As we have entered the era of “big data,” the capability of Earth observations has been dramatically increased and reached an unprecedented level by widely accessible remotely sensed big data. The current remote sensing systems collect several terabytes of Earth observation data per day and enable the measurement of objects at the submeter level. Moreover, with the rapid development of imaging and earth observation technologies, the collected data volumes are predicted to be amplified quickly. Efficient management and analytics for such remotely sensed data are critical in the applications of Earth observations, but present great challenges due to data complexity, diversity, and volume. Actually, there exists great imbalance between the capacity of data management and analytics and the capacity of data acquisition in remote sensing. Thus, it is an urgent demand to develop effective data management tools and advanced analytical techniques for the best use of remotely sensed big data. Meanwhile, streaming and online real-time algorithms are required for quick and intelligent decision making.