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file the location has additional advantages since we can manage
image data through internet.
4.1 Using 2D-PIR for Content based metadata
2D-PIR that proposed by M Nabil (1997) has an architecture of
Image Retrieval System. The real image is considered as a big
raster image file. Metadata of the image file is replaced by two
type of file iconic image and a symbolic 2D-PIR
transformation of the image. The iconic image is a small bitmap
file that is stored in local storage as a preview of the original
image data. A symbolic image is a spatial / topological
information of the image file. This symbolic image is used as a
representation of image content for image query. Using these
two type of 'metadata', the user can query image data using two
alternatives : selecting image based on image preview, or
selecting image based on symbolic content.
4.2 Storing spatial and temporal information
The next step is building a database that contains image
information, constructed for spatial and temporal information.
There are many types of data that should be stored for every
image to make a single record. An Object Oriented Database is
recommended for this purpose. Some important objects that
related to image information and should be stored in the
database are :
a. Topology
A topology object is a directed graph that represents a 2D-
PIR of image content. This spatial information is made by
manual sketch using vector editor, or semi-automatic
creation using Artificial Intelligence or edge detection. All
topology files are stored in local storage for faster access.
Topology file will be used to query image file based on
image content.
b. Image Preview
An image preview is a small raster image in JPEG or GIF
format, created from original image. An image preview file
will be used as a sample file for image query using
similarity of spectral information. This preview is also used
as a preview output of image query.
c. File Name
A filename is a standard O/S file name.
d. URL / Search path
The URL / Search path is a pointer to file location. In local
storage or LAN, a search path is a volume name, followed
by a full-path directory name where the original image file
stored, for example : G:\IMAGEVAVHRR\JAVA. If data is
available through internet or intranet, a search path can be
replaced by a URL, using an IP number or Internet Address,
for example :
http://leviathan.tamu.edu:70/1 s/slides/Corel
e. Image Title
An image title is a string, for example 'NDVI for West Java'
f. Time Stamp
A time stamp is a valid time of data acquisition. The user
can refer to text-based metadata or header file to find this
information.
g. Image format
Image format information is a string that describe what
application should be used (or launched) to open this image,
for example ER-Mapper, PCI or ERDAS. If image file
format can be used for more than 1 application, this object
notes the image file type, e.g : BIL , LAC.
h. Coordinate
Coordinate system includes all projection information if
any.
i. Sensor
Sensor information contain sensor type and number of
bands.
4.3 Query Possibility
From database structure proposed above, we can make image
queries based on historical information, Image definition (title),
spectral similarity or image feature that is stored on spatial
information. Some example of query that is possible to be
developed :
Find image of East Java before 01 Jan 1988
Find NDVI of Indonesia between 01 Jun 1995 and 31 Dec
1995
Find image that similar to image "BALI"
Find image after 31 Dec 1997 that match this topology.
5. Future Work
Based on this conceptual design, development of this temporal
data handling requires a computer language that supports Object
Oriented programming and the ability to develop Object
Oriented Database. Java and C++ Language would be the best
language for this purpose. A Graphical User Interface (GUI)
should be considered as an interface. For internet / intranet
access, Java is easier implemented than C++.
Some future applications related to this topic are :
5.1 Image Query based on feature
Data Query is widely used in relational database, known as
Structured Query Language (SQL). In temporal database, data
query is currently under development. There are many
prototypes of a Temporal SQL. Similarly, Image Query Based
on Content or Feature is a new issue for multimedia objects.
5.2 Dynamic modelling and prediction using satellite
imagery
Considering the occurrence of time type information, we can
perform dynamic modelling and prediction using satellite
imagery. In current remote sensing and GIS application, It is
only possible to perform spatial non-temporal modelling.
For Satellite imagery that alfeady contains spatial and temporal
information, dynamic modelling and prediction can be
implemented using mathematical models.
Some remote sensing satellites can capture one specific area
everyday. We can develop much more dynamic models
incorporating temporal data using daily information from
satellite imagery.