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The 3rd ISPRS Workshop on Dynamic and Multi-Dimensional GIS & the 10th Annual Conference of CPGIS on Geoinformatics
Chen, Jun

ISPRS, Vol.34, Part 2W2, “Dynamic and Multi-Dimensional GIS”, Bangkok, May 23-25, 2001
Yifan LI 1 Shaopeng SUN 2
1 Nautical Science and Technology Institute
Dalian Maritime University, Dalian, China, 116026
E-mail: yifanli@163.net
2 Nautical Science and Technology Institute
Dalian Maritime University, Dalian, China, 116026
E-mail: sun_sp@usa.net
KEY WORDS: Variable Map Scale, Spatial Data Model, Spatial Data Warehouse, Web-GIS
Through the research of the infinitely variable map scale in GIS, this paper bring forwards a set of design philosophy of infinitely variable
map scale in GIS from data modeling, data storage to data release. This design philosophy can provides powerful application support to
research and application of Digital Earth.
The accessing, management and application of data that
obtained from survey earth, have become the key technology in
the research of the digital earth. But surveying earth adopts
multi-scale method, so the data was gathered and accessed
repeatedly, making vast waste. With the application of Digital
Earth, we need extract information from the largest scale spatial
database, map with any scale and any theme, and achieve the
query and analysis function in geography information system.
This is infinitely variable map scale information generalization
The infinitely variable map scale technology includes map
automatic generalization and information automatic
generalization. The map automatic generalization has been
researched for twenty years and has gotten achievements. The
map automatic generalization is mapping according to scale and
theme, and symbolizes the map. This technology focus its main
purpose on the automatic generalization of map's graphics, but in
GIS, its main purpose is not only limited in the map visualization,
but also to achieve the query and analysis function of GIS, so
only the automatic generalization cannot satisfy the infinitely
variable map scale information generalization technology of
Digital Earth, we need information automatic generalization. The
information automatic generalization mainly accomplishes
information filtration, semantic integrality checking, topology
integrality, consistency checking, topology revert, attribute and
weight information reconstruction when extracts and generates
data from large scale spatial database to small scale spatial
database. It is need to reconstruct data structure if there is
difference in subject and purpose. This paper brings forward a
new resolution in information automatic generalization, and
achieves the infinitely variable map scale technology of GIS by
combing map automatic generalization.
The data management of infinitely variable map scale is the
necessary condition of multi data infusion and emulate & virtual
technology. But the related geographic data are multiple and
complicated, the general rule of spatial data cannot be described
and expressed exactly. Therefore, we need the support of
advanced map generalization model and database model. The
data management of infinitely variable map scale is an
information processing technology to use a big scale (e.g.
1:50000) spatial database as basic data source, auto add or
reduce information content of spatial object in designated region
with the change of scale, in order to make the self adapting of
compression and recur of spatial geographic data and map scale.
The distributed data storage of spatial data warehouse, analysis
and extraction of spatial data provide the theoretical basic of data
management of infinitely variable map scale. In addition, the key
technologies of data management of infinitely variable map scale
also should include:
2.1 Infinitely Variable Map Scale Oriented Data Model
There are two kinds of spatial data model in GIS: vector model
and raster model. The basic unit of vector model is zero
dimensional object (point). Points were integrated into high
dimensional object. Vector model objects include point, line and
region. Point and line are collection of one or many joined and
sequent points. These objects are close to the boundary of region,
and form a continuous region. Raster model is using serried
square grid to discretize data of designated geographic region,
and represents as pixel matrix. The position coordinates of object
are implicated in row-column of pixel matrix, and the features of
object are represented by gray scale of pixels. Point is expressed
as a pixel; Line is expressed as a cluster of adjoint pixels; Region
is expressed as pixels that fill in inside of the outline. With the
development of GIS and Remote Sensing, researchers want find
an integrated data model, and explore an integrated data
structure. Hybrid model or Composite model is the third data
model that combines vector and raster, and absorb their merits.
Procession of infinitely variable map scale spatial data need fast
compression and recur. Raster model can complete the
compression and recur quickly and vector model can restore
topological relationship, geometrical relationship and attribute
relationship of GIS. Therefore, we should adopt hybrid model
which combines vector and raster model as our infinitely variable
map scale spatial data. In this hybrid model, we use vector model
to deal with the geographic relationship of compressed infinitely
variable map scale information, and use raster model to achieve
the visualization of geographic data.
2.2 Spatial Data Warehouse
The functions supported by spatial data model and spatial
database determine the realization of functions of GIS. Thus, in
order to realize infinitely variable map scale function, we need
spatial database that has map generalization and information
generalization ability.
Based on definite theme, spatial data warehouse integrates data
from different databases, so data is integrity in structure. It can
extract data from different time measure, such as instant, period
of time, all time. Thus, we can deal with multi-application in
different fields. Spatial data warehouse integrate temporal
attributes and spatial attribute tightly. Through building analysis