It appears you don't have support to open PDFs in this web browser. To view this file, Open with your PDF reader
Abstract
Mineral spectral library (MSL) is the foundation of hyperspectral remote sensing, and a significant tool of storing and managing massive mineral spectral data to facilitate the matching or identifying of unknown rocks and minerals conveniently and fast. However, mineral spectral data are scattered and stored in different spectral libraries worldwide, which behave different spectral resolutions, mineral categories and measurement parameters, and hinder its application in field investigation, mineral identification, landcover identification and geological mapping. An integrated MSL using shared data is developed currently in Central South University, China, to improve the properties of MSL. We collected the shared spectral data and related information (e.g., mineral attribute data, spectrometer information, etc.) worldwide, performed data cleaning measures to retain the qualified spectral data and consolidated all the data in a common framework so as to establish a reliable and comprehensive dataset, and developed an integrated MSL for data management and diversified applications. The user can analysis the target spectrum with the spectrum absorption characteristic parameters, and match the measured spectral curve with the reference spectrum in the integrated MSL to find the most similar spectrum curve. It’s crucial to note that a new spectrum classifier was designed to limit the scope of matching for improving the efficiency of identification when the experimental sample lacks the specific information. The integrated MSL is developed in B/S and C/S website environments. A demonstration of functions of the integrated MSL and its preliminary applications are introduced in the article.
You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer
Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
Details
1 School of Geosciences and Info-Physics, Central South University, Changsha, China; School of Geosciences and Info-Physics, Central South University, Changsha, China; Laboratory of Geo-Hazards Perception, Cognition and Predication, Central South University, Changsha, China