scholarly journals Pixel-Based Calibration and Atmospheric Correction of a UAS-Mounted Thermal Camera for Land Surface Temperature Measurements

2021 ◽  
Vol 64 (6) ◽  
pp. 2137-2150
Author(s):  
Yan Zhu ◽  
Keith Cherkauer
Keyword(s):  
Land Surface ◽  
Atmospheric Correction ◽  
Correction Method ◽  
Temperature Measurements ◽  
List Type ◽  
Thermal Camera ◽  
Thermal Imagery ◽  
Calibration Methods ◽  
Thermal Cameras ◽  
Calibration Algorithm

HighlightsA novel pixel-based calibration algorithm and an atmospheric correction method are developed.Application of the calibration methods reduces the RMSE of measurements to less than 1.32°C.The calibrations facilitate stitching of images together to form whole-field mosaics.Abstract. Thermal imagery can be used to provide insight into the water stress status and evapotranspiration demand of crops, but satellite-based sensors are generally too coarse spatially and too infrequent temporally to provide information of use for the management of specific fields. Thermal cameras mounted on small unmanned aerial systems (UAS) have potential to provide canopy temperature information at high spatial and temporal resolutions useful for crop management; however, without appropriate camera corrections, the measurement biases of these uncooled thermal cameras can be larger than ±5°C. Such uncertainty can render such camera measurements useless. In this research, a pixel-based (non-uniformity) calibration algorithm and an atmospheric correction method based on in-field approximate blackbody sources (water targets) were developed for a thermal camera. The objective was to improve the temperature measurement accuracy of the thermal camera on various land surfaces including soil and vegetation. With sufficient accuracy, temperature measurements can be used for the estimation of latent heat flux of field crops in the future. The thermal camera was first calibrated in a laboratory setting where the camera and environmental conditions were controlled. The results indicated that in the range between 10°C and 45°C, the calibrated temperatures were accurate, with an average bias of 1.76°C, and had a high linear correlation with reference temperatures (water target temperatures) (R2 > 0.99). Variability of measurements was also better constrained. In-field atmospheric correction is also important for obtaining high-accuracy thermal imagery. By applying both pixel-based calibration and atmospheric corrections, the RMSE (root mean square error) of validation targets from two dates in 2017 was reduced from 4.56°C and 6.36°C before calibration to 1.32°C and 1.24°C after calibration. The calibration process also increased the range of temperatures in the imagery, which enhanced contrast and may help with identification of tie-points and stitching of images together to form whole-field mosaics. Keywords: Atmospheric correction, Pixel-based calibration, Thermal remote sensing, UAS, Water targets.

scholarly journals Inversion and Analysis of Land Surface Temperature based on Landsat - a case study of BeiBei District in Chongqing

2020 ◽  
Vol 165 ◽  
pp. 03006
Author(s):  
Zhou Yang ◽  
Liu Na-na
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Exchange Process ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Temperature Inversion ◽  
Correction Method ◽  
Inversion Method ◽  
Temperature Area

Land surface temperature is the surface of the earth’s energy change and the exchange process, which is an important index for a lot of scientific research. In this paper, the surface temperature changes of BeiBei district in Chongqing in the past 20 years were inverted in 6 time phases. The surface temperature inversion method of Landsat remote sensing data was studied, and the atmospheric correction method was adopted to conduct the inversion by using Landsat5TM and landsat8OLI-TIRS image data. The results showed that from 2004 to 2014, the area of high temperature area increased year by year, and the area of low temperature area also increased year by year.

An Atmospheric Correction Method for Medium Resolution Spectral Imager Thermal IR Soundings

2012 ◽  
Vol 500 ◽  
pp. 397-402 ◽  
Author(s):  
Hai Lei Liu ◽  
Li Sheng Xu ◽  
Ji Lie Ding ◽  
Ba Sang ◽  
Xiao Bo Deng
Keyword(s):  
Water Vapor ◽  
Land Surface ◽  
Atmospheric Correction ◽  
Correction Method ◽  
Qinghai Lake ◽  
Medium Resolution ◽  
Interpolation Procedure ◽  
The Difference ◽  
Spectral Imager

