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Salt Content Distribution and Paleoclimatic Significance of the Lop Nur 'Ear' Feature: Results from Analysis of EO-1 Hyperion Imagery
- Source :
- Remote Sensing, Vol 6, Iss 8, Pp 7783-7799 (2014)
- Publication Year :
- 2014
- Publisher :
- MDPI AG, 2014.
-
Abstract
- Lop Nur, a playa lake located on the eastern margin of Tarim Basin in northwestern China, is famous for the “Ear” feature of its salt crust, which appears in remote-sensing images. In this study, partial least squares (PLS) regression was used to estimated Lop Nur playa salt-crust properties, including total salt, Ca2+, Mg2+, Na+, Si2+, and Fe2+ using laboratory hyperspectral data. PLS results for laboratory-measured spectra were compared with those for resampled laboratory spectra with the same spectral resolution as Hyperion using the coefficient of determination (R2) and the ratio of standard deviation of sample chemical concentration to root mean squared error (RPD). Based on R2 and RPD, the results suggest that PLS can predict Ca2+ using Hyperion reflectance spectra. The Ca2+ distribution was compared to the “Ear area” shown in a Landsat Thematic Mapper (TM) 5 image. The mean value of reflectance from visible bands for a 14 km transversal profile to the “Ear area” rings was extracted with the TM 5 image. The reflectance was used to build a correlation with Ca2+ content estimated with PLS using Hyperion. Results show that the correlation between Ca2+ content and reflectance is in accordance with the evolution of the salt lake. Ca2+ content variation was consistent with salt deposition. Some areas show a negative correlation between Ca2+ content and reflectance, indicating that there could have been a small-scale temporary runoff event under an arid environmental background. Further work is needed to determine whether these areas of small-scale runoff are due to natural (climate events) or human factors (upstream channel changes).
- Subjects :
- playa lake
Hyperion data
partial least squares
Science
Subjects
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 6
- Issue :
- 8
- Database :
- Directory of Open Access Journals
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9d35f41451c46fcbff822a8d3f15115
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/rs6087783