us to optimize our processing in line with our hardware capacities, and that resulted in significant gains in large-scale image processing efficiencies. The modularized, multi-mission data processing enabled seamless end-to-end image processing, as demonstrated by the capability of the multi-mission system to execute geometric and radiometric corrections to the extent of making it analysis-ready. The processing workflows were highly scalable and enabled us to generate higher-level thematic information products from the ingestion of raw data.
全球范围内发射的对地观测卫星数量激增，给负责对地观测数据的系统采集、处理、存档和传播的卫星直接地面接收站带来了巨大压力。由于不同传感器产生的数据具有复杂性、大容量和多样性，卫星传感器数量的增长对地面段有效载荷数据处理系统产生了影响。在本文中，我们旨在介绍一个通用的、多任务的、模块化的有效载荷数据处理系统，我们正在实施该系统，以优化从历史和当前传感器直接在南非国家航天局（SANSA）地面接收站接收的卫星数据处理。我们展示了多任务处理系统的架构框架，该框架由五个处理模块组成，即数据摄取模块、辐射和几何处理模块、大气校正和分析就绪数据（ARD）模块、增值产品（VAP）模块，最后是打包和交付模块。我们的结果表明，开放架构的多任务处理系统在实施后消除了与专有单任务系统相关的瓶颈。可定制的架构使我们能够根据硬件能力优化处理，这在大规模图像处理效率方面带来了显著提升。模块化的多任务数据处理实现了无缝的端到端图像处理，多任务系统执行几何和辐射校正直至使其具备分析就绪能力就证明了这一点。处理工作流程具有高度可扩展性，使我们能够从原始数据的摄取中生成更高级别的专题信息产品。
