Terminology in thermal infrared remote sensing of natural surfaces

Norman, John M.; Becker, F.

doi:10.1080/02757259509532284

Cited by 178 publications

(170 citation statements)

References 11 publications

Supporting

Mentioning

168

Contrasting

Unclassified

Order By: Relevance

“…Sensible heat flux is, by analogy with Ohm’s law, driven by a temperature gradient between the surface and the atmosphere and is counteracted by a resistance term. Despite the simplicity of this expression, the complication lies in the determination of the aerodynamic surface temperature that cannot be measured directly and is not equal to the radiometric surface temperature measured by the Thermal Infrared Sensor (Norman and Becker 1995; Kustas and Anderson 2009). Thus, the approach for the approximation of the aerodynamic surface temperature from the radiometric surface temperature is the main difference in the various EB models.…”

Section: Introductionmentioning

confidence: 99%

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Brenner

Zeeman

Bernhardt

et al. 2018

International Journal of Remote Sensing

View full text Add to dashboard Cite

Spatially distributed high-resolution data of land surface temperature (LST) and evapotranspiration (ET) are important information for crop water management and other applications in the agricultural sector. While satellite data can provide LST high-resolution data of 100 m, the current development of unmanned aerial systems (UAS) and affordable low-weight thermal cameras allows LST and subsequent ET to be derived at resolutions down to centimetre scale.In this study, UAS-based images in the thermal infrared (TIR) and visible spectral range were collected over a managed temperate grassland in July 2016 at the Terrestrial Environmental Observatories Networks TERENO preAlpine observatory site at Fendt, Germany. The UAS set-up included a lightweight thermal camera (Optris Pi Lightweight) and a regular digital camera (Sony α 6000) that allowed for the acquisition of thermal and optical images with a ground resolution of 5 cm and 1 cm, respectively. Three TIR-based ET models of different complexity were applied and the resulting ET estimates were compared to the Eddy covariance (EC) observations of turbulent energy fluxes and also to the evaporative fraction. While the Deriving Atmosphere Turbulent Transport Useful To Dummies Using Temperature (DATTUTDUT) model and the Triangle Method belong to the group of simpler contextual models, the Two-Source Energy Balance (TSEB) model incorporates a more physically based formulation of the surface energy balance. In addition to the comparison of UAS-based estimates of latent heat fluxes to EC observations, the effect of the spatial resolution of the model imagery input on the modelled results was analysed by running the models with imagery from the native resolution of the acquired images to resolutions that were aggregated up to 30 m.The results show that both contextual models are sensitive to the input image resolution and that the agreement with the EC observations improves with increasing image resolution. The TSEB model assumes that LST pixels represent a mixed signal of the soil and canopy components, thus an image resolution coarse enough to ensure this assumption should be chosen. However, with the exception of the native image resolution of 5 cm, we found no effect of image resolution on the spatially weighted mean TSEB estimates.For the studied grassland, the comparison of model estimates with EC observations indicates that all three models are able to reproduce observed energy fluxes with comparable accuracy with mean absolute errors of ET between 20 and 40 W m−2. The TSEB model showed larger deviations from the reference observations under cloudy conditions with rapid fluctuations of LST within the 30 min averaging period for EC. The two contextual models yielded similar results for most of the flights. The good performance of the DATTUTDUT model, which had the lowest input requirements of the three models, is especially promising in view of the application of UAS for routine near-real-time ET monitoring.

show abstract

Section: Introductionmentioning

confidence: 99%

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Brenner

Zeeman

Bernhardt

et al. 2018

International Journal of Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Norman et al [102] proposed a new model named two-source model, also known as duel-source model to improve the accuracy of LE estimates using satellite remote sensing data, especially over sparse surfaces [102][103][104][105][106]. The basic principle of this model is to partitioning the composite radiometric surface temperature into soil and vegetation components, and considered sensible and latent heat fluxes are transferred to the atmosphere from both surface components.…”

