With the increasing volume of remote sensing data, the efficient online data management and service system has become an essential infrastructure for research on massive remote sensing data application. At present, different remote sensing data storage and service application schemes have brought difficulties to the system implementation and application due to the lack of independent intermediate framework design. There is an urgent need for a remote sensing data online distributed management and service framework-independent of data storage and service application, and to reconstruct the implementation mode of data management and service, reduce the difficulty of massive remote sensing image online management and service. Against this background, we design and propose a platform-independent online distributed management and service framework for remote sensing(RS-ODMS) by abstracting the remote sensing data management and computing model. This framework constructs a remote sensing data distributed hybrid storage model (DHS) and a remote sensing image data distributed parallel computing model(DPC) to improve the remote sensing data management ability and service efficiency. Experimental results show that the prototype system based on RS-ODMS can support an expansion capability of multiple distributed storage backends on remote sensing image management. And it is endowed with high efficiency, stable service ability and extensive applicability, which can provide reference for the online management and service application research of massive remote sensing data.