Various studies related to spatial indices are currently being conducted. Most of these studies focus on lowering the costs for indexed searches in on-demand environments during spatial query processing. However, on-demand environments often have issues with service delays when there is a congestion of the query on the server when dealing with information about complicated moving objects. Therefore, a study on spatial indices that considers broadcast environment is required. Studies on information transfer in broadcast environments should consider the characteristics of one-dimensional sequential flow. However, studies thus far on indexing methods that consider such characteristic are insufficient. In particular, there has been no study that considers both the data transfer sequence and an index structure capable of managing a moving object within a broadcast environment. In this paper, we propose a data transfer method that considers the location/distribution of objects and the air index structure for the location management of moving objects within a broadcast environment. The results from theoretical analyses and experiments show the proposed algorithms that use the GSI method are scalable and energy efficient for range queries and k-nearest neighbor queries.