Next Article in Journal
Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery
Previous Article in Journal
A Non-MLE Approach for Satellite Scatterometer Wind Vector Retrievals in Tropical Cyclones
Article Menu

Export Article

Open AccessArticle
Remote Sens. 2014, 6(5), 4149-4172; doi:10.3390/rs6054149

Determination of Carbonate Rock Chemistry Using Laboratory-Based Hyperspectral Imagery

Department of Earth Systems Analysis, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands
Department of Physics, Faculty of Mathematics and Natural Sciences, Syiah Kuala University, Darussalam, Banda Aceh, 23111 Aceh, Indonesia
Author to whom correspondence should be addressed.
Received: 6 December 2013 / Revised: 11 April 2014 / Accepted: 28 April 2014 / Published: 5 May 2014
View Full-Text   |   Download PDF [4474 KB, uploaded 19 June 2014]   |  


The development of advanced laboratory-based imaging hyperspectral sensors, such as SisuCHEMA, has created an opportunity to extract compositional information of mineral mixtures from spectral images. Determining proportions of minerals on rock surfaces based on spectral signature is a challenging approach due to naturally-occurring minerals that exist in the form of intimate mixtures, and grain size variations. This study demonstrates the application of SisuCHEMA hyperspectral data to determine mineral components in hand specimens of carbonate rocks. Here, we applied wavelength position, spectral angle mapper (SAM) and linear spectral unmixing (LSU) approaches to estimate the chemical composition and the relative abundance of carbonate minerals on the rock surfaces. The accuracy of these classification methods and correlation between mineral chemistry and mineral spectral characteristics in determining mineral constituents of rocks are also analyzed. Results showed that chemical composition (Ca-Mg ratio) of carbonate minerals at a pixel (e.g., sub-grain) level can be extracted from the image pixel spectra using these spectral analysis methods. The results also indicated that the spatial distribution and the proportions of calcite-dolomite mixtures on the rock surfaces vary between the spectral methods. For the image shortwave infrared (SWIR) spectra, the wavelength position approach was found to be sensitive to all compositional variations of carbonate mineral mixtures when compared to the SAM and LSU approaches. The correlation between geochemical elements and spectroscopic parameters also revealed the presence of these carbonate mixtures with various chemical compositions in the rock samples. This study concludes that the wavelength position approach is a stable and reproducible technique for estimating carbonate mineral chemistry on the rock surfaces using laboratory-based hyperspectral data. View Full-Text
Keywords: SisuCHEMA hyperspectral data; carbonate rocks; mineral mixtures; SWIR reflectance spectra; spectral recognition approaches; geochemical analysis SisuCHEMA hyperspectral data; carbonate rocks; mineral mixtures; SWIR reflectance spectra; spectral recognition approaches; geochemical analysis

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Zaini, N.; van der Meer, F.; van der Werff, H. Determination of Carbonate Rock Chemistry Using Laboratory-Based Hyperspectral Imagery. Remote Sens. 2014, 6, 4149-4172.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top