Remote sensing data, as national fundamental and strategic resources, plays an important role in economy, state security, environment protection and ecology. Since remote sensing data have been widely used in various industries, there is a large amount of data requests from different users, demanding a lot of valuable EOS (earth observation resources). On one hand, users′ data requests increase constantly. On the other hand, EOS resources are always limited. Our objective is to ease the contradiction between a large amount of users′ requests and limited EOS resources. The key idea is to merge identical or similar users′ requests in order to reduce the total number of requests, and then to use requirement forecasting and requirement mining technology to improve requirement fusion efficiency. It is high likely that different users may share identical or similar data requests, since users may show concerns about the same area of the earth over the same time range.