Based on the thermal radiative transfer equation (RTE), a new atmospheric correction method named Single Band Water Vapor Dependent (SBWVD) method is developed for land surface temperature (LST) retrieval for the FY-3A Medium Resolution Spectral Imager (MERSI) with only one thermal infrared (TIR) channel. Assuming that the surface emissivity is known, water vapor content (WVC) is the only one parameter for input to the SBWVD algorithm to retrieve LST from MERSI TIR observations. FY-3A MERSI Level 2 water vapor product is employed to evaluate the performance of the proposed method, and a 2-D data interpolation procedure is applied in order to match the MERSI L1B data in spatial resolution. Some tests, including numerical simulation for MERSI sensor and the synchronous measurements of MERSI and the radiosondes for the radiative calibration of the FY-3A tests in Qinghai Lake, have been carried out for the proposed algorithm, respectively. The results show that the difference between the retrieved LST and the in-situ measurements is less than 0.6 K for most situations. The comparison with the MODIS LST products (V5) shows that the root mean square error (RMSE) is under 0.72 K. Thus, our proposed new algorithm is applicable for the atmospheric correction and LST retrieval using MERSI TIR channel observations.

scholarly journals Assessing the Performance of a Low-Cost Thermal Camera in Proximal and Aerial Conditions

2020 ◽  
Vol 12 (21) ◽  
pp. 3591
Author(s):  
Matheus Gabriel Acorsi ◽  
Leandro Maria Gimenez ◽  
Maurício Martello
Keyword(s):  
Thermal Imaging ◽  
Low Cost ◽  
Temperature Measurements ◽  
Aerial Images ◽  
Thermal Camera ◽  
Calibration Models ◽  
Accurate Temperature ◽  
Thermal Cameras ◽  
Accuracy Indices ◽  
Better Than

The development of low-cost miniaturized thermal cameras has expanded the use of remotely sensed surface temperature and promoted advances in applications involving proximal and aerial data acquisition. However, deriving accurate temperature readings from these cameras is often challenging due to the sensitivity of the sensor, which changes according to the internal temperature. Moreover, the photogrammetry processing required to produce orthomosaics from aerial images can also be problematic and introduce errors to the temperature readings. In this study, we assessed the performance of the FLIR Lepton 3.5 camera in both proximal and aerial conditions based on precision and accuracy indices derived from reference temperature measurements. The aerial analysis was conducted using three flight altitudes replicated along the day, exploring the effect of the distance between the camera and the target, and the blending mode configuration used to create orthomosaics. During the tests, the camera was able to deliver results within the accuracy reported by the manufacturer when using factory calibration, with a root mean square error (RMSE) of 1.08 °C for proximal condition and ≤3.18 °C during aerial missions. Results among different flight altitudes revealed that the overall precision remained stable (R² = 0.94–0.96), contrasting with the accuracy results, decreasing towards higher flight altitudes due to atmospheric attenuation, which is not accounted by factory calibration (RMSE = 2.63–3.18 °C). The blending modes tested also influenced the final accuracy, with the best results obtained with the average (RMSE = 3.14 °C) and disabled mode (RMSE = 3.08 °C). Furthermore, empirical line calibration models using ground reference targets were tested, reducing the errors on temperature measurements by up to 1.83 °C, with a final accuracy better than 2 °C. Other important results include a simplified co-registering method developed to overcome alignment issues encountered during orthomosaic creation using non-geotagged thermal images, and a set of insights and recommendations to reduce errors when deriving temperature readings from aerial thermal imaging.

scholarly journals Improving Accuracy of Unmanned Aerial System Thermal Infrared Remote Sensing for Use in Energy Balance Models in Agriculture Applications

2021 ◽  
Vol 13 (9) ◽  
pp. 1635
Author(s):  
Mitchell S. Maguire ◽  
Christopher M. U. Neale ◽  
Wayne E. Woldt
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Thermal Infrared ◽  
Temperature Measurements ◽  
Unmanned Aerial System ◽  
Thermal Camera ◽  
Thermal Imagery ◽  
Warm Up ◽  
Thermal Measurements ◽  
Improving Accuracy

