Determination of global land surface temperature using data from only five selected thermal infrared channels: Method extension and accuracy assessment

Zheng, Xiaopo; Li, Zhao-Liang; Wang, Tianxing; Huang, Huabing; Nerry, Françoise

doi:10.1016/j.rse.2021.112774

Cited by 24 publications

(7 citation statements)

References 78 publications

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“…The formula L sen is the brightness of the thermal radiation received by the sensor in units [W/(m 2 sr μm)]; T sen represents the brightness temperature in K; λ is the effective wavelength in μm; ε is the surface specific emissivity; δ is the surface specific emissivity; C 1 = l.19104 W × 108 W/(m 2 ·sr·m); C 2 = 1.43877 × 104 mK; In the surface temperature inversion formula ψ 1 , ψ 2 , and ψ 3 are intermediate variables that are cubic trinomials concerning atmospheric water vapor content ω, and the function expression is as follows (Zheng et al, 2022):…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Study of Urban Heat Island Effect in Hangzhou Metropolitan Area Based on SW-TES Algorithm and Image Dichotomous Model

Shang,

Xu,

Liu

et al. 2023

Sage Open

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In recent years, with economic development, urbanization has been accelerating. In the past 100 years, the global average temperature has increased by 0.5°C, and according to the predictions of most global climate models, the temperature will continue to increase by 1.5°C to 3.0°C in the next 100 years. Under the influence of global warming, the urban heat island effect problem is becoming more and more serious, bringing much harm. Studying the thermal effect and its influencing factors is of great significance for sustainable urban development. In this study, the seasonal and interannual surface temperature changes of the study area are inverted based on the SW-TES algorithm, and the LST inversion of the algorithm is simply verified. At the same time, a cell dichotomous model was established to explore the influencing factors of the urban heat island effect and the influence of different land use types and normalized vegetation indices in the Hangzhou metropolitan area was analyzed. The results showed that the overall heating trend of the study area showed a heating trend, the expansion rate of regional construction land was relatively fast, and the scale of urban land was increasing. Based on the results of surface temperature changes of areas with different land types, we obtained the temperature trends of each land type [from 2005 to 2018] and found that there was a negative correlation between surface temperature and normalized vegetation index. This study provides a theoretical basis to evaluate the urban heat island effect and analyze factors that impact it and would promote sustainable urban development.

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Section: Methodsmentioning

confidence: 99%

“…The surface temperature is first inverted using a single-channel algorithm and thermal infrared to bring in the thermal emissivity of the surface combined with the atmospheric water vapor content to be able to invert the surface air temperature. The equations are as follows (Zheng et al, 2022):…”

Section: Methodsmentioning

confidence: 99%

Study of Urban Heat Island Effect in Hangzhou Metropolitan Area Based on SW-TES Algorithm and Image Dichotomous Model

Shang,

Xu,

Liu

et al. 2023

Sage Open

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“…Therefore, the experiments were conducted in relatively dry atmospheric conditions in this paper. The use of more robust LST estimation methods, such as the hybrid algorithm that requires no additional input [42][43][44], will be applied to enable the algorithms to be suitable to a wider range of atmospheric conditions. Moreover, the empirical relationship between solar radiance and CWV has been summarized in previous studies [45].…”

Section: Future Improvements Of the Proposed Methodsmentioning

confidence: 99%

Mid-Infrared Emissivity Retrieval from Nighttime Sentinel-3 SLSTR Images Combining Split-Window Algorithms and the Radiance Transfer Method

Ren

Wang

et al. 2022

IJERPH

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Land surface emissivity is a key parameter that affects energy exchange and represents the spectral characteristics of land cover. Large-scale mid-infrared (MIR) emissivity can be efficiently obtained using remote sensing technology, but current methods mainly rely on prior knowledge and multi-temporal or multi-angle remote sensing images, and additional errors may be introduced due to the uncertainty of external data such as atmospheric profiles and the inconsistency of multiple source data in spatial resolution, observation time, and other information. In this paper, a new practical method was proposed which can retrieve MIR emissivity with only a single image input by combining the radiance properties of TIR and MIR channels and the spatial information of remote sensing images based on the Sentinel-3 Sea and land surface temperature radiometer (SLSTR) data. Two split-window (SW) algorithms that use TIR channels only and MIR and TIR channels to retrieve land surface temperature (LST) were developed separately, and the initial values of MIR emissivity were obtained from the known LST and TIR emissivity. Under the assumption that the atmospheric conditions in the local area are constant, the radiance transfer equations for adjacent pixels are iterated to optimize the initial values to obtain stable estimation results. The experimental results based on the simulation dataset and real SLSTR images showed that the proposed method can achieve accurate MIR emissivity results. In future work, factors such as angular effects, solar radiance, and the influence of atmospheric water vapor will be further considered to improve performance.

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“…Land surface temperature (LST) is one of the key parameters for studying processes in land surface systems at regional and global scales, enabling monitoring of the spatial and temporal variability in the energy balance state at the surface [ 1 , 2 , 3 , 4 ]. Satellite thermal infrared remote sensing is an effective means of obtaining LST [ 5 , 6 , 7 , 8 ]. With the rapid development of remote sensing technology and inversion algorithms, LST data obtained by thermal infrared remote sensing inversion algorithms are widely used in various fields, such as evapotranspiration and soil moisture estimation [ 9 ], urban heat island studies [ 10 , 11 , 12 , 13 ], disaster monitoring [ 14 ], and environmental monitoring [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

A Quantitative Study of a Directional Heat Island in Hefei, China Based on Multi-Source Data

Shi

Jiang

et al. 2023

Sensors

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Surface urban heat islands (SUHIs) are essential for evaluating urban thermal environments. However, current quantitative studies of SUHIs ignore the thermal radiation directionality (TRD), which directly affects study precision; furthermore, they fail to assess the effects of TRD characteristics at different land-use intensities, on the quantitative studies of SUHIs. To bridge this research gap, this study eliminates the interference of atmospheric attenuation and daily temperature variation factors, in quantifying the TRD based on land surface temperature (LST), from MODIS data and station air temperature data for Hefei (China) from 2010–2020. The influence of TRD on SUHI intensity quantification was evaluated by comparing the TRD under different land-use intensities in Hefei. The results show that: (1) daytime and nighttime directionality can reach up to 4.7 K and 2.6 K, and occur in areas with the highest and medium urban land-use intensity, respectively. (2) There are two significant TRD hotspots for daytime urban surfaces, where the sensor zenith angle is approximately the same as the forenoon solar zenith angle, and where the sensor zenith angle is near its nadir in the afternoon. (3) The TRD can contribute up to 2.0 K to the results of assessing the SUHI intensity based on satellite data, which is approximately 31–44% of the total SUHI in Hefei.

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Determination of global land surface temperature using data from only five selected thermal infrared channels: Method extension and accuracy assessment

Cited by 24 publications

References 78 publications

Study of Urban Heat Island Effect in Hangzhou Metropolitan Area Based on SW-TES Algorithm and Image Dichotomous Model

Study of Urban Heat Island Effect in Hangzhou Metropolitan Area Based on SW-TES Algorithm and Image Dichotomous Model

Mid-Infrared Emissivity Retrieval from Nighttime Sentinel-3 SLSTR Images Combining Split-Window Algorithms and the Radiance Transfer Method

A Quantitative Study of a Directional Heat Island in Hefei, China Based on Multi-Source Data

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