scholarly journals Roof Color-Based Warm Roof Evaluation in Cold Regions Using a UAV Mounted Thermal Infrared Imaging Camera

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6488
Author(s):  
Kirim Lee ◽  
Jinhwan Park ◽  
Sejung Jung ◽  
Wonhee Lee
Keyword(s):  
Surface Temperature ◽  
Infrared Imaging ◽  
Pearson Correlation ◽  
Thermal Infrared ◽  
Thermal Infrared Imaging ◽  
Cool Roof ◽  
Color Differences ◽  
Aerial Vehicle ◽  
Heating Load ◽  
Objective Basis

Existing studies on reducing urban heat island phenomenon and building temperature have been actively conducted; however, studies on investigating the warm roof phenomenon to in-crease the temperature of buildings are insufficient. A cool roof is required in a high-temperature region, while a warm roof is needed in a low-temperature or cold region. Therefore, a warm roof evaluation was conducted in this study using the roof color (black, blue, green, gray, and white), which is relatively easier to install and maintain compared to conventional insulation materials and double walls. A remote sensing method via an unmanned aerial vehicle (UAV)-mounted thermal infrared (TIR) camera was employed. For warm roof evaluation, the accuracy of the TIR camera was verified by comparing it with a laser thermometer, and the correlation between the surface temperature and the room temperature was also confirmed using Pearson correlation. The results showed significant surface temperature differences ranging from 8 °C to 28 °C between the black-colored roof and the other colored roofs and indoor temperature differences from 1 °C to 7 °C. Through this study, it was possible to know the most effective color for a warm roof according to the color differences. This study gave us an idea of which color would work best for a warm roof, as well as the temperature differences from other colors. We believe that the results of this study will be helpful in heating load research, providing an objective basis for determining whether a warm roof is applied.

scholarly journals Study of ice accretion on wind turbine blade profiles using thermal infrared imaging

2020 ◽  
pp. 0309524X2093394
Author(s):  
Adeel Yousuf ◽  
Jia Yi Jin ◽  
Pavlo Sokolov ◽  
Muhammad S Virk
Keyword(s):  
Temperature Distribution ◽  
Surface Temperature ◽  
Wind Turbine ◽  
Turbine Blade ◽  
Infrared Imaging ◽  
Thermal Infrared ◽  
Ice Accretion ◽  
Blade Profile ◽  
Thermal Infrared Imaging ◽  
Surface Temperature Distribution

Atmospheric icing has been recognized as hindrance in proper utilization of good wind resources in cold regions. There is a growing need to better understand the ice accretion physics along wind turbine blades to improve its performance and for optimal design of anti/de-icing system. This article describes a study of ice accretion along wind turbine blade profiles using thermal infrared imaging. Surface temperature distribution along four different blade profile surfaces is studied at different operating conditions. Analysis shows that surface temperature distribution along blade profile surface during ice accretion process is a dynamic process and change in atmospheric conditions and blade geometric characteristics significantly affects the surface temperature and resultant ice accretion. The effect of blade geometry on ice accretion is more prominent in case of wet ice conditions due to low freezing fraction and water run back along blade profile surface.

scholarly journals Multi-Resolution Study of Thermal Unmixing Techniques over Madrid Urban Area: Case Study of TRISHNA Mission

2019 ◽  
Vol 11 (10) ◽  
pp. 1251 ◽  
Author(s):  
Carlos Granero-Belinchon ◽  
Aurelie Michel ◽  
Jean-Pierre Lagouarde ◽  
Jose A. Sobrino ◽  
Xavier Briottet
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
Infrared Imaging ◽  
Thermal Infrared ◽  
Resource Assessment ◽  
Regression Kriging ◽  
Scale Invariant ◽  
Thermal Infrared Imaging ◽  
Spatio Temporal ◽  
Classification Index

This work is linked to the future Indian–French high spatio-temporal TRISHNA (Thermal infraRed Imaging Satellite for High-resolution natural resource Assessment) mission, which includes shortwave and thermal infrared bands, and is devoted amongst other things to the monitoring of urban heat island events. In this article, the performance of seven empirical thermal unmixing techniques applied on simulated TRISHNA satellite images of an urban scenario is studied across spatial resolutions. For this purpose, Top Of Atmosphere (TOA) images in the shortwave and Thermal InfraRed (TIR) ranges are constructed at different resolutions (20 m, 40 m, 60 m, 80 m, and 100 m) and according to TRISHNA specifications (spectral bands and sensor properties). These images are synthesized by correcting and undersampling DESIREX 2008 Airborne Hyperspectral Scanner (AHS) images of Madrid at 4 m resolution. This allows to compare the Land Surface Temperature (LST) retrieval of several unmixing techniques applied on different resolution images, as well as to characterize the evolution of the performance of each technique across resolutions. The seven unmixing techniques are: Disaggregation of radiometric surface Temperature (DisTrad), Thermal imagery sHARPening (TsHARP), Area-To-Point Regression Kriging (ATPRK), Adaptive Area-To-Point Regression Kriging (AATPRK), Urban Thermal Sharpener (HUTS), Multiple Linear Regressions (MLR), and two combinations of ground classification (index-based classification and K-means classification) with DisTrad. Studying these unmixing techniques across resolutions also allows to validate the scale invariance hypotheses on which the techniques hinge. Each thermal unmixing technique has been tested with several shortwave indices, in order to choose the best one. It is shown that (i) ATPRK outperforms the other compared techniques when characterizing the LST of Madrid, (ii) the unmixing performance of any technique is degraded when the coarse spatial resolution increases, (iii) the used shortwave index does not strongly influence the unmixing performance, and (iv) even if the scale-invariant hypotheses behind these techniques remain empirical, this does not affect the unmixing performances within this range of resolutions.

