DOI: 10.5281/zenodo.14193286
title: Band Ratio Mosaics from Airborne Hyperspectral Data at Aramo, Spain

description:  






Metadata information

 


Full Title
Band Ratio Mosaics from Airborne Hyperspectral Data at Aramo, Spain


Abstract


This dataset comprises results from the S34I Project, derived from processing airborne hyperspectral data acquired at the Aramo pilot site in Spain. Spectral Mapping Services (SMAPS Oy) conducted the airborne data acquisition in May 2024 using the Specim AisaFENIX sensor (covering VNIR-SWIR spectral ranges) over 17 flight lines. SMAPS performed geometric correction, radiometric calibration to reflectance, and atmospheric correction of the data. Subsequent processing steps included spectral smoothing with a Savitzky-Golay filter, cloud masking, bad pixel corrections, and hull correction (continuum removal).

Manual processing and interpretation of hyperspectral data is a challenging, time-consuming, and subjective task, necessitating automated or semi-automated approaches. Therefore, we present a semi-automated workflow for large-scale interpretation of hyperspectral data, based on a combination of state-of-the-art methodologies. This dataset results from the calculation of a series of band ratios applied to the images and their subsequent mosaicking into a TIFF file. The mosaics are delivered as georeferenced TIFF files that cover approximately 97 km² with a spatial resolution of 1.2 m per pixel. The NoData value is set to -9999, representing areas of cloud removal or missing flight lines. The projected coordinate system is UTM Zone 30 Northern Hemisphere WGS 1984, EPSG 4326.

Hyperspectral band ratios involve applying mathematical operations (such as division, subtraction, addition, or multiplication) among the reflectance values of different spectral bands. This technique enhances subtle variations in how materials absorb and reflect light across the electromagnetic spectrum. These variations are caused by electronic transitions, vibrations of chemical bonds (including -OH, Si-O, Al-O, and others), and lattice vibrations within the material's crystal structure.

By creating these mathematical combinations, specific absorption features are emphasized, generating unique spectral fingerprints for different materials. However, these fingerprints alone cannot definitively identify a mineral, as different minerals may share similar absorption features due to common chemical bonds or crystal structures. Spectral geologists use band ratios as a tool to highlight potential areas of interest, but they must integrate this information with other geological knowledge and analyses to accurately interpret the mineralogy of an area. 

This dataset includes nine spectral band ratios. The mathematical formulas used to calculate each ratio are provided below:

 

BR1 target Carbonate / Chlorite / Epidote

BR1  = ((C7 + C9) / (C8))

C7= Mean of bands between 2246.6 and 2257.55 nm

C8= Mean of bands between 2339 and 2345 nm

C9= Mean of bands between 2400 and 2410 nm

 

BR2 target Chlorite

BR2  = ((Cl1 + Cl2) / (Cl2))

Cl1 = Mean of bands between 2191.93 and 2197.4 nm

Cl2 = Mean of bands between 2246.63 and 2257.55 nm

 

BR3 target Clay

BR3  = ((C1 + C2) / (C2))

C1 = Mean of bands between 1590.32 and 1612.56 nm

C2 = Mean of bands between 2191.93 and 2208.35 nm

 

BR4 target Dolomite

BR4  = ((C6 + C8) / (C7))

C6= Mean of bands between 2186 and 2191 nm

C7= Mean of bands between 2246.6 and 2257.55 nm

C8= Mean of bands between 2339 and 2345 nm

 

BR5 target Fe2

BR5  = ((Fe2n + Fe2d) / (Fe2d))

Fe2n = Mean of bands between 721.85 and 742.48 nm

 

BR6 target Fe3

BR6  = ((Fe3n - Fe3d) / (Fe3n + Fe3d))

Fe3n = Mean of bands between 776.87 to 811.26 nm

Fe3d = = Mean of 3 bands around 610 nm

 

BR7 target = Kaolinite / clays

BR7 = ((K1 + K2) / (K3 + K4))

K1 = Mean of bands between 2082.27 and 2104.23 nm

K2 = Mean of bands between 2104.23 and 2115.2 nm

K3 = Mean of bands between 2159.07 and 2164.55 nm

K4 = Mean of bands between 2202.88 and 2208.35 nm

 

BR8 target Kaolinite2 / clays

BR8 = ((K1_2 + K2_2) / (K2_2))

K1_2 = Mean of bands between 2197.4 and 2219.29 nm

K2_2 = Mean of bands between 2159.07 and 2170.03 nm

 

BR9 target NDVI (Normalized Difference Vegetation Index)

BR9 = ((NIR - Red) / (NIR + Red))

NIR= Mean of bands between 776.87 and 811.26 nm

Red = Mean of bands between 666.87 to 680.6 nm



Keywords
Earth Observation, Remote Sensing, Hyperspestral Imaging, Automated Processing, Hyperspectral Data Processing, Mineral Exploration, Critical Raw Materials


Pilot area
Aramo


Language


English



URL Zenodo
https://zenodo.org/uploads/14193286


Temporal reference
 


Acquisition date (dd.mm.yyyy)
01.05.2024


Upload date (dd.mm.yyyy)
20.11.2024


Quality and validity
 


Fromat
GeoTiff


Spatial resolution
1.2m 


Positional accuracy
0.5m 


Coordinate system
EPGS 4326


Access and use constrains
 


Use limitation
None


Access constraint
None


Public/Private
Public


Responsible organisation
 


Responsible Party
Beak Consultants GmbH


Responsible Contact
Roberto De La Rosa


Metadata on metadata
 


Contact
Roberto.delarosa@beak.de


Metadata language
English