Unmanned aerial system (UAS) remote sensing has rapidly expanded in recent years, leading to the development of several multispectral and thermal infrared sensors suitable for UAS integration. Remotely sensed thermal infrared imagery has been used to detect crop water stress and manage irrigation by leveraging the increased thermal signatures of water stressed plants. Thermal infrared cameras suitable for UAS remote sensing are often uncooled microbolometers. This type of thermal camera is subject to inaccuracies not typically present in cooled thermal cameras. In addition, atmospheric interference also may present inaccuracies in measuring surface temperature. In this study, a UAS with integrated FLIR Duo Pro R (FDPR) thermal camera was used to collect thermal imagery over a maize and soybean field that contained twelve infrared thermometers (IRT) that measured surface temperature. Surface temperature measurements from the UAS FDPR thermal imagery and field IRTs corrected for emissivity and atmospheric interference were compared to determine accuracy of the FDPR thermal imagery. The comparison of the atmospheric interference corrected UAS FDPR and IRT surface temperature measurements yielded a RMSE of 2.24 degree Celsius and a R2 of 0.85. Additional approaches for correcting UAS FDPR thermal imagery explored linear, second order polynomial and artificial neural network models. These models simplified the process of correcting UAS FDPR thermal imagery. All three models performed well, with the linear model yielding a RMSE of 1.27 degree Celsius and a R2 of 0.93. Laboratory experiments also were completed to test the measurement stability of the FDPR thermal camera over time. These experiments found that the thermal camera required a warm-up period to achieve stability in thermal measurements, with increased warm-up duration likely improving accuracy of thermal measurements.

scholarly journals Assessing an Atmospheric Correction Algorithm for Time Series of Satellite-Based Water-Leaving Reflectance Using Match-Up Sites in Australian Coastal Waters

2021 ◽  
Vol 13 (10) ◽  
pp. 1927
Author(s):  
Fuqin Li ◽  
David Jupp ◽  
Thomas Schroeder ◽  
Stephen Sagar ◽  
Joshua Sixsmith ◽  
...  
Keyword(s):  
Coastal Waters ◽  
Atmospheric Correction ◽  
Correction Method ◽  
In Situ Measurements ◽  
Landsat 8 ◽  
Correction Algorithm ◽  
Simple Method ◽  
North East ◽  
The Impact

An atmospheric correction algorithm for medium-resolution satellite data over general water surfaces (open/coastal, estuarine and inland waters) has been assessed in Australian coastal waters. In situ measurements at four match-up sites were used with 21 Landsat 8 images acquired between 2014 and 2017. Three aerosol sources (AERONET, MODIS ocean aerosol and climatology) were used to test the impact of the selection of aerosol optical depth (AOD) and Ångström coefficient on the retrieved accuracy. The initial results showed that the satellite-derived water-leaving reflectance can have good agreement with the in situ measurements, provided that the sun glint is handled effectively. Although the AERONET aerosol data performed best, the contemporary satellite-derived aerosol information from MODIS or an aerosol climatology could also be as effective, and should be assessed with further in situ measurements. Two sun glint correction strategies were assessed for their ability to remove the glint bias. The most successful one used the average of two shortwave infrared (SWIR) bands to represent sun glint and subtracted it from each band. Using this sun glint correction method, the mean all-band error of the retrieved water-leaving reflectance at the Lucinda Jetty Coastal Observatory (LJCO) in north east Australia was close to 4% and unbiased over 14 acquisitions. A persistent bias in the other strategy was likely due to the sky radiance being non-uniform for the selected images. In regard to future options for an operational sun glint correction, the simple method may be sufficient for clear skies until a physically based method has been established.

scholarly journals IAU Commission 25, and the development of early photometric systems

2018 ◽  
Vol 13 (S349) ◽  
pp. 357-373
Author(s):  
Christiaan Sterken
Keyword(s):  
List Type ◽  
Basic Principles ◽  
Half Century ◽  
Stellar Photometry ◽  
Select Group ◽  
International Astronomical ◽  
Calibration Methods ◽  
Standard Calibration ◽  
One Year ◽  
Basic Philosophy

