In this paper, we investigate time-division based framework for integrated sensing, communication, and computing in integrated satellite-terrestrial networks. We consider a scenario, where Internet-of-Things devices on the ground operate with sensing and communication in a time-division manner, and can process the sensing results locally, at the edge, or in the cloud via the satellite communication link. Based on the proposed framework, we formulate a multi-dimensional optimization problem to maximize the utility performance of sensing, communication, and computing abilities. After decomposing the original optimization problem into two subproblems, we first derive the closed-form solution of the optimal task partitioning strategy for terrestrial users and satellite users. Then, we develop the joint subframe allocation and task partitioning strategy to optimize the overall performance, by means of which the Pareto optimal solutions can be obtained along the Pareto frontier. Extensive simulations are provided to demonstrated the effectiveness of the proposed strategy, which is 10% to 60% superior compared with the benchmarks. Also, the trade-off between the multidimensional resource and multi-functional performance is analyzed from the perspective of network design.

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