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Remote sensing has emerged as a new technique for collecting farmland data due to its rapid advancement, rising popularity, and application in social production practice. In order to understand and manage farmland resources in China, it is essential to account for and monitor high-standard farmland and its usage. Therefore, this work used satellite remote sensing empowered with various abilities for monitoring high-standard farmland by employing GF-2 high-resolution satellite images to identify targets and objects in Hebei and Guangdong provinces. Farmland occupation and utilization were analyzed by detecting destructions, underutilization, and overutilization, and converting farmland for other economic activities registered on a special field sheet for quantification. A statistical summary was compiled for the two provinces, and the results reveal that high-standard farmland irregularities were detected in both Hebei and Guangdong provinces. However, in Hebei province, this was due to domestic purposes, such as building home shelters and domestic factories. On a contract, the result shows that in Guangdong province, farmland was being converted for economic purposes on an industrial scale, such as high residential apartment blocks and new industrial zones, and environmental destruction. Furthermore, the results reveal that there is still a steady and continuous decline in arable land due to accelerated industrialization and population pressure, especially in the Guangdong provinces, which is a threat to national food security. The high interpretation accuracy demonstrates that high-resolution remote sensing is an effective farmland monitoring tool that can be used to advance policy formulation.

The absorption features of olivine in visible and near-infrared (VNIR) reflectance spectra are the key spectral parameters in its mineralogical studies. Generally, these spectral parameters can be obtained by exploiting the Modified Gaussian Model (MGM) with a proper continuum removal. However, different continua may change the deconvolution results of these parameters. This paper investigates the diagnostic spectral features of olivine with diverse chemical compositions. Four different continuum removal methods with MGM for getting the deconvolution results are presented and the regression equations for predicting the Mg-number (Fo#) are introduced. The results show that different continua superimposed on the mineral absorption features will make the absorption center shift, as well as the obvious alterations in shape, width, and strength of the absorption band. Additionally, it is also found that the logarithm of a second-order polynomial continuum can match the overall shape of the spectrum in logarithmic space, and the improved regression equations applied to estimate the chemical composition of olivine-dominated spectra also have a better performance. As an application example, the improved approach is applied to pulse laser irradiated olivine grains to simulate and study the space weathering effects on olivine diagnostic spectral features. The experiments confirm that space weathering can make the absorption band center shift toward longer wavelength. Therefore, the Fo# estimated from remote sensing spectra may be less than its actual chemical composition. These results may provide valuable information for revealing the difference between the spectra of olivine grains and olivine-dominated asteroids.