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International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B7. Istanbul 2004
environmental problems; inadequate political will and
inappropriate legislative and administrative frameworks in
which responsibility for air quality management is divided
between a number of government ministries and the local
administrations are some of the reasons.
Since 1995 the Department of the Environment (DOE) and
the Air Quality Control Company (AQCC) of Iran have
monitored some parameters of air pollution continually.
Figure | shows the locations of air pollution monitoring
stations in Tehran.
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Figure 1.The Locations of air pollution stations in Tehran
Regarding various environmental standards defined in the
world; in this paper PSI (Pollutant Standard Index) standard
have been used.
1, 71
p = x Is X (C, = BP, ) + Ly
B Hi ^y
o
[,= Pollution index
[= PSI related to high break point
[j 47 PSI related to low break point
BPy;- High break point >= C,
BP,, Low break point <= C,
C,= Pollutant concentration
3. TEMPORAL GIS
We live in a dynamic world. Every thing around us changes
at different rates. Most of the phenomena change over time
so spatio-temporal GIS have been developed [Nadi, 2003.].
Traditional GIS applications deal with sets of static objects,
many spatial referenced objects change with time and more
and more applications referred to location and time are
considered; therefore the necessity of using spatio-temporal
GIS is inevitable. A spatio-temporal GIS aims to process,
manage and analyze spatio-temporal data [Yuan, 1996.].
Storage of captured data from monitoring stations in
temporal database helps us to optimally manage air quality.
Air pollution depends on location and time. Capacity of each
information system is extensively dependent on its data
model [Yuan, 1996.]. A data model should define data type,
relationship, operations and rules to maintain database
integrity [Date, 1995.]. Considering large amount of
monitored data, designing and normalizing database is
seriously recommended. A rigorous data model must
anticipate spatio-temporal queries and analytical method to
be performed in the temporal GIS [Yuan, 1996.].
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From temporality point of view, there are two types of
information, static and dynamic, which must be modeled
under a temporal GIS. In this research air pollution
monitoring stations are mostly static and the value of
pollutants over the time is dynamic.
Temporal modeling in GIS started with time stamping layers
and then goes into process based modeling. This, trend is
represented below [Nadi, 2003]:
- Time stamping
e Snapshot model
e Space time composite (STC)
e Spatio-temporal objects
- Event or process-based
e Event based spatio-temporal data model (ESTDM)
e Domain oriented spatio-temporal data model
Air quality changes continually and we can monitor different
values over the time for each pollutant .This changes should
be stored in the database so snapshot model is chosen. In
snapshot model, each layer is composed of temporally
homogeneous units. In the other word, in the snapshot model,
when an event occurs, new layer will be constructed and
occurrence time will be stamped to the layer (all of the
information, changed or not changed, will be stored in the
layer) [Nadi, 2003].
An ideal spatio-temporal database is mentioned as a database
that has the ability to keep the track of changed data besides
having the normal function essential to every spatial
database. In addition to the process of updating geographical
objects, keeping the valid topological (either temporal or
spatial) relationship are also operational [Roshannejad,
1996].
4. GIS IN AIR QUALITY MANAGMENT
By doing air quality modeling in a GIS environment, the
output of the pollutant records can be obtained in the form of
spatial records.
GIS science and technology is capable of supporting the
development of geospatial air quality models. For modeling
in GIS environment, AQMS may consider as be thought of
comprising three phases namely, monitoring, development of
DSS and execution. The milestone capabilities of GIS for
AQMS are as fallow [Hussain, 2003.]:
a) Tolocate the monitoring station
b) To develop geospatial air quality models
c) To develop spatial decision support system (SDDS).
5. METHODOLOGY
In this research the monitored environmental data from seven
stations in Tehran in 2002 were collected, and then the
accuracy of the data was assessed by using statistical
analysis. To detect and remove errorly recorded data, the
specific domain of each pollutant should be determined.
Accuracy of instrument in observation, record and transmit
affect on data quality. Other parameter affecting data quality
should be determined.
The data was structured and stored in the temporal database
while Tehran's digital map at a scale of 1:2000 was being
uploaded and topologically structured using ArcView and
ArcInfo GIS software. The location of stations on the map
was determined. Attribute data were assigned to spatial
objects and the system became ready for spatio- temporal
analysis and management.
Fig
