The database of recording the snapshots of land parcels history is the foundation for the most of the models on
simulating land use/cover change (LUCC) process. But the sequences of temporal snapshots are not sufficient to deduce
and describe the mechanism of LUCC process. The temporal relationship between scenarios of LUCC we recorded could
not be transfer into causal relationship categorically, which was regarded as a key factor in spatial-temporal reasoning.
The proprietor of land parcels adapted themselves to the policies from governments and the change of production
market, and then made decisions in this or that way. The occurrence of each change of a land parcel in an urban area was
often related with one or more decision texts when it was investigated on the local scale with high resolution of the
background scene. These decision texts may come from different sections of a hierarchical government system on
different levels, such as villages or communities, towns or counties, cities, provinces or even the paramount. All these
texts were balance results between advantages and disadvantages of different interest groups. They are the essential
forces of LUCC in human dimension. Up to now, a methodology is still wanted for on how to express these forces in a
simulation system using GIS as a language. The presented paper was part of our initial research on this topic.
The term "Event" is a very important concept in the frame of "Object-Oriented" theory in computer science. While in the
domain of temporal GIS, the concept of event was developed in another category. The definitions of the event and their
transformation relationship were discussed in this paper on three modeling levels as real world level, conceptual level
and programming level. In this context, with a case study of LUCC in recent 30 years in Xiamen city of Fujian province,
P. R. China, the paper focused on how to extract information of events and rules from the policy files collected and
integrate the information into the LUCC temporal database. The paper concluded by listing the main steps of how to
extract events and rules from files and build an event database, and indicating directions for future work about how to
develop a spatial-temporal reasoning system on the event-oriented LUCC database.