Raster Image Data:
satellite data
scanned aerial photographs
Expert Knowledge:
concepts end methods
from remote sensing, geo-science
and Image processing
Known Geographic Information:
spetiai data
factual data
Figure 1: Remote sensing as a knowledge-based analysis task
X DEVELOPING AN EXPERT SYSTEM TO
ASSIST REMOTE SENSING TASKS
Instead of developing new data processing methods in
remote sensing, the RESEDA project is exploring exi
sting operational methods in state-of-the-art remote sen
sing projects. Our objectives are to embed these methods
into a consistent theoretical framework and to represent
them in a knowledge base on a computer system. To this
end, we are developing an intelligent advisory system,
called the RESEDA Assistant, which makes use of this
software knowledge base in order to assist the user in
efficiently performing remote sensing tasks.
The main purpose of the RESEDA Assistant is to plan the
sequence of computations necessary for a given analysis.
For that purpose, the user specifies the available data and
the desired data. The available data may include sensor
data and some additional geographic information repre
sented in a resident database or to be entered by the user.
From these specifications, the RESEDA Assistant com
putes a set of processing plans, that is, sequences of
computations. These computations may consist of ima
ge-processing operators, statistical evaluations, or mani
pulations of spatial data. In the first stage of the RESEDA
project, the computed processing plans will be printed out
by a prototype system called the RESEDA Advisor and
will have to be executed explicitly by the user. The final
system, the RESEDA Assistant, will display a set of
alternative processing plans as a menu. After selecting
one of the menu items, the respective processing plan will
be executed automatically by a plan interpreter. In this
context, automatic execution means that the appropriate
data processing programs are called with correct argu
ments in correct sequence; the programs being called
may nonetheless run in interactive mode and require
intervention by the user, such as digitizing training areas
for a supervised classification. Serving as a knowledge-
based interface to traditional analysis software, the RESEDA
Assistant resembles to the Analyst Advisor developed at
the CCRS in Ottawa (Goodenough, 1987) that interfaces
the LDIAS data processing system. However, the con
cepts of these systems differ, since RESEDA focuses
rather on the methodological knowledge of a remote
sensing expert than on the facilities offered by a given
data analysis system.
The global control strategy of the RESEDA expert sy
stem is backward chaining. That is, the system first asks
for the desired information. The desired information may
be described by its format (e.g., image, map, or factual
data), its accuracy (i.e., qualitative or quantitative results
required), and the subject of interest (i.e., which target
classes or target attributes are to be recognized). The
system tries to activate processing models that are able to
compute the desired information from other data. If this
data is not present, the system recursively tries to activate
processing models for computing the data. The process
stops when the system tries to determine data items that
are explicitly labeled as so-called primary data. In this
case, the user is asked whether the primary data in
question is available. If the user says no, the system tracks
back and tries to activate different processing models.
The advantage of the backward-chaining strategy is that
the user is asked for available data only if this is effecti
vely necessary. An alternate design idea, which is not to
ask for the available data at all, was rejected, since it
would have required the implementation of a complete
data management system. This was found not to be
feasible because of the great number of foreign data
sources that can be made available on demand, such as
remote sensing data, geographic databases, raster-scan
ned maps, or even printed maps to be digitized manually
by the user.