Information Technology Reference
In-Depth Information
Fig. 3.
Relational View of Federated GIS+DIS
{
H
D
C
V
d
c
c
v
m
rhr
o
q
rhr
0
d
v'
m'
rhr
rhr'
o
q'
q"
rhr
o
2
1
d
c'
v
m"
o'
From Relational
{
d'
c
v"
sm
nil
o"
q"'
rhr
to the CDV Functional View
Category/Type
Domain
c
q1
o1
Version
v'
v
d
q2
o2
q3'
o3'
o3
m'
m
q3
o = o1+o2+o3
q = q1;q2;q3
rhr
>From these we are then, somehow, able to extract, or as we shall call it: lter,
representations of resources, one-by-one. Typically, however, the (for example)
remotely sensed data also contains a confusing aggregation of other data that
somehow must be screened away.
type
Coordinate =
Real
Real
Real
Area = Coordinate
-set
SpaResMap = Area
m
(RR
m
Fuzzy)
AIs = A
I
-set
Filter = (AIs
Data)
!
(AIs
SpaResMap)
Filters =
m
Filter
So what we have, usually in a geographic information system are maps, or images,
of complex aggregations of Data, and what we want are simple recordings, in the
form of well-dened Spatial Resource Maps of resources. By a Spatial Resource
Map, we understand a mapping from a an area, that is: a set of three dimensional
coordinates to a map from Resource Representations to Fuzzy qualiers. The
idea is that the spatial map \cleanly" represents only those resources for which
certain attribute values are present and within given indicator ranges. We choose
to map from an area in order to capture averaging properties. Thus a Filter is a
function from a triple of Attribute designators, Indicator ranges and (for example
an image of remotely sensed) Data to a Spatial Resource Map.
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