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Temperature Measurement Sites

Temperature Measurement Sites

A thermometer measures body temperature. The common sites for measuring body temperature are the oral cavity, axillary region, temporal artery, and skin surface, such as the forehead, abdomen, and axilla. True core body temperature is assessed in the rectum, tympanic membrane, pulmonary artery, esophagus, and urinary bladder.
Oral: When assessing oral temperature, the thermometer tip should be placed under the tongue in the posterior sublingual pocket. It offers accurate readings and can be...

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Updated: Jan 1, 2026

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping

Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping

Published on: November 7, 2016

DTSGUI: A Python Program to Process and Visualize Fiber-Optic Distributed Temperature Sensing Data.

Marian Domanski¹, Daven Quinn², Frederick D Day-Lewis

¹U.S. Geological Survey, Central Midwest Water Science Center, 405 N. Goodwin Avenue, Urbana, Illinois 61801, USA.

|December 17, 2019

Summary

This summary is machine-generated.

Fiber-optic distributed temperature sensing (FO-DTS) generates complex data. A new Python tool, DTSGUI, simplifies processing, analysis, and visualization for hydrologic science applications.

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Area of Science:

Hydrologic Sciences
Environmental Monitoring
Geophysics

Background:

Fiber-optic distributed temperature sensing (FO-DTS) offers valuable insights into hydrologic processes.
However, the complexity of FO-DTS data hinders widespread adoption.
Existing tools are insufficient for efficient data management and analysis.

Purpose of the Study:

To introduce DTSGUI, a novel software package designed to address FO-DTS data challenges.
To provide researchers with a comprehensive tool for editing, processing, and visualizing FO-DTS data.
To facilitate the full utilization of information-rich FO-DTS datasets in hydrologic research.

Main Methods:

Development of DTSGUI, a public-domain Python-based software package.
Implementation of functionalities for data editing, parsing, and processing.
Integration of statistical analysis, georeferencing, and visualization capabilities.

Main Results:

DTSGUI enables efficient handling of large and complex FO-DTS datasets.
The software supports comprehensive data analysis, from basic editing to advanced visualization.
Georeferencing capabilities allow for spatial integration of temperature data.

Conclusions:

DTSGUI significantly lowers the barrier to entry for utilizing FO-DTS technology in hydrology.
The software empowers researchers to extract more meaningful information from temperature sensing data.
DTSGUI promotes broader adoption and application of FO-DTS in diverse hydrologic studies.