Drainage pattern classification by texture analysis
Results of Case Studies
- Fig 5 shows the change of energy by window size in kitami area. As the window size become larger, the high frequency components become invisible, and classification of drainage systems get better because the noises decrease proportional to the window size.
- Fig. 6 shows the change of energy by grid size in KITAMI area. As the grid size become larger, the high frequency components also become invisible. The classification results of 80m grid size was better than the others.
- Fig 7 shows the change of energy by quantization level. As the quantization level become smaller, the variation of result become greater. The classification result with level slicing by 80m was better than the others. In this case, the size of co-occurrence matrix was 20*20 pixels.
- A combination of the homogently and correlation gave better results that the others for classification of drainage systems.
Comparison with Drainage Systems
A plain, dendrite drainage, parallel drainage in gentle area and parallel drainage in steep area were selected as the study area in SO area. And parallel drainage in steep area was selected as those in those in KITAMI area.
Fig. 8 and Fig.9 show the histograms of homogeneity and correlation in those areas respectively. As shown in fig 10, drainage systems were classified by the parallel piped classification method.
Fig. 11 and Fig. 12 shows the results of the classification by experts and that by texture analysis respectively. The mapping discrepancies between computer generated pattern and expert's made pattern were shown in Table 2.
Table 2 Discrepancies of Classification in KITAMI Area
| drainage systems |
Discrepancies |
parallel drainage
dendritic drainage in gentle area
dendritic drainage in steep area
unknown |
47.8%
34.9%
34.9%
25.4% |
Conclusions
- Drainage pattern classification has been developed by the authors using texture analysis. A combination of correlation and homogeneity gave the best results as compared with other types of texture. Computer-generated drainage patterns would be very useful for geological survey.
- There are some differences between the classified image by texture analysis and that by experts. Such differences exist mainly in the areas where DEM is not correct. If DEM is correct, it would be expected that classification accuracy of drainage systems would become higher.
Reference
- Japan Association of Remote Sensing. "Processing and Analysis of Images", 1986
