Item talk:Q245928
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "CreativeWork", "additionalType": "Conference Paper", "name": "Spectroscopic remote sensing for material identification, vegetation characterization, and mapping", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70159021", "url": "https://pubs.usgs.gov/publication/70159021" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70159021 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.1117/12.919121", "url": "https://doi.org/10.1117/12.919121" } ], "inLanguage": "en", "datePublished": "2012", "dateModified": "2021-10-27", "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.", "description": "839014", "publisher": { "@type": "Organization", "name": "SPIE" }, "editor": [ { "@type": "Person", "name": "Shen, Sylvia S.", "givenName": "Sylvia S.", "familyName": "Shen" }, { "@type": "Person", "name": "Lewis, Paul E.", "givenName": "Paul E.", "familyName": "Lewis" } ], "author": [ { "@type": "Person", "name": "Kokaly, Raymond F. raymond@usgs.gov", "givenName": "Raymond F.", "familyName": "Kokaly", "email": "raymond@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0003-0276-7101", "url": "https://orcid.org/0000-0003-0276-7101" }, "affiliation": [ { "@type": "Organization", "name": "Crustal Geophysics and Geochemistry Science Center", "url": "https://www.usgs.gov/centers/geology-energy-and-minerals-science-center" } ] } ], "funder": [ { 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