Spatio-temporal association rules mining is a key technology and a hot issue in the field of spatio-temporal data mining.The classical Apriori algorithm is usually utilized to detect the spatio-temporal association rules from the spatio-temporal transaction table

which is derived from the original spatio-temporal data.In most existing approaches to generate the spatio-temporal transaction table

many defects

such as data redundancy

further affects the efficiency of spatio-temporal association rules mining.This paper proposes an events-coverage based spatio-temporal association rules mining（ECSTAR for short） to overcome these limitations.ECSTAR employs the event’s coverage to divide the researching spatio-temporal domain into some cells to generate a spatio-temporal transaction.Among each cell

spatio-temporal relationship predications are utilized to present the spatio-temporal relationship between the events and spatio-temporal objects.Thus

the spatio-temporal transaction table is built and spatio-temporal association rules are mined by the Apriori algorithm.Moreover

many concepts about ECSTAR are expounded and its algorithm is narrated in detail.Finally

a practical experiment demonstrates the feasibility and validity of the ECSTAR.