@article{0445432828bc488d9bdd92c1101ce2b5,
title = "Mineral classification of soils using hyperspectral longwave infrared (LWIR) Ground-based data",
abstract = "Soil mineralogy is an important factor affecting chemical and physical processes in the soil. Most common minerals in soils-quartz, clay minerals and carbonates-present fundamental spectral features in the longwave infrared (LWIR) region. The current study presents a procedure for determining the soil mineralogy from the surface emissivity spectrum. Ground-based hyperspectral LWIR images of 90 Israeli soil samples were acquired with the Telops Hyper-Cam sensor, and the emissivity spectrum of each sample was calculated. Mineral-related emissivity features were identified and used to create indicants and indices to determine the content of quartz, clay minerals, and carbonates in the soil in a semi-quantitative manner-from more to less abundant minerals. The resultant mineral content was in good agreement with the mineralogy derived from chemical analyses.",
keywords = "Emissivity spectrum, Hyperspectral remote sensing, Longwave infrared image, Soil mineralogy",
author = "Gila Notesco and Shahar Weksler and Eyal Ben-Dor",
note = "Publisher Copyright: {\textcopyright} 2019 by the authors. All right reserved.",
year = "2019",
month = jun,
day = "1",
doi = "10.3390/rs11121429",
language = "אנגלית",
volume = "11",
journal = "Remote Sensing",
issn = "2072-4292",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "12",
}