Section: Two-source Models (Tsm)mentioning

confidence: 99%

Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review

2014

View full text Add to dashboard Cite

Abstract:With the advent of new satellite technology, the radiative energy exchanges between Sun, Earth, and space may now be quantified accurately. Nevertheless, much less is known about the magnitude of the energy flows within the climate system and at the Earth's surface, which cannot be directly measured by satellites. This review surveys the basic theories, observational methods, and different surface energy balance algorithms for estimating evapotranspiration (ET) from landscapes and regions with remotely sensed surface temperatures, and highlights uncertainties and limitations associated with those estimation methods. Although some of these algorithms were built up for specific land covers like irrigation areas only, methods developed for other disciplines like hydrology and meteorology, are also reviewed, where continuous estimates in space and in time are needed. Temporal and spatial scaling issues associated with the use of thermal remote sensing for estimating evapotranspiration are also discussed. A review of these different satellite based remote sensing approaches is presented. The main physical bases and assumptions of these algorithms are also discussed. Some results are shown for the estimation of evapotranspiration on a rice paddy of Chiayi Plain in Taiwan using remote sensing data.

show abstract

“…At the EC tower sites, LST was measured using two Apogee (models IRR-PN and IRTS-P, 3:1 field of view) IRTs at nominally 1.25 m agl, one viewing nadir, the other aimed 45 degrees with due south azimuth angle. For comparison with the IRT data, estimates of LST were also available from longwave pyrgeometers mounted at each site (Kipp & Zonen CGR3 models at the lysimeter sites, and CNR1 net radiometers at the EC sites, Bohemia, New York), which yields a ''hemispherical' surface temperature estimate through inversion of the Stefan-Boltzmann equation [8].…”

Section: Datamentioning

confidence: 99%

“…While LST is a useful controlling variable in energy balance modeling, uncertainties in accounting for variations in thermal emissivity, atmospheric corrections, radiometer viewing angle, and sensor calibration can significantly degrade the accuracy of LST retrievals from remotely sensed brightness temperatures [8]. Another complicating factor is the need for specifying surface layer atmospheric properties (principally wind speed and air temperature) over the modeled landscape.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area

Kustas

Alfieri

Anderson

et al. 2012

Advances in Water Resources

View full text Add to dashboard Cite

Evett, Steven R.; Neale, Christopher M. U.; French, Andrew N.; Hipps, Lawrence E.; Chávez, José L.; Copeland, Karen S.; and Howell, Terry A., "Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area" (2012 a b s t r a c tApplication and validation of many thermal remote sensing-based energy balance models involve the use of local meteorological inputs of incoming solar radiation, wind speed and air temperature as well as accurate land surface temperature (LST), vegetation cover and surface flux measurements. For operational applications at large scales, such local information is not routinely available. In addition, the uncertainty in LST estimates can be several degrees due to sensor calibration issues, atmospheric effects and spatial variations in surface emissivity. Time differencing techniques using multi-temporal thermal remote sensing observations have been developed to reduce errors associated with deriving the surface-air temperature gradient, particularly in complex landscapes. The Dual-Temperature-Difference (DTD) method addresses these issues by utilizing the Two-Source Energy Balance (TSEB) model of [1], and is a relatively simple scheme requiring meteorological input from standard synoptic weather station networks or mesoscale modeling. A comparison of the TSEB and DTD schemes is performed using LST and flux observations from eddy covariance (EC) flux towers and large weighing lysimeters (LYs) in irrigated cotton fields collected during BEAREX08, a large-scale field experiment conducted in the semi-arid climate of the Texas High Plains as described by [2]. Model output of the energy fluxes (i.e., net radiation, soil heat flux, sensible and latent heat flux) generated with DTD and TSEB using local and remote meteorological observations are compared with EC and LY observations. The DTD method is found to be significantly more robust in flux estimation compared to the TSEB using the remote meteorological observations. However, discrepancies between model and measured fluxes are also found to be significantly affected by the local inputs of LST and vegetation cover and the representativeness of the remote sensing observations with the local flux measurement footprint.Published by Elsevier Ltd.

show abstract

Terminology in thermal infrared remote sensing of natural surfaces

Cited by 178 publications

References 11 publications

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Estimation of evapotranspiration of temperate grassland based on high-resolution thermal and visible range imagery from unmanned aerial systems

Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review

Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area

Contact Info

Product

Resources

About