Published information on the costs of mapping processes is sparce and 
what has been published is difficult to compare as there are no 
standards for comparison. Furthermore even though some quantified 
information is available, as with the costing information, it is 
difficult to use as there are no standards. 
OBJECTIVE 
The objective of this paper is to examine in some depth the question of 
how to quantify the density of mapped features. Furthermore an 
explanation will be given of how the proposed feature density 
classification system will both solve the immediate quantification 
problem for the cost modelling task and serve a much wider purpose by 
establishing standards. 
It is therefore the intention of the authors, after the feature density 
classification system has been created and standards established, to 
propose a resolution to ISP to recommend the use of the standards in 
all relevant publications. 
APPROACH 
It is possible to develop a feature density classification system using 
two alternative approaches, 
by 1. actual quantification of all features, i.e. the measurement of 
the total length of line per unit area or the counting of 
individual features per unit area 
2. estimation by visual inspection using a series of standards 
The second alternative is to be preferred because of the considerable 
amount of effort required both in creating and using the first method, 
thus visual estimation appears more practical particularly at the 
estimation stage. The visual estimation method can be further 
considered in two alternative ways, 
as 2.1 a combined presentation of all features 
2.2 separate presentations of different features 
The second possibility, 2.2, has been chosen for the following reasons: 
in different areas completely different combinations of natural and 
cultural features occur (buildings, communications, hydrography, 
contours, etc.) 
separate estimates are expected to lead to a smaller error in the 
cumulative total (partial cancellation of individual estimating 
errors) 
easier application of resulting information to new circumstances. 
The proposed visual estimation method of classifying feature density 
will consist of a series of samples of mapping (each 12.5 cm x 12.5 cm) 
depicting selected features at certain scales. The essential elements 
of the system are: 
there will be 6 categories of planimetric features, namely 
a. buildings, b. communications, c. water features, d. vegetation 
and area symbols, e. boundaries and borders and f. point and symbol 
features. 
there will be 1 category of height feature, contours (information 
for spot heighting, profiling and DGM data collection will be 
derived from the contour classification.) 
the above features will have 5 classes of density : dense, medium 
dense, medium, medium open and open.