Answers are grounded in this paper and cite their sources.
Explores GLCM parameters' impact on lithological mapping, suggesting improved classification accuracy with optimal settings.
Gray Level Co-Occurrence Matrix (GLCM) textures demonstrate great potential in lithological mapping, yet the influence of GLCM parameters (window size, distance, and angle) on mapping lithology using Sentinel-1 images has never been thoroughly explored. Textures calculated with different GLCM parameters using Sentinel-1 data under different incidence angles were used for lithological classification in a semi-arid area. We found large incidence angle can improve the classification result slightly; larger window size and smaller distance with an appropriate angle can lead to a higher classification accuracy; different parameter combinations can result in a maximum difference in classification accuracy of about 10%, and the highest accuracy (76.27%) is achieved by using a window size of 15*15 with a distance of 1 at the angle of 0°. Our study enhances the application of Sentinel-1-derived GLCM textures in geological fields, the promising classification accuracy indicates more opportunity for lithology discrimination using SAR data compared to earlier studies.
No takes yet. Share an insight, caveat, or question.
Lu et al. (2024) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: