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Mapping white micas and their absorption wavelengths using hyperspectral band ratios [An article from: Remote Sensing of Environment]
Book Details
PublisherElsevier
ISBN / ASINB000RR8GSY
ISBN-13978B000RR8GS8
AvailabilityAvailable for download now
Sales Rank99,999,999
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Remote Sensing of Environment, published by Elsevier in 2006. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
Measuring the wavelength position of the absorption feature of white micas in the 2200nm region is a useful tool in mapping the affects of hydrothermal alteration. However, this subtle wavelength shift is difficult to measure accurately using unmixing and matching algorithms that rely on spectral end members, because the wavelength position is uncorrelated to the general shape of the reflectance spectra of white micas. An alternative method is presented that uses pixel-dependent information only and that is based on extracting diagnostic spectral information of the mineral of interest through band ratios. Multiple regression analysis is then used to determine the relation between band ratios calculated from airborne imaging spectroscopy and the absorption wavelength of white micas measured in rock samples on the ground. The complicating effects of vegetation mixing with mineral signatures at the pixel level are addressed through a combination of band ratios that target the respective diagnostic absorptions. With this method the presence of white micas at the earth surface is estimated from two band ratios, L"2"1"6"8" "n"mL"2"1"8"5" "n"m and L"2"0"0"5" "n"mL"2"0"7"9" "n"m, where band ratio L"2"0"0"5" "n"mL"2"0"7"9" "n"m is proportional to the abundance of cellulose in spinifex vegetation. The absorption wavelength of white micas is then estimated from the two band ratios L"2"2"2"0" "n"mL"2"2"0"2" "n"m and L"2"2"3"7" "n"mL"2"2"2"0" "n"m. The results of both band-ratio regression analyses can then be combined to show predicted wavelengths of white mica in the areas of highest probability of containing white mica.
Description:
Measuring the wavelength position of the absorption feature of white micas in the 2200nm region is a useful tool in mapping the affects of hydrothermal alteration. However, this subtle wavelength shift is difficult to measure accurately using unmixing and matching algorithms that rely on spectral end members, because the wavelength position is uncorrelated to the general shape of the reflectance spectra of white micas. An alternative method is presented that uses pixel-dependent information only and that is based on extracting diagnostic spectral information of the mineral of interest through band ratios. Multiple regression analysis is then used to determine the relation between band ratios calculated from airborne imaging spectroscopy and the absorption wavelength of white micas measured in rock samples on the ground. The complicating effects of vegetation mixing with mineral signatures at the pixel level are addressed through a combination of band ratios that target the respective diagnostic absorptions. With this method the presence of white micas at the earth surface is estimated from two band ratios, L"2"1"6"8" "n"mL"2"1"8"5" "n"m and L"2"0"0"5" "n"mL"2"0"7"9" "n"m, where band ratio L"2"0"0"5" "n"mL"2"0"7"9" "n"m is proportional to the abundance of cellulose in spinifex vegetation. The absorption wavelength of white micas is then estimated from the two band ratios L"2"2"2"0" "n"mL"2"2"0"2" "n"m and L"2"2"3"7" "n"mL"2"2"2"0" "n"m. The results of both band-ratio regression analyses can then be combined to show predicted wavelengths of white mica in the areas of highest probability of containing white mica.
