Image optimization versus classification — An application oriented comparison of different methods by use of thematic mapper data

Image optimization and classification procedures are comparatively analyzed and discussed relative to their possibilities and limitations for distinct applications. To meet the objectives LANDSAT Thematic Mapper data of two test-sites in different climatic areas (Saudi-Arabia and southwest Germany) have been chosen.

For optimized presentation of TM-imagery, a basic concept was developed through which structural as well as spectral image contents can be enhanced within one product. By choice of bands and processing parameters the concept can be modified and fitted to various applications. Supervised and unsupervised classification methods are applied, to separate surface phenomena by use of original, enhanced, and preprocessed data. Comparative evaluations have shown, that both methods give best results using not more than three spectral bands for one evaluation step. By qualitative and quantitative analysis it could be demonstrated, that classifying with original, enhanced or preprocessed components leads to the same results. For geologic applications in arid areas a standard band combination could be defined, which offers optimized conditions for rock discrimination and possibilities for separating diagnostic features. Concerning landuse applications, the various spectral behaviours of different surface phenomena cannot be meaningfully represented within one optimization product. The lack of structural (relief) information on classification results however could be compensated by special merging techniques under additional use of image optimization products.