Thermal infrared imaging of geothermal environments by UAV (unmanned aerial vehicle)

2016 ◽  
Vol 4 (2) ◽  
pp. 136-145 ◽  
Author(s):  
Abdul Nishar ◽  
Steve Richards ◽  
Dan Breen ◽  
John Robertson ◽  
Barbara Breen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Infrared Imaging ◽  
Thermal Infrared ◽  
Thermal Infrared Imaging ◽  
Aerial Vehicle ◽  
Geothermal Environments

scholarly journals Thermography as a Method to Detect Dental Anxiety in Oral Surgery

2021 ◽  
Vol 11 (12) ◽  
pp. 5421
Author(s):  
Roberta Gasparro ◽  
Grazia Leonetti ◽  
Michele Riccio ◽  
Andrea Irace ◽  
Gilberto Sammartino ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Oral Surgery ◽  
Pearson Correlation ◽  
Dental Anxiety ◽  
Thermal Infrared ◽  
Thermal Infrared Imaging ◽  
Significant Difference ◽  
Thermal Cameras ◽  
And Gender ◽  
Age Range

: (1) Background: the aim of this study was to evaluate if dental anxiety can be measured objectively using thermal infrared imaging. (2) Methods: Patients referred to the Department of Oral Surgery of the University of Naples Federico II and requiring dental extractions were consecutively enrolled in the study. Face thermal distribution images of the patients were acquired before and during their first clinical examination using infrared thermal cameras. The data were analyzed in relation to five regions of interest (ROI) of the patient’s face (nose, ear, forehead, zygoma, chin). The differences in the temperatures assessed between the two measurements for each ROI were evaluated by using paired T-test. The Pearson correlation and linear regression were performed to evaluate the association between differences in temperatures and Modified Dental Anxiety Scale (MDAS) questionnaire score, age, and gender; (3) results: sixty participants were enrolled in the study (28 males and 32 females; mean age 57.4 year-old; age range 18–80 year-old). Only for nose and ear zone there was a statistically significant difference between measurements at baseline and visit. Correlation between the thermal imaging measurements and the scores of the MDAS questionnaire was found for nose and ear, but not for all of the other regions. (4) Conclusions: the study demonstrated a potential use of thermal infrared imaging to measure dental anxiety.

scholarly journals Evaluation of Applicability of Various Color Space Techniques of UAV Images for Evaluating Cool Roof Performance

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4213
Author(s):  
Kirim Lee ◽  
Jihoon Seong ◽  
Youkyung Han ◽  
Won Hee Lee
Keyword(s):  
Surface Temperature ◽  
Pearson Correlation ◽  
Color Space ◽  
Thermal Infrared ◽  
Urban Heat Islands ◽  
Infrared Sensor ◽  
Indoor Temperature ◽  
Cool Roof ◽  
Urban Heat ◽  
Infrared Cameras

Global warming is intensifying worldwide, and urban heat islands are occurring as urbanization progresses. The cool roof method is one alternative for reducing the urban heat island phenomenon and lowering the heat on building roofs for a comfortable indoor environment. In this study, a cool roof evaluation was performed using an unmanned aerial vehicle (UAV) and a red, green and blue (RGB) camera instead of a laser thermometer and a thermal infrared sensor to evaluate existing cool roofs. When using a UAV, an RGB sensor is used instead of expensive infrared sensor. Various color space techniques, namely light-reflectance value, hue saturation value (HSV), hue saturation lightness, and YUV (luma component (Y) and two chrominance components, called U (blue projection) and V (red projection)) derived from RGB images, are applied to evaluate color space techniques suitable for cool roof evaluation. This case study shows the following quantitative results: among various color space techniques investigated herein, the white roof with lowest temperature (average surface temperature: 44.1 °C; average indoor temperature: 33.3 °C) showed highest HSV, while the black roof with the highest temperature (surface temperature average: 73.4 °C; indoor temperature average: 37.1 °C) depicted the lowest HSV. In addition, the HSV showed the highest correlation in both the Pearson correlation coefficient and the linear regression analyses when the correlation among the brightness, surface temperature, and indoor temperature of the four color space techniques was analyzed. This study is considered a valuable reference for using RGB cameras and HSV color space techniques, instead of expensive thermal infrared cameras, when evaluating cool roof performance.

Use of thermal infrared imaging for monitoring renewed dome growth at Mount St. Helens, 2004

2008 ◽  
pp. 347-359 ◽  
Author(s):  
David J. Schneider ◽  
James W. Vallance ◽  
Rick L. Wessels ◽  
Matthew Logan ◽  
Michael S. Ramsey
Keyword(s):  
Infrared Imaging ◽  
Thermal Infrared ◽  
Thermal Infrared Imaging ◽  
Dome Growth ◽  
Mount St Helens
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