Spectroscopic remote sensing for material identification, vegetation characterization, and mapping

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Edited by: Paul E. Lewis and Sylvia S. Shen

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Abstract

Identifying materials by measuring and analyzing their reflectance spectra has been an important procedure in analytical chemistry for decades. Airborne and space-based imaging spectrometers allow materials to be mapped across the landscape. With many existing airborne sensors and new satellite-borne sensors planned for the future, robust methods are needed to fully exploit the information content of hyperspectral remote sensing data. A method of identifying and mapping materials using spectral feature analyses of reflectance data in an expert-system framework called MICA (Material Identification and Characterization Algorithm) is described. MICA is a module of the PRISM (Processing Routines in IDL for Spectroscopic Measurements) software, available to the public from the U.S. Geological Survey (USGS) at http://pubs.usgs.gov/of/2011/1155/. The core concepts of MICA include continuum removal and linear regression to compare key diagnostic absorption features in reference laboratory/field spectra and the spectra being analyzed. The reference spectra, diagnostic features, and threshold constraints are defined within a user-developed MICA command file (MCF). Building on several decades of experience in mineral mapping, a broadly-applicable MCF was developed to detect a set of minerals frequently occurring on the Earth's surface and applied to map minerals in the country-wide coverage of the 2007 Afghanistan HyMap data set. MICA has also been applied to detect sub-pixel oil contamination in marshes impacted by the Deepwater Horizon incident by discriminating the C-H absorption features in oil residues from background vegetation. These two recent examples demonstrate the utility of a spectroscopic approach to remote sensing for identifying and mapping the distributions of materials in imaging spectrometer data.

Additional publication details

Publication type Conference Paper
Publication Subtype Conference Paper
Title Spectroscopic remote sensing for material identification, vegetation characterization, and mapping
DOI 10.1117/12.919121
Volume 8390
Year Published 2012
Language English
Publisher SPIE
Contributing office(s) Crustal Geophysics and Geochemistry Science Center
Larger Work Type Conference Paper
Larger Work Title Algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XVIII: 23-27 April 2012, Baltimore, Maryland, United States
Conference Title Algorithms and technologies for multispectral, hyperspectral, and ultraspectral imagery XVIII
Conference Location Baltimore, Maryland
Conference Date April 23-27 2012
Online Only (Y/N) N
Additional Online Files (Y/N) N