Abstract
The availability of the large volume of remote sensing data has allowed for the developing of several automated algorithms for detecting linear geological features and more reliable analysis. However, most of the algorithms focus on edge detection and tone change on a satellite image, which represents all geological and non-geological features. In this study, a topographic fabric algorithm, which calculates the slope and aspect at each point in a DEM, is applied for automatically geological linear features mapping in Bau Goldfield, Malaysia using the new version of the Shuttle Radar Topographic Mission (SRTM) DEM. A series of topographic fabric input parameters was tested using different combinations of input values in order to decide the optimal parameters that provided the suitable detection parameters, best fit and the highest accuracy. Comparison with the geological map demonstrated that the tested parameters made the algorithm able to automatically detect geological structures.
Acknowledgements
The authors would also like to thank the Earth Remote Sensing Data Analysis Centre (ERSDAC), Japan, the NASA Land Processes Distributed Active Archive Center and the User Services, USGS Earth Resources Observation and Science (EROS), and the Consortium for Spatial Information (CSI) of the Consultative Group for International Agricultural Research (CGIAR) for providing and distributing remotely sensed data.
Disclosure statement
No potential conflict of interest was reported by the authors.