A semi-empirical method for estimating complete surface temperature from radiometric surface temperature, a study in Hong Kong city

Yang, Jinxin; Wong, Man Sing; Ho, Hung Chak; Krayenhoff, E. Scott; Chan, Pak Wai; Abbas, Sawaid; Menenti, Massimo

doi:10.1016/j.rse.2019.111540

Cited by 26 publications

(35 citation statements)

References 45 publications

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“…In order to study the impact of geometry on different SUHIs, satellite data acquired by the Landsat 5 (L5) / Thematic Map (TM) (30 m x 30 m after resampling) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) (90 m x 90 m) and the airborne high‐spatial resolution (0.2 m x 0.2 m) thermal data were collected. The satellite data of Landsat TM and ASTER were used to retrieve the radiometric surface temperature using the single channel method (Equation 1) (Yang et al ., 2015) and then estimate the T c by applying the method developed by (Yang et al ., 2020a) (Equation 2 and Equation 3):

E ((), i) = τ_{i} ([], normalε ((), i) B ((), T_{r} ((), i)) + ((), 1 - normalε ((), i)) R_{at}^{↓} ((), i)) + R_{at}^{↑} ((), i)

…”

Section: Methodsmentioning

confidence: 99%

“… T r ( i ) is the nadir‐view radiometric surface temperature estimated according to Equation (1), which also takes into account the geometry of the built‐up space within the footprint of the radiometer, but captures the exitance of horizontal facets only, λ p ( i ) is building density, F ( i ) is the wall area index, calculated as the ratio of wall area to horizontal area, Kn ( i ) is the solar irradiance onto the urban canopy(Wm −2 ), θ a ( i ) is solar azimuth angle (°), θ z ( i ) is solar zenith angle (°). These parameters were selected because they are the main factors that affect the difference between T c and T r after evaluation of the simulated data mentioned above (Yang et al ., 2020a).…”

Section: Methodsmentioning

confidence: 99%

“…The method developed to estimate the complete surface temperature by Yang et al . (2020a) (Equation 2 and Equation 3) was evaluated using a synthetic, model – based data set, and results showed it can reach good accuracy (r 2 = 0.97, RMSE = 1.500 K for daytime and r 2 = 0.98, RMSE = 0.690 K for nighttime). The relationships suggested by Yang et al .…”

Section: Methodsmentioning

confidence: 99%

“…The relationships suggested by Yang et al . (2020a) were developed using simulated data by carrying out a large number of numerical experiments with TUF – 3D for a wide range of key model parameters and atmospheric forcing variables. The method of Yang et al .…”

Section: Methodsmentioning

confidence: 99%

“…The method of Yang et al . (2020a), therefore, is not limited to the specific conditions applying to the image data used to evaluate and demonstrate the approach.…”

Section: Methodsmentioning

confidence: 99%

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Assessing the impact of urban geometry on surface urban heat island using complete and nadir temperatures

Yang

Menenti

et al. 2020

Intl Journal of Climatology

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The surface urban heat island intensity (SUHII) when using nadir-viewing radiometric and complete surface temperature (T r and T c) was evaluated. The urban areas of the Kowloon peninsula and Hong Kong Island were selected and four daytime Landsat TM images and two nighttime ASTER images were collected to retrieve T r and then model T c based on a semi-empirical model. SUHIIs were estimated using both the retrieved T r and modelled T c. High spatial resolution (HR) airborne thermal images (0.2 m) observed at 12:10 noon on Oct 24, 2017 were used to retrieve T c directly. Results based on HR data and satellite data were consistent and indicated that the geometry of the built-up space had a larger impact on SUHII when using T c (SUHIIc) than T r (SUHIIr). During daytime SUHIIc decreased while SUHIIr showed a very slight increase with building density. Both SUHIIc and SUHIIr decreased with higher building height but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr decreased with increasing building height variance and increased with increasing sky view factor (SVF). The rate of decrease with building height variance for SUHIIc was larger than SUHIIr. The rate of increase of SUHIIc with SVF was higher than SUHIIr. During nighttime, geometry effects on SUHIIc and SUHIIr were different from daytime. Both SUHIIc and SUHIIr increased with building density, while the rate of increase of SUHIIc with building density, as well as with building height, was much higher than SUHIIr. Both SUHIIc and SUHIIr decreased with SVF, but the rate of decrease of SUHIIc was higher than SUHIIr. Both SUHIIc and SUHIIr initially increased with building height variance and then remained Abbreviations: SUHIIc, The difference between the complete surface temperature of reference rural areas and the complete surface temperature of urban areas; SUHIIr, The difference between the radiometric surface temperature of reference rural areas and the radiometric surface temperature of urban areas; UHII, The difference between air temperature of reference rural station and the air temperature of urban stations.

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E ((), i) = τ_{i} ([], normalε ((), i) B ((), T_{r} ((), i)) + ((), 1 - normalε ((), i)) R_{at}^{↓} ((), i)) + R_{at}^{↑} ((), i)

…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…The method of Yang et al . (2020a), therefore, is not limited to the specific conditions applying to the image data used to evaluate and demonstrate the approach.…”

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Assessing the impact of urban geometry on surface urban heat island using complete and nadir temperatures

Yang

Menenti

et al. 2020

Intl Journal of Climatology

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Thermal Infrared Imaging of the Urban Landscape to Understand Urban Microclimate

Yang

Menenti

Wong

et al. 2021

Urban Remote Sensing

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Utility of thermal remote sensing for evaluation of a high‐resolution weather model in a city

Hall,

Blunn,

Grimmond

et al. 2024

Quart J Royal Meteoro Soc

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Progress in high‐resolution numerical weather prediction (NWP) for urban areas will require new modelling approaches and extensive evaluation. Here, we exploit land surface temperature (LST) data from Landsat‐8 to assess 100 m resolution NWP for London (UK) on four cloud‐free days. The LST observations are directional radiometric temperatures with non‐negligible uncertainties. We consider the challenges of informative comparison between the Landsat LST and the NWP scheme's internal characterisation of the complete surface temperature. The LST spatial coverage allows large‐scale observation–model differences to be explored. In one case, obvious spatial artifacts in the NWP surface temperature are observed relative to the Landsat LST. These are found to be related to the NWP's initial method of downscaling of soil moisture using soil properties. Updated model runs have higher spatial correlation between model and Landsat LST. In cases where meteorological conditions favour the formation of horizontal convective rolls, warmer air temperatures associated with updraughts in the mixed layer extend inappropriately to the urban surface. This manifests as warm stripes in the model surface temperature that are not present in the Landsat LST. NWP–Landsat LST differences are larger in more built‐up areas on days nearer summer solstice. This is largely attributed to urban thermal anisotropy, as Landsat preferentially views warmer urban surfaces, whereas the model LST represents all surfaces. We evaluate two approaches to quantify this sampling effect, but further work is needed to fully constrain it and facilitate more informative model evaluation.

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A semi-empirical method for estimating complete surface temperature from radiometric surface temperature, a study in Hong Kong city

Cited by 26 publications

References 45 publications

Assessing the impact of urban geometry on surface urban heat island using complete and nadir temperatures

Assessing the impact of urban geometry on surface urban heat island using complete and nadir temperatures

Thermal Infrared Imaging of the Urban Landscape to Understand Urban Microclimate

Utility of thermal remote sensing for evaluation of a high‐resolution weather model in a city

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