China Data Cube (CDC) for Big Earth Observation Data: Lessons Learned from the Design and Implementation

Earth Observation (EO) data have the macro-level decision and analysis capabilities, which plays a key role in Earth science and significant scientific discoveries [1]. With the rapid development of space technologies, more and more EO data are accessed freely and shared openly. However, it is increasingly difficult, also more complex, to mine the information and knowledge among these massive-temporal datasets. EO Data Cubes (DC) provides a best-of-breed technology to build a spatial data infrastructure to fill this gap [2]. Among them, Australian Geoscience Data Cube (AGDC) [3, 4], as the leader and contributor, has supported data processing and analytical capability by dividing and restructuring grids. Following this open source software and work experience, we design and develop China Data Cube (CDC) system in recent years. Based on the new OGC DGGS standard and cloud computing technologies, CDC has got better system performance, more EO data types and richer local application cases. According to current and future months of work, this paper will describe and share the lessons learned from design and implement of CDC system. It will include following several aspects: 1) Overview of CDC system; 2) parallel EO data ingestion technology; 3) Cloud based EO data storage strategy; 4) Extension of more EO data types, especially China EO data; 5) The future work for CDC.