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Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
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IR Frequency Region: Fingerprint Region01:03

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Updated: Jun 23, 2026

Near-Infrared Temperature Measurement Technique for Water Surrounding an Induction-heated Small Magnetic Sphere
08:52

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Published on: April 30, 2018

[The correlation based mid-infrared temperature and emissivity separation algorithm].

Jie Cheng1, Ai-Xiu Nie, Yong-Ming Du

  • 1Beijing Normal University, State Key Laboratory of Remote Sensing Science, Beijing 100875, China. brucechan2003@126.com

Guang Pu Xue Yu Guang Pu Fen Xi = Guang Pu
|May 19, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a new algorithm for separating surface temperature and emissivity from ground-based mid-infrared hyperspectral data. The method accurately retrieves temperature and emissivity, proving robust against noise and atmospheric variations.

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Area of Science:

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

Context:

  • Accurate temperature and emissivity separation is crucial for infrared remote sensing applications.
  • Ground-based mid-infrared hyperspectral data presents unique challenges for atmospheric and surface property retrieval.
  • Existing methods often struggle with atmospheric interference and instrumental noise.

Purpose:

  • To develop and validate a novel algorithm for temperature and emissivity separation using ground-based mid-infrared hyperspectral data.
  • To leverage the relationship between atmospheric downward radiance and surface emissivity for improved retrieval accuracy.
  • To assess the algorithm's performance, robustness, and applicability in realistic measurement scenarios.

Summary:

  • The proposed algorithm analyzes the correlation between atmospheric downward radiance and surface emissivity, using temperature bias as an optimization criterion for surface temperature retrieval.
  • Surface emissivity is subsequently calculated once the surface temperature is accurately determined.
  • The algorithm demonstrated high accuracy in simulated mid-infrared hyperspectral data, showing broad applicability and insensitivity to instrumental noise and atmospheric variations.

Impact:

  • Enables more precise surface temperature and emissivity measurements from ground-based infrared hyperspectral sensors.
  • Advances the field of infrared remote sensing by providing a reliable method for data analysis.
  • Facilitates improved environmental monitoring, geological surveys, and climate studies through enhanced data accuracy.