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Saham Mirzaei

3 papers indexed

crossrefWater2025-06-05Cited by 10

Comparing UAV-Based Hyperspectral and Satellite-Based Multispectral Data for Soil Moisture Estimation Using Machine Learning

Hadi Shokati, Mahmoud Mashal, Aliakbar Noroozi, Saham Mirzaei, Zahra Mohammadi-Doqozloo, Kamal Nabiollahi, et al.

Accurate estimation of soil moisture content (SMC) is crucial for effective water management, enabling improved monitoring of water stress and a deeper understanding of hydrological processes. While satellite remote sensing provides broad coverage, its spatial resolution often li…

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crossrefRemote Sensing2025-05-31Cited by 1

Monitoring Gypsiferous Soils by Leveraging Advanced Spaceborne Hyperspectral Imagery via Spectral Indices and a Machine Learning Approach

Najmeh Rasooli, Saham Mirzaei, Stefano Pignatti

Enhancing the spatial resolution of gypsiferous soil detection, as a valuable baseline information layer, is beneficial for investigating agroecological processes and tackling land degradation in semi-arid environments. This study evaluates the performance of PRISMA (PRecursore I…

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crossrefRemote Sensing2024-07-02Cited by 13

Early-Season Crop Mapping by PRISMA Images Using Machine/Deep Learning Approaches: Italy and Iran Test Cases

Saham Mirzaei, Simone Pascucci, Maria Francesca Carfora, Raffaele Casa, Francesco Rossi, Federico Santini, et al.

Despite its high importance for crop yield prediction and monitoring, early-season crop mapping is severely hampered by the absence of timely ground truth. To cope with this issue, this study aims at evaluating the capability of PRISMA hyperspectral satellite images compared with…

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