Utilizing a low-altitude unmanned aerial vehicle (UAV), a hyperspectral remote-sensing system can identify key grass species indicating grassland degradation, developing an ASI index and classification rules and leveraging spectral differences and plant senescence reflectance to effectively monitor and evaluate grassland conditions and degradation.
A novel intelligent inversion model integrating multiscale fractal analysis, PCA, and machine learning techniques (RF and SVM) was devised to accurately estimate soil organic matter (SOM) using hyperspectral data.
This tutorial illustrates spectroscopic imaging principles, applications, advantages, and limitations for UV-vis, FL, NIR, IR, THz, Raman, XRF, ICP-MS, and LIBS techniques. It provides a guide for understanding spectroscopic imaging for diverse sample types and applications.
This study explores the enhanced performance of modified alternating least squares (MALS) over alternating least squares (ALS) in analyzing infrared and Raman image spectral data, highlighting the stability and computational efficiency of MALS.
This review explores the latest advancements in near-infrared (NIR) imaging technology, detailing its diverse applications such as tracking solvent diffusion in polymers, portable analysis systems in pharmaceuticals, high-speed polymer monitoring, and NIR imaging for fish embryo development research.
An inside look at the fundamentals of Raman microscopy and how Raman can be utilized in chemical imaging and analysis, from its inception to modern applications.