AbstractThe International Astronomical Union was conceived in 1918, and was formed one year later in Brussels. One of the 32 initial Commissions was the Committee on Stellar Photometry that later on became IAU Commission 25 Astronomical Photometry and Polarimetry, and since 2015 Commission B6 with the same name. The initial functions to be exercised by the Committee were (a)to advise in the matter of notation, nomenclature, definitions, conventions, etc., and(b)to plan and execute investigations requiring the cooperation of several observers or institutions.The basic philosophy was that IAU Commission 25 was to be an advisory body, rather than a decision-making committee that imposes its regulations. This position was reconfirmed at the 10th IAU General Assembly in 1958.From the early days on, the Commission members engaged in the teaching of the principles of photometric measurement – either via the Commission meetings and the ensuing reports, or via external means, such as lectures and publications. The topics of instruction dealt with absorption of light in the atmosphere, the modification imposed by the character of the receiving apparatus, the unequal response of different receivers to a same stimulus, and variations in the data-recorder response from one experiment to another.From the 1930s on it was suggested that IAU Commission 25 takes responsibility in matters of standard stars, standard filters and standard calibration methods.During the first half-century since its foundation, Commission 25 was an active forum for discussions on the basic principles of astronomical photometry, including the associated problems of transformability of magnitudes and colour indices from one instrumental configuration to another. During the second half-century of its existence, the Commission has served as a sort of news agency reporting on the developments in detector engineering, filter technology and data reduction. All along the Commission members were committed to accuracy and precision, a struggle that was primarily driven by the jumps forward in performance and sensitivity of every new detector that was introduced.The development over one century shows that the Commission was continuously touching on the philosophy of precise measurement, where accurate measuring – for a select group of pioneers – was an end in itself.This presentation looks back on the opinions of key players in the photometric standardisation debate, and briefly presents two case studies that illustrate the illusionary accuracy reached over a century in determining, as Commission member Ralph Allan Sampson put it, “a detail like magnitude”.

scholarly journals Estimating evaporation with thermal UAV data and two-source energy balance models

2016 ◽  
Vol 20 (2) ◽  
pp. 697-713 ◽  
Author(s):  
H. Hoffmann ◽  
H. Nieto ◽  
R. Jensen ◽  
R. Guzinski ◽  
P. Zarco-Tejada ◽  
...  
Keyword(s):  
Heat Flux ◽  
Energy Balance ◽  
High Resolution ◽  
Eddy Covariance ◽  
Land Surface ◽  
Weather Conditions ◽  
Heat Fluxes ◽  
Thermal Camera ◽  
Model Input ◽  
Eddy Covariance Measurements

Abstract. Estimating evaporation is important when managing water resources and cultivating crops. Evaporation can be estimated using land surface heat flux models and remotely sensed land surface temperatures (LST), which have recently become obtainable in very high resolution using lightweight thermal cameras and Unmanned Aerial Vehicles (UAVs). In this study a thermal camera was mounted on a UAV and applied into the field of heat fluxes and hydrology by concatenating thermal images into mosaics of LST and using these as input for the two-source energy balance (TSEB) modelling scheme. Thermal images are obtained with a fixed-wing UAV overflying a barley field in western Denmark during the growing season of 2014 and a spatial resolution of 0.20 m is obtained in final LST mosaics. Two models are used: the original TSEB model (TSEB-PT) and a dual-temperature-difference (DTD) model. In contrast to the TSEB-PT model, the DTD model accounts for the bias that is likely present in remotely sensed LST. TSEB-PT and DTD have already been well tested, however only during sunny weather conditions and with satellite images serving as thermal input. The aim of this study is to assess whether a lightweight thermal camera mounted on a UAV is able to provide data of sufficient quality to constitute as model input and thus attain accurate and high spatial and temporal resolution surface energy heat fluxes, with special focus on latent heat flux (evaporation). Furthermore, this study evaluates the performance of the TSEB scheme during cloudy and overcast weather conditions, which is feasible due to the low data retrieval altitude (due to low UAV flying altitude) compared to satellite thermal data that are only available during clear-sky conditions. TSEB-PT and DTD fluxes are compared and validated against eddy covariance measurements and the comparison shows that both TSEB-PT and DTD simulations are in good agreement with eddy covariance measurements, with DTD obtaining the best results. The DTD model provides results comparable to studies estimating evaporation with similar experimental setups, but with LST retrieved from satellites instead of a UAV. Further, systematic irrigation patterns on the barley field provide confidence in the veracity of the spatially distributed evaporation revealed by model output maps. Lastly, this study outlines and discusses the thermal UAV image processing that results in mosaics suited for model input. This study shows that the UAV platform and the lightweight thermal camera provide high spatial and temporal resolution data valid for model input and for other potential applications requiring high-resolution and consistent LST.

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