Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation01:26

Inductively Coupled Plasma Atomic Emission Spectroscopy: Instrumentation

Inductively coupled plasma (ICP) is the common plasma source used in atomic emission spectroscopy (AES), a technique that detects and analyzes various elements in a sample. This method is often called inductively coupled plasma atomic emission spectroscopy (ICP-AES).
There are three main types of inductively coupled plasma atomic emission spectroscopy  (ICP-AES) instruments: sequential, simultaneous multichannel, and Fourier transform instruments, with the latter being less commonly used.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Frailty-Related Factors among Women Living with and without HIV Aged 40 Years and Older. The Women's Interagency HIV Study.

The Journal of frailty & aging·2024
Same author

The formation of ubiquitin rich condensates triggers recruitment of the ATG9A lipid transfer complex to initiate basal autophagy.

bioRxiv : the preprint server for biology·2023
Same author

Feasibility of Brain Atrophy Measurement in Clinical Routine without Prior Standardization of the MRI Protocol: Results from MS-MRIUS, a Longitudinal Observational, Multicenter Real-World Outcome Study in Patients with Relapsing-Remitting MS.

AJNR. American journal of neuroradiology·2017
Same author

Reduced binding of Pittsburgh Compound-B in areas of white matter hyperintensities.

NeuroImage. Clinical·2015
Same author

Improved method for calibrating the visible and near-infrared channels of the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer.

Applied optics·2010
Same author

Calibration comparison for the Landsat 4 and 5 multispectral scanners and thematic mappers.

Applied optics·2010
Same journal

Multifunctional reconfigurable terahertz metasurface based on vanadium dioxide phase transition: achieving broadband absorption and efficient polarization conversion.

Applied optics·2026
Same journal

High-Q-factor electromagnetically induced transparency utilizing quasi-bound states in the continuum in an all-dielectric terahertz metasurface.

Applied optics·2026
Same journal

Automated stitching interferometry for high-precision metrology of X-ray mirrors.

Applied optics·2026
Same journal

Experimental demonstration of an approach to designing a metal-dielectric DBR resonant cavity structure.

Applied optics·2026
Same journal

High-precision wavefront reconstruction from a single-shot interferogram using a physics-driven hybrid feature calibration network.

Applied optics·2026
Same journal

Ultra-high-Q Fano resonance based on coupled topological corner states in Kagome photonic crystals.

Applied optics·2026
See all related articles

Related Experiment Video

Updated: Jun 8, 2026

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
07:34

Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

Published on: August 22, 2019

Band selection procedure for multispectral scanners.

J C Price

    Applied Optics
    |October 2, 2010
    PubMed
    Summary
    This summary is machine-generated.

    Optimizing spectral bands for remote sensing instruments is crucial for effective resource monitoring. This study presents a method to select optimal bands, finding 15-25 bands suffice for most natural materials.

    More Related Videos

    Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy
    09:57

    Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

    Published on: July 25, 2022

    Related Experiment Videos

    Last Updated: Jun 8, 2026

    Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals
    07:34

    Excitation-Scanning Hyperspectral Imaging Microscopy to Efficiently Discriminate Fluorescence Signals

    Published on: August 22, 2019

    Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy
    09:57

    Multiplex Chemical Imaging Based on Broadband Stimulated Raman Scattering Microscopy

    Published on: July 25, 2022

    Area of Science:

    • Earth and Space Sciences
    • Remote Sensing Technology
    • Data Science

    Background:

    • Advancements in sensor technology and data processing are driving the development of sophisticated remote sensing devices.
    • Effective resource monitoring relies on optimizing the design of multispectral instruments, necessitating careful consideration of spectral band selection.
    • Trade-offs in instrument design are essential due to evolving technological capabilities.

    Purpose of the Study:

    • To describe a methodology for optimizing the selection of spectral bands for multispectral remote sensing instruments.
    • To apply this methodology to a diverse set of spectral data, including natural and artificial materials.
    • To determine the optimal number of spectral bands required for accurate spectral characterization.

    Main Methods:

    • Development of an optimization methodology for selecting spectral bands in multispectral instruments.
    • Application of the methodology to laboratory and outdoor reflectance spectra.
    • Analysis of spectral data across visible and near-infrared ranges at high spectral resolution (0.01-μm).

    Main Results:

    • The study successfully applied the band selection methodology to various material spectra.
    • For most natural materials, 15-25 spectral bands were found to be sufficient for describing spectral variability.
    • Minerals and certain artificial substances may require a higher number of spectral bands (up to double) for adequate description.

    Conclusions:

    • The proposed methodology provides a framework for optimizing spectral band selection in remote sensing.
    • The number of spectral bands required is material-dependent, with natural materials generally needing fewer bands than minerals or artificial substances.
    • This research contributes to the design of more efficient and effective remote sensing instruments for resource monitoring.