Data Structure Patterns: 
1) Gridded pattern (X,Y spacings remain constant and only Z, ie., one 
dimension need to be recorded); 
2) Sectional pattern (eg., in Z=constant or any arbitrary plane, ie., 
only two dimensions need to be recorded); or 
3) Irregular pattern (where all three coordinates need to be recorded) 
is used in view of irregular surfaces or other requirements. 
In the above, the interpolation methods or surface fitting techniques 
would depend on the accuracy requirements, data density and distribution. 
All these may lead into computer graphics for the purpose of visual dis- 
play and illustration. 
Information required in such non-topographic applications can be cate- 
gorized as follows: 
a) Mensuration Parameters, eg., areas, volumes, curvature, gradient, 
shape, etc. 
b) Change Parameters, eg., velocity, acceleration, volume change, etc. 
c) Statistical Parameters, eg., area, volume or mass distribution, 
time variation, etc. 
d) Associated Parameters, eg., stress, forces, etc. 
Excepting the first one (mensuration), the rest are all derived from the 
raw photogrammetric data. Throughout these, however, the Software poten- 
, tials are. enormous. Generally speaking, an efficient, adequate and app- 
ropriate file handling system is all that is required in many of the nu- 
merous variety of applications. 
PROJECT DEVELOPMENT WITH VALUE-ENGINEERING 
In today's economy, technological, circumstantial and competitive fac- 
tors interact in a very complicated fashion. For example, a production 
schedule has to take account of customer (sponsor) demand, requirements 
for materials, capacities of equipment, possibilities of equipment non- 
availability (and failures), data production limitations, etc. It is not 
easy to prepare a schedule that is both realistic and economical. 
The other reasons for complexity are that the organizations may be 
pursuing inconsistent goals, the responsibility for making decisions may 
be diffused between organizations and the socio-economic environment in 
which the organization operates may be uncertain. 
There are generally many ways to approach any problem. Furthermore, 
there is often no clear line of demarkation between the work of the phot- 
ogrammetrist and the user of the photogrammetric data. Such an user can 
be from any field, such as, industrial engineering, space science, X-ray 
technology, metallurgy, surgery, etc. Because of such diversities, the 
photogrammetrist can not follow any standard procedure. Each job may be 
uniquely different from the other. This demands careful development and 
designing of such projects. Such innovations are best done by the VALUE 
ENGINEERING (VE) approach. Details of such VE approach is presented in 
Figs 2 and 3. There are four basic phases involved here: (1) Informa- 
tion phase, (2) Speculative phase, (3) Analytical phase, and (4) Appli- 
cation phase. See Mudge [8], for the Value Engineering concepts. 
Such a project development, however, becomes ineffective and ineffici- 
ent if its cost-effectiveness is inadequate.