Trapezoid-based surface soil moisture retrieval using a pixel-to-pixel scheme: A preliminary result over the North China Plain

Leng, Pei; Li, Zhao-Liang; Liao, Qian‐Yu; Ma, Jing; Sun, Yayong; Song, Qi; Zhang, Xia; Shang, Gao

doi:10.1016/j.jhydrol.2022.128350

Cited by 2 publications

(2 citation statements)

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“…Therefore, it is used in the global meteorological model prediction, earth surface, and atmospheric interaction studies. 5 Since 1980s, LST retrieval using satellite thermal infrared (TIR) observations has been most intriguing subject of the scientific society. Atmospheric correction is an essential part of the LST retrieval methodology, because an atmospheric constituent attenuates the surface leaving radiation.…”

Section: Introductionmentioning

confidence: 99%

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Retrieval of land surface temperature from INS-2TD thermal infrared observations using a generalized single-channel algorithm over South-Asia region

Dave,

Pandya,

Shah

et al. 2024

J. Appl. Rem. Sens.

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The experimental Indian Nano-Satellite (INS)-2TD acquires data in a long-wave infrared (7 to 16 μm) region with a fairly good spatial resolution of 175 m. Our study focuses on the retrieval of land surface temperature (LST) using a physics-based generalized single-channel (GSC) algorithm for the INS-2TD observations. A total of 597,240 at-sensor radiance simulations were carried out using moderate resolution atmospheric transmittance 5.3 radiative transfer model for varying conditions pertaining to surface, atmosphere, and sensor geometry to develop and validate the GSC algorithm for broadband INS-2TD sensor. The result from simulated test dataset shows the algorithm's consistent performance with root-mean-square error (RMSE) of 2.87 K and 0.97 R 2 . Pixel-to-pixel intercomparison of retrieved LST and standard LST product of Indian National Satellite (INSAT)-3D indicates a good agreement with 0.99 R 2 and range of RMSE from 1.17 to 4.78 K over the six selected datasets of South-Asia. The results reveal that the retrieved INS-2TD LST products perform very well, except having a hot bias of around 4.78 K compared to INSAT-3D LST over the Himalayan mountains due to the topographic effect. These results show the overall reasonable accuracy of the retrieved LST over heterogeneous surfaces and highly dynamic atmospheric conditions.

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Section: Introductionmentioning

confidence: 99%

“… – 4 LST retrieval through satellite observations is frequent and covers larger areas with good spatial resolution. Therefore, it is used in the global meteorological model prediction, earth surface, and atmospheric interaction studies 5 …”

Section: Introductionmentioning

confidence: 99%