Keywords: Spatio-temporal database, Conceptual modeling, Observational data, Event
Abstract Recently many kinds of spatio-temporal data are repeatedly acquired for almost
the same objects because of the recent rapid progress of data acquisition technology. We have
strong needs to use many kinds of fragmentary data, in order to estimate the dynamic changes of
feature more accurately. It is necessary to establish or develop a framework of GIS, which
allows to estimate, reconstruct and predict the phenomena in the real world by integrating
various kinds of data. In this study we propose FEO (Feature/Event/Observation) model as
conceptual framework for dynamic revision of spatio-temporal database. FEO model will be a
part of the basis of intelligent GIS, which can reconstruct phenomena in the real world.
1. Introduction
1.1 Various kinds of needs
Geographic Information System (GIS) is expected to apply to a wide variety of fields, not
only to the existing fields such as facility management of lifeline, fixed property management
for taxation or emergency support after disasters, but also monitoring of the traffic congestion,
provision of guidance information in Intelligent Transport System (ITS), and the support of the
marketing activities. In these fields it will be required to collect information on phenomena
changing dynamically, to understand the situation, and furthermore to predict to the future
movement of the phenomena. Therefore data with finer resolution of time, space and attribute
will be needed for spatio-temporal database compared to the resolution of existing maps or
statistics.
1.2 Development of acquisition technology of spatio-temporal data
Because of development of sensor technology or network technology, the technological
capability of collection and measurement of spatial data has been expanding. For example there
is a survey technology to measure the three dimensional shape data of buildings using laser
scanner and video image (Zhao and Shibasaki, 1997). It means that we can get three
dimensional data of buildings from various angle using these new technology with existing
photogrammetry. On the other hand, the monitoring technology of the route choice activities of
cars using automatic recognition of vehicle number captured by video camera, or the monitoring
technology of moving activities of people using PHS are put to practical use, and these
technology will be expected to contribute to capture the spatio-temporal phenomena.
1.3 GIS of next generation
As we mentioned previous section, these collection and measurement technology of
spatio-temporal data, with finer resolution, have enabled to measure the same object repeatedly
from various angles, to acquire data of aspects which was not captured before. The system,
which can estimate the spatio-temporal distributions and changes of features (in this study cars
and people are included in features as mobile ones) with real-time processing taking in
monitoring data occurring continuously, is regarded as a form of GIS of next generation.
1.4 Lack of interaction between data acquisition and database development
However, we cannot always get the data just corresponding to each needs of a wide variety of
applications mentioned before. We need the process, in which the distributions and the changes
of objects are estimated interpreting various data from the measuring and monitoring process.
Even in the development and updating process of GIS database from existing photogrammetry,
previous understanding of the changes of buildings from administrative data or ground survey
data in the narrow road area, in which we cannot measure adequately, enable to help the
development of database more accurately.
When we take a general view of the study about acquisition and integration of
spatio-temporal data and about development and management of database from a viewpoint of
realizing a next generation GIS above, both studies have been developed separately. In other
words "edited" data representing the spatial distributions or temporal changes are made at first
and put them into the database. In these assumptions both studies have proceeded.
For the reason above, much less works about unify of the way of putting observational data
into database and the way of integration of the database can be seen.
On the other hands, many works about spatio-temporal database have been mainly done from
a viewpoint of how to realize database effectively based on a assumption of the existence of
"edited", "well-arranged" data above (For example, Langran:1992). These approaches, however,
have at least some problems that the process to estimate the states of features exists separately
and that observational data are scattered without putting into database and whose relations to the
corresponding feature tend to be unclear. Furthermore we have some possibilities of lacking in
necessary information, other than observational data, when estimating. The reason is that GIS
database is not designed for estimation of the states of features.
1.5 Development of representation model for "extended" spatio-temporal database
It is essential to unify the process of data acquisition and integration and the process of
database development and updating, and then to develop "extended" database managing the data
about features including observational data to overcome these problems above. For that object
various problems about conceptual model representing spatio-temporal changes of features,
implementation of database based on this conceptual model, and estimation model for the states
and changes of features, should be solved.
In this study chapter 2 introduces our conceptual model for representing "extended"
spatio-temporal database including observational data, not only feature data. Chapter 3 then
discusses about the estimation method with our proposed model. At last Chapter 4 and 5
demonstrates application possibility with some simple examples.
Of course in some fields systems or methods to estimate the states of features from various
kinds of observational data are investigated according to each property of feature and
observation means. But these investigations have started only recently and have not spread to
the other fields. The investigations about conceptual model as more general model will be
expected to contribute to the evaluation of each existing integration method or database
management, exploration of the new fields, and further development of each method.
2. Proposal of Feo Model
Chapter 2 proposes our FEO model as conceptual representation model, including observational
data not only features, for "extended" spatio-temporal database.
2.1 Basic concept
In order to realize "extended" spatio-temporal database as we mentioned before, requirement
for representation model is understood below.
- Conceptual model representing spatio-temporal distributions and changes of features with
their uncertainty
- Representation model including even observational data as explicit spatio-temporal data,
having distinguish between data representing spatio-temporal distributions or changes of
features and observational data which distributions and changes of feature are estimated or
reconstructed based on.
- Representation model of event as external cause because features have their internal changes
and their changes by external causes.
For requirement 1), we use an existing proposed conceptual feature model as we mention in
2.2. and therefore it is out of study object. In order to meet the requirement 2), conceptual
observation model is needed and we propose it in this paper. Foe requirement 3), conceptual
event model is also needed and will be proposed in this paper. Next section introduces our FEO
model as conceptual representation model based on the requirements above.
