Imaging Spectrometry for Geological Applications

Abstract

Reflectance and emittance spectra have been used for many years to obtain compositional information about the Earth's surface. Electronic transition and charge transfer processes associated with transition‐metal ions such as Fe, Ti, Cr, and so on produce diagnostic absorption features in the visible and near‐infrared (VNIR) wavelength region of the spectra of minerals and rocks, while vibrational processes in H 2 O and OH − produce fundamental overtone absorptions in the shortwave infrared (SWIR) portion of the spectrum. Field and laboratory studies have demonstrated that reflectance spectroscopy can be used for mineral identification and further geological studies. The translation of these measurements to imaging data led to the development of the field of imaging spectrometry in remote sensing. Imaging spectrometers acquire images in a large number of narrow contiguous spectral bands to enable the extraction of reflectance spectra at a pixel scale that can be directly compared with similar spectra measured either in the field or in a laboratory. In this chapter, the use of imaging spectrometer data for geological applications is discussed by describing the processing chain of data analysis from the raw data acquisition to prospective applications. Several topics are addressed. An appraisal of future spaceborne imaging spectrometer missions and potential prospective applications provides insight into this vastly growing field of research.

Spectral characteristics of salt-affected soils: A laboratory experiment

“…In both cases, analysis was restricted to the wavelength range between 1000 and 2400 nm, since most of diagnostic spectral signatures of salt minerals occur in NIR and SWIR regions. As regards the absorption features, characteristics such as depth, depth position (k d ) and area of the absorption feature were considered (Kruse, 1995;Van der Meer, 2000). These characteristics were calculated from continuum-removed spectra to enhance absorption features in the recorded soil reflectance spectra.…”

Classification by diagnosing all absorption features (CDAF) for the most abundant minerals in airborne hyperspectral images

“…There are varieties of silicas different in names but more or less with high similarity in the absorption features in their reflectance curves. Adding to this, the soils reflectance with special characteristics due to their physical and chemical particulars while their main constituents are minerals, organic materials, air, and water [10,16]. These pixels were classified with 100% accuracy using CDAF technique.…”

Exploring the relationship between vegetation spectra and eco-geo-environmental conditions in karst region, Southwest China

“…As band widths are narrow and range of spectra is wide, subtle differences in spectral features can be extracted and used for mapping physical and chemical properties of bare substrates (van der Meer et al 2001;Aspinall et al 2002). The use of spectral characteristics of substrates is not accessible if substrates are covered by vegetation.…”