Mineral Exploration Methods
Using Satellite Data
Band Ratios using ArcGIS and Remote Sensing
- By Sattam Chakraborty
Founder: GeoNgiser
email: contact.sattam@gmail.com
Source of
Satellite Data
For the Mineral Exploration, using Remote Sensing, we will
mainly the Satellite Date from the following sources:
1. Landsat – 8/9
2. Sentinel – 2
We will use the various specific Bands to find the respective
Minerals. The Bands will be processed in the ArcGIS Software,
using the Raster Calculator Tool. Finally the Mineral Map will be
prepared.
Band Ratio Methodology
For, the specific Mineral/ore, we use specific Band
Ratio as follows:
Iron : SWIR1 / NIR
Landsat : Band 6 / Band 5
Sentinel : Band 11 / Band 8
Iron Oxide : Red / Blue
Landsat : Band 4 / Band 2
Sentinel : Band 4 / Band 2
Clay : SWIR1 / SWIR2
Landsat : Band 6 / Band 7
Sentinel : Band 11 / Band 12
ArcGIS Methodology
In Arc Tool Box  Spatial Analyst  Math
Algebra  Raster Calculator
For Iron : Float (“Band 6”) / Float (“Band 5”)  Save Output as “Iron.Tif”
For Iron Oxide: Float (“Band 4”) / Float (“Band 2”)  Save Output as “Iron
Oxide.Tif”
For Clay : Float (“Band 6”) / Float (“Band 7”)  Save Output as “Clay.Tif”
In Arc Tool Box  Spatial Data Management Tools  Raster 
Raster Processing  Composite Band (Iron.Tif + Iron Oxide.Tif
+Clay.Tif) = Mineral Map.Tif
ArcGIS Methodology
Iron
ArcGIS Methodology
Iron Oxide
ArcGIS Methodology
Clay
ArcGIS Methodology
ArcGIS Methodology
Mineral Map Interpretation
Red : Iron , Green : Iron Oxide , Blue : Clay
Band Ratio Mineral Exploration
The Satellite Image Surveys are the first step in any exploration methods.
The Remote Sensing Study, helps us to utilize the various Satelllite images, whether from Landsat
or Sentinel.
In this Paper we have used the Landsat - 8 images of the Kendujhar District in Odisha. Kendujhar
is also known as the “Iron Town”.
The region around Barbil has one of the largest deposits of iron ore and manganese ore in the
world.
We have used the various Bands and used the “Band Ratio” Method for Mineral Exploration.
We have generated the maps of Iron, Iron Oxide and Clay (Soil). Finally, we have formed the
Composite “Mineral Map”.
The final “Mineral Map” shows the Iron in Red color, Iron Oxide in Green color and Clay in Blue
color.
Thus, from the red areas in the Mineral Map, we can easily detect the areas with highest Iron
Potential areas. Thus, it is one of the best approaches in the Mineral Exploration