Abstract: Land Observing Satellite Data Center is the core platform for storing, distributing, processing, and integrating land observing satellite resources. It can provide high quality and effective services for the State Council and the relevant departments of government and local authorities. In the era of big data, the data center benefits from big data opportunities as well as suffering from big data challenges. In this paper, the big data challenges in the center are discussed and then a big data solution is presented. In particular, five major challenges include the 3V dimensions of big data (i.e. Volume, Variety, and Velocity) and the specific challenges in the CRESDA, i.e., extensibility and integration (of multiple disparate management systems). To tackle the challenges aforementioned, a distributed architecture is proposed to manage all resources inside the data center thanks to the Hadoop-like framework for storing and processing the big remote sensing data. It is hoped that the proposed architecture can lend more support to national decision-making, improve the country's spatial information resources application level and serves as a new economic growth source of land observing satellite data applications.