Hello, Dear scientific community,
I want to delineate hydrothermal alteration zones using an RGB Band combination on ASTER data. I've already consulted the literature on this topic and I found that 468 is the most relevant band combination for alteration and lithology discrimination. but I want to know if is there any mathematical method to calculate and select the most appropriate band combination.
Hi Mohammed Jalal Tazi , I don't really know if there is a method but it occurs to me that this would be a good task for deep learning techniques. However, I think it would be helpful to investigate in which wavelengths the hydrothermal alteration minerals reflect and absorb light and then combine those wavelengths taking into account the bands available to the sensor, in this case ASTER.
Spectral signature library: https://crustal.usgs.gov/speclab/QueryAll07a.php
You can apply PCA using the ASTER bands. Also, you can try to calculate feature importance using the raster values that can be extracted from different ASTER bands after a visual inspection of various color composite images (ASTER bands and PC bands). From the analysis of feature importance, you could get an idea of best optimum bands that can be used for your study. Mohammed Jalal Tazi
Thank you for your question! Selecting the right band combination for delineating hydrothermal alteration zones using ASTER data is a crucial step in your analysis. While there isn't a specific mathematical formula to determine the "most appropriate" band combination, you can consider various techniques to make an informed choice. Here's a general approach:
1. Spectral Analysis:
- Examine the spectral characteristics of the bands in ASTER data.
- Understand the wavelengths at which different materials, such as hydrothermal alteration minerals, exhibit distinctive spectral responses.
- Pay attention to absorption features in the spectrum.
2. Literature Review:
- As you've already mentioned, consulting the literature is a great starting point. Look for studies and research papers that discuss band combinations specifically for hydrothermal alteration mapping using ASTER data.
- Researchers often share their successful band combinations in these papers.
3. Use of Spectral Indices:
- Some spectral indices, like the Normalized Difference Vegetation Index (NDVI) or the Iron Oxide Ratio (IOR), can be applied to identify specific materials or alterations.
- Experiment with these indices and band combinations to see which ones provide the best results for your study area.
4. Trial and Error:
- Don't hesitate to try different band combinations and see which one yields the most visually distinctive and interpretable results for hydrothermal alteration zones.
- You can use software tools, such as remote sensing packages in GIS software or specialized remote sensing software, to manipulate the bands and create RGB composites.
5. Principal Component Analysis (PCA):
- PCA can help in data dimensionality reduction and can provide insight into which bands contain the most information.
- After performing PCA, you can select the principal components that highlight alteration features.
6. Collaboration:
- Collaborate with experts in the field of remote sensing and geological exploration. They may have valuable insights and experience in band combination selection.
While there is no one-size-fits-all mathematical method, the selection of a band combination depends on the specific characteristics of your study area and the geological context. Experimentation and consultation with experts are often essential to finding the most suitable band combination for your hydrothermal alteration mapping project.
Wishing you success in your research on hydrothermal alteration zones using ASTER data! If you have any more questions or need further guidance, please feel free to ask.
- Badges
- Science topic
- Similar topics
- Analytical Chemistry
- Column