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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Haixia He Bing Zhang Zhengchao Chen Ru Li |
| Copyright Year | 2009 |
| Description | Author affiliation: Center for Earth Observation and Digital Earth, Chinese Academy of Sciences, Beijing, 100080 (Bing Zhang; Zhengchao Chen) || The State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing, 100101 (Haixia He) || Institute of space and earth information science, the Chinese university of Hong Kong) (Ru Li) |
| Abstract | Lunar minerals mapping is one of basic aims of China's Lunar Exploration Program. The goal of this paper was to use multiple mineral mapping techniques including classification and spectral matching for lunar surface minerals mapping and choose the effective methods based on the image data which was simulated by 76 lunar samples spectra supplied by LSCC. The results indicated that Mahalanobis Distance and support vector machine performs best of the supervised classification methods. SAM is more effective than SID of the spectral matching methods. The classification capability was different for the different size samples of the same materials. The samples with obvious diagnosed spectral characteristic can be identified effectively. Those without diagnosed spectral characteristic are sensitive to the mapping method. Besides the mapping methods, there are other factors which may affect the mapping results, such as the lunar soil component, the lunar soil maturity, the particle size and the data preprocessing procedure. |
| File Size | 268343 |
| File Format | |
| ISBN | 9781424433940 |
| DOI | 10.1109/IGARSS.2009.5417859 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-07-12 |
| Publisher Place | South Africa |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Moon Minerals Soil Earth Optical surface waves Spectroscopy Remote sensing Geoscience Hyperspectral imaging Iron Lunar surface minerals mapping image simulation spectral matching method |
| Content Type | Text |
| Resource Type | Article |
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