A Review of Spatiotemporal Super-Resolution Mapping for Remote Sensing Data Fusion

Presently, due to the limitations of satellite launch cost and existing technology, it is scarcely possible to obtain single remotely sensed images with both fine-spatial resolution and high temporal resolution at the same time freely. For solving this kind of predicament, an effective method is to fuse multisource remote sensing data by using spatial–temporal super-resolution mapping (STSRM) algorithms. STSRM is developed on the foundation of super-resolution mapping (SRM), which is used for generating land-cover map with a finer spatial resolution by allocating subpixels position in the mixed pixels of coarse remotely sensed images. This review summarizes the existing mainstream models of spatiotemporal SRM and concludes the advantages and limitations of these methods. At the same time, this article analyzes methods of classification accuracy assessment, expounds the existing problems and challenges, and makes a forward-looking prospect for the future development direction of spatiotemporal SRM.

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Development of a Molecular Assessment High-Resolution Observation Spectrometer (MAHOS) for Microsatellites

Compact and lightweight sensors with a high-frequency resolution are required for the passive observation of atmospheric water and oxygen emission lines at a reduced cost and power consumption. A molecular assessment high-resolution observation spectrometer (MAHOS) is developed as a compact, low power, digital fast Fourier transform spectrometer to be installed on a microsatellite. MAHOS has a compact design with dimensions of 0.154×0.125×0.040 m3 and mass of 0.7 kg. It uses only a few materials including a field-programmable gate array (FPGA) module with a lightweight aluminum alloy box. The highly stable spectrometer exhibits a sampling speed of 2.6624 GS/s and 16 384 frequency channels. The stability of the spectrometer is longer than 1200 s within the 1-GHz bandwidth. Thermal dissipation is achieved through a heat conductive gel filled in the gap between the most heat-generating component, the FPGA, and the aluminum alloy case. Results of a finite element analysis indicate that the design is stiff and stable enough to survive in the launch environment. Thermal analysis indicates the durability of the system during operation. Even in space where heat dissipation is not possible, self-heating temperatures are not a problem for the FPGA. In the future, the performance of the spectrometer will be verified by conducting environmental tests.

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Anticipation of Air Pollution Density Patterns Affected by Wind Velocity Based on Fourier Transform Spectrometer Across the Silk Road Countries by Using EcoBeltSat—A 6U CubeSat

EcoBeltSat is a 6U nanosatellite (CubeSat) able to offer access on space for scientists to determine the effects of cross-border air pollution flux, and acquire a more precise understanding of climate change and global warming for the Belt and Road countries. The objective of this CubeSat mission is demonstrated by the use of an onboard atmospheric spectrometer as the first payload. Therefore, a second payload is suggested to estimate and localize renewable energy sources in these countries. The aim of this mission is achieved based on Fourier transform spectrometer (FTS), which is used for wind velocity measurement around the globe by using Cubesats. This data can offer confidence to the investors in the sector of renewable energy projects, for example, wind farms, solar power plants, and other systems. In this article, the association of air pollution measurements by the spectrometer and the wind velocity measurements by FTS instrument is proposed to give an innovative idea and the opportunity for a spaceborne predictive pollution map which avoid the actual implementation of billions of sensors implanted on the ground around the world.

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