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This letter presents a method to calculate the width \omega over the half-period of the cosine term in a diurnal temperature cycle (DTC) model. \omega deduced from the thermal diffusion equation (TDE) is compared with \omega obtained from solar geometry. The results demonstrate that \omega deduced from the TDE describes the shape of the DTC model more adequately around sunrise and the time of maximum temperature than \omega obtained from solar geometry. Additionally, taking into account the physical continuity of land surface temperature (LST) variation, a day-to-day temporal progression (DDTP) model of LST is developed to model several days of DTCs. The results indicate that the DDTP model fits in situ [or Spinning Enhanced Visible and Infrared Imager (SEVIRI)] LST well with a root-mean-square error (RMSE) less than 1 K. Compared with the DTC model, the DDTP model slightly increases the quality of LST fits around sunrise. Assuming that only six LST measurements corresponding to the NOAA/AVHRR and MODIS overpass times for each day are available, several days of DTCs can be predicted by the DDTP model with an RMSE less than 1.5 K. [ABSTRACT FROM PUBLISHER]

Radiometric calibration is a prerequisite to quantitative remote sensing, and its accuracy has a direct impact on the reliability and accuracy of the quantitative application of remote-sensing data. This article attempts to cross-calibrate the visible and near-infrared channels 1 (450–520 nm), 2 (520–590 nm), 3 (630–690 nm), and 4 (770–890 nm) of the China–Brazil Earth Resources Satellite (CBERS)-02B/charge-coupled device (CCD) camera with channels 3 (459–479 nm), 4 (545–565 nm), 1 (620–670 nm), and 2 (841–876 nm) of the Terra/Moderate Resolution Imaging Spectroradiometer (MODIS), respectively. The radiative transfer modelling (RTM) method is implemented using the CBERS-02B/CCD and Terra/MODIS measurements at the Dunhuang radiometric calibration site in October 2008. The differences between the cross-calibration and vicarious calibration techniques for channels 1, 2, 3, and 4 are 11.15%, –0.89%, 2.88%, and 11.28%, respectively. Furthermore, the accuracies of the cross-calibration coefficients of CBERS-02B/CCD are analysed, wherein the results indicate that the calibration uncertainty is within 5%. [ABSTRACT FROM PUBLISHER]

Under the influence of Sima Xiangru's gorgeous style of writing, Yang Xiong created four brilliant poetic essays-' Ganquan Fu, Hedong Fu, Yulie Fu and ' Changyang Fu", of which Changyang Fu is the most special. There exist three different views on this essay that it is an apology like Sima Xiangru's prose- Blaming the Shu People,that it marked the beginning of prose fu and that it is a link in the stylistic shift of Hanfu. In the present author's opinion, these views are just talks in generalities. If we examine the background and narrative structure of Changyang Fu, we find that they are closely related to the arguments on the system of emperors' temples, which included the rise of Confucianism,the political appeals of scholars, the return to the patriarchal clan system,and the advocacy of Zhou Dynasty's social institutions. Although the controversy between the monarch and the Confucian scholars was never resolved,the three temples,Temple of Emperor Gaozu,Temple of Emperor Wen and Temple of Emperor Wu were preserved. It was against this background that "Changyang Fu" was written,and it was the notion that the ancestors have merits and the family has virtue that decided the structure of narration and the connotation of Tactful Admonition,among which the idea of getting rid of lechery and the genre of apology has specially far-reaching impact on the writing of Dafu in the Eastern Han Dynasty. [ABSTRACT FROM AUTHOR]

Hyperspectral thermal infrared (HTIR) data offers enormous potential for land surface temperature (LST) and emissivity (LSE) inversion. Methods to fully use a large amount of spectral information, while avoiding data redundancy, is constantly being explored. Therefore, a new framework for LST and LSE inversion using HTIR data is proposed in this study. First, the stepwise iteration method based on information content was used to select channels that were more sensitive to land surface information. Principal component analysis (PCA) and a two-step machine learning method were then used to retrieve the LST and LSE based on the selected channels. The findings demonstrate that the LST and spectra of the LSE can be obtained simultaneously based on the proposed framework. An LST inversion accuracy of 1.5K and an emissivity inversion accuracy of 0.017 can be achieved. However, an increase in the number of channels does not result in superior outcomes. Satisfactory inversion results can be obtained by selecting only 10–35 channels with the highest information content. In conclusion, this framework can be used to guide channel selection and land surface parameters inversion for HTIR sensors. [ABSTRACT FROM AUTHOR]