Space-air-ground networks play important roles in both fifth generation (5G) and sixth generation (6G) techniques. Low earth orbit (LEO) satellites and high altitude platforms (HAPs) are key components in space-air-ground networks to provide access services for the massive mobile and Internet of Things (IoT) users, especially in remote areas short of ground base station coverage. LEO satellite networks provide global coverage, while HAPs provide terrestrial users with closer, stable massive access service. In this work, we consider the cooperation of LEO satellites and HAPs for the massive access and data backhaul of remote area users. The problem is formulated to maximize the revenue in LEO satellites, which is in the form of mixed integer nonlinear programming. Since finding the optimal solution by exhaustive search is extremely complicated with a large scale of network, we propose a satellite-oriented restricted three-sided matching algorithm to deal with the matching among users, HAPs, and satellites. Furthermore, to tackle the dynamic connections between satellites and HAPs caused by the periodic motion of satellites, we present a two-tier matching algorithm, composed of the Gale-Shapley-based matching algorithm between users and HAPs, and the random path to pairwise-stable matching algorithm between HAPs and satellites. Numerical results show the effectiveness of the proposed algorithms.