@article {2422,
	title = {Soil Moisture Content Estimation From Hyperspectral Remote Sensing Data},
	journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
	volume = {18},
	year = {2025},
	pages = {22231-22240},
	abstract = {Because of its significant absorption power, especially in the shortwave infrared optical region, water dominates the optical reflectance properties of water-bearing materials. This allows us to study a material{\textquoteright}s water-related features, such as its moisture content, from optical reflectance. In this study, we proposed a framework to estimate soil moisture content from PRISMA hyperspectral remote sensing data. The proposed framework requires a dry endmember spectrum and an endmember spectrum of high soil moisture along with ground truth moisture content, obtained from ground measurements. The method takes into account the complex interaction of light with soils, the large variation of environmental conditions, leading to spectral variability and the soil-specific behavior of water. The framework is extensively validated using ground-measured soil moisture data from the International Soil Moisture Network database. A total of 1418 PRISMA images corresponding to 151 ground stations were analyzed. From 518 retained images, a total root-mean-squared error of 8.682 \% and R2 of 0.385 was obtained.},
	keywords = {Absorption, Hyperspectral, Hyperspectral imaging, Land surface, Machine learning regression, Optical imaging, Optical reflection, Optical sensors, PRISMA, Reflectivity, remote sensing, Soil measurements, Soil moisture, soil moisture content (SMC), vegetation mapping},
	doi = {10.1109/JSTARS.2025.3603841},
	author = {Jambhali, Ketaki Vinay and Koirala, Bikram and Bnoulkacem, Zakaria and Paul Scheunders}
}
@inproceedings {2331,
	title = {Soil Moisture Content Estimation from Hyperspectral Remote Sensing Data},
	booktitle = {2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)},
	year = {2023},
	pages = {1-5},
	keywords = {Hyperion EO-1, Hyperspectral, Hyperspectral imaging, machine learning, Moisture, Optical reflection, Optical saturation, Optical sensors, Optical signal processing, remote sensing, Soil moisture, soil moisture content},
	doi = {10.1109/WHISPERS61460.2023.10431194},
	author = {Jambhali, Ketaki Vinay and Koirala, Bikram and Bnoulkacem, Zakaria and Paul Scheunders}
}
