PHOTOINTERPRETATION, UNSUPERVISED OR SUPERVISED CLASSIFICATION ? 
FRIEDRICH QUIEL 
Institut für Photogrammetrie und Topographie 
Universität Karlsruhe 
ENGLERSTRASSE 7 
7500 KARLSRUHE GERMANY 
ABSTRACT 
Remote sensing data contain a wealth of information and a variety of evaluation tech- 
niques are used. The most suitable procedure should be selected to extract the information 
necessary to solve a specific problem. To reach this goal, the requirements of the 
application and the possibilities of the evaluation procedure should match as close as 
possible, 
Different sets of requirements are discussed and examples in geology and land use mapping 
are used to demonstrate the possibilities and limitations of photointerpretation, unsuper- 
vised and supervised classification. 
Common problems in photo interpretation and classification are feature selection, 
determination of characteristic values for classes, need for ground information and 
incorporation of additional information. 
Classifications are mainly restricted to spectral and/or textural classes. The additional 
use of size, shape, pattern etc. would expand the application of classification techniques 
to other problems and data. 
The combination of photointerpretation and classification is a very powerful tool to 
economically meet the requirements for many problems. It can be supported very 
effectively by the use of different data, e.g. LANDSAT and aerial photographs. 
INTRODUCTION 
With the availability of digital remote sensing data, computer supported digital 
evaluation techniques become increasingly important. In using remotely sensed data to 
solve a specific problem, a decision must be made, which of the different evaluation 
techniques and data are most suitable for the task at hand. It is therefore appropriate to 
discuss the advantages, disadvantages, requirements and limitations of the major techniques, 
i.e. photointerpretation, supervised and unsupervised classification in general terms.