Dimensionality Reduction (DR) is an indispensable step to enhance classifier accuracy with data redundancy in hyperspectral images (HSI). This paper proposes a framework for DR that combines band ...
A groundbreaking study by researchers from a number of institutions in China introduces a novel hyperspectral remote sensing technique capable of hour-hectometer level horizontal distribution of trace ...
Marine vessels are indispensable to the global economy, transporting over 80% of goods worldwide. However, their emissions, including sulfur oxides (SOₓ), nitrogen oxides (NOₓ), particulate matter, ...
Hyperspectral image classification has become a pivotal task in remote sensing data processing. However, current deep learning-based methods still face challenges in effectively extracting ...
The Digital Imaging and Remote Sensing Laboratory conducted a data collection campaign to gather multi-modal imagery data in collaboration with SpecTIR, LLC, Kucera International, and a dedicated team ...
Just how much carbon is in the soil? That's a tough question to answer at large spatial scales, but understanding soil organic carbon at regional, national, or global scales could help scientists ...
Hyperspectral remote sensing image of the Salt River in Arizona. Credit: ©2025 Xplore Inc. All rights reserved SAN FRANCISCO – Xplore Inc. unveiled hyperspectral ...
China's rapid urbanization has escalated air pollution, notably nitrogen dioxide (NO2), which impacts health and the environment. Traditional monitoring methods lack the granularity needed to capture ...
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