33], The recent developments in worldwide environ
mental information systems make meta-data an urgently
necessary tool to exploit the value of these data [74].
The advantages of an explicit representation of the data-
and program structures are obvious [91]:
simplification of program control;
ability for abstraction, due to the availability of speciali
zation hierarchies;
ability to explain reasoning processes;
simplification of knowledge acquisition;
better software maintenance.
In our context the problem of achieving semantic integrity
may be solved by several means [88]
making meta-information explicit already increases
the transparency of image analysis procedures. Meta-
information in a first step consist of data about: time
of measurement, accuracy, source, derivation for
mula, history, etc. It may be stored as text or explicitly
coded which then allows direct manipulation by an
analysis program;
data - meta-data synchronization aims at updating
meta-data together with changes in the data- or object
model;
meta-data comparison may be used to find semantic
equivalences or heterogeneities and possibly resolve
conflicts. This of course requires a formalized repre
sentation of the meta-data e.g. [28 and 29];
meta-data generation may help keeping the meta-data
consistent and up to date. This immediately is avail
able for meta-information such as time of creation or
accuracy of results;
relevance evaluation may be used to assess the sen
sitivity of reasoning results with respect to certain
model assumptions and may be performed on the
meta-data. This is equivalent to algebraic (i.e. theo
retical) derivations of the sensitivity of mensuration
designs, here performed on more complex image
analysis procedures.
This discussion wanted to stress the importance of ex
plicitly storing the object, image, analysis and interpre
tation models in a way such that they are accessible by
computer programs [76]. This may be a long term goal,
but it needs to be approached soon in order to increase
the transparency of the image interpretation results and
to make them more useful for other contexts.
A future
No conclusions can be drawn, no future can be pre
dicted both would suggest solutions to be available for
solving the difficult problems sketched in this paper. We,
however, can take possibilities and opportunities future
essentially consists of. A possible future of photogram-
metric research may be guided by the following goals:
image interpretation can be taken to be the central
issue in photogrammetric research. This involves the
extensive use of tools from computer graphics for
forward modelling the imaging process, from image
understanding for modelling the analysis process and
from the research in man-machine-interfaces, for
modelling the cognitive aspects of computer programs
and human analysts and their interaction;
semantic models seem to replace the geometric/
physical models dealt with during the last 100 years of
photogrammetric research. They need to explicitly
contain knowledge about user needs and of meta-
NGT GEODESIA 93 - 8
information of all kind. Languages for smoothly inter
acting with object, analysis and perception models
seem to be a possibility to adequately represent this
knowledge;
the integration with the neighbouring disciplines ap
pears to give the right boundary conditions for a fruit
ful development. All aspects need to be covered:
applications (geography, geology, ecology, basic
sciences (physics, computer science, cognitive sci
ence, control, and techniques (pattern recogni
tion, computer vision, artificial intelligence, It
seems to be high time to realize this integration not
only in scientific conferences or meetings, but in joint
projects, interdisciplinary research teams and last
but not least in the corresponding curricula.
Our field of research becomes more and more exciting.
We should grasp the fantastic opportunities in order to
provide tools for solving the huge and urgent problems.
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