Remote Sensing | |
Mineral Classification of Makhtesh Ramon in Israel Using Hyperspectral Longwave Infrared (LWIR) Remote-Sensing Data | |
Gila Notesco1  Yaron Ogen2  Eyal Ben-Dor2  James Jin-King Liu2  Yu-Chang Chan2  Magaly Koch2  | |
[1] Remote Sensing Laboratory, Tel Aviv University, Tel Aviv 69978, Israel; | |
关键词: hyperspectral remote-sensing; longwave infrared image; emissivity; Makhtesh Ramon; mineral classification; | |
DOI : 10.3390/rs70912282 | |
来源: mdpi | |
【 摘 要 】
Hyperspectral remote-sensing techniques offer an efficient procedure for mineral mapping, with a unique hyperspectral remote-sensing fingerprint in the longwave infrared spectral region enabling identification of the most abundant minerals in the continental crust—quartz and feldspars. This ability was examined by acquiring airborne data with the AisaOWL sensor over the Makhtesh Ramon area in Israel. The at-sensor radiance measured from each pixel in a longwave infrared image represents the emissivity, expressing chemical and physical properties such as surface mineralogy, and the atmospheric contribution which is expressed differently during the day and at night. Therefore, identifying similar features in day and night radiance enabled identifying the major minerals in the surface—quartz, silicates (feldspars and clay minerals), gypsum and carbonates—and mapping their spatial distribution. Mineral identification was improved by applying the radiance of an
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland.
【 预 览 】
Files | Size | Format | View |
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RO202003190005937ZK.pdf | 1197KB | download |