The BIRDS series from Kyushu Institute of Technology has deployed 1U CubeSat constellations from International Space Station since 2017. BIRDS-3 was deployed in June 2019. Lessons learnt from BIRDS-1 and BIRDS-2 have been used to improve the bus system of BIRDS-3. Improvements have been made in On-Board Computer, Electrical Power and Communication systems. BIRDS-3 has implemented novel Backplane Mission which uses SoftCIB; an in-house designed software defined backplane interface board. The mission has the potential to standardize interface and cut down on development time. BIRDS-3 project has placed a LoRa module to check its performance in space. The module has the potential for future low-cost, low-powered Store and Forward mission and CubeSat communication system. This paper provides detailed information on the improved BIRDS bus system, LoRa Demonstration and Backplane Mission designs, and onorbit results since its deployment in June 2019. The results presented are based on cumulative operation time of three years for three satellites operating each for a year. The satellites are functional and will remain in orbit until summer of 2021.
Earth observation (EO) missions remain a challenging task for small satellite platforms due to their demanding requirements and space environment effects. In this study, the camera payload development and mission requirements are presented together with the ground-based testing results for a 6U CubeSat called KITSUNE, operating at low Earth orbit. The major challenge of the payload development is maintaining the focus of the optical system despite the thermal vacuum environment in orbit since the low thermal capacity and rapid temperature variation of CubeSats hinder the camera focus. First, the payload is developed with an objective of a 5-m-class imaging mission, which has a 31.4 MP CMOS sensor and a lens with a 300-mm focal length. Second, polyimide heaters and multilayer insulators are utilized in order to maintain focus during imaging operations. Third, a collimator lens is used to aid in image capture during thermal vacuum tests. These images are analyzed thoroughly using various focus measure operators. The Diagonal Laplacian was found to be the most suitable operator due to the consistency in test results. The results also showed that the heat generated by the camera sensor significantly affects the lens temperature and, ultimately, the target temperature of the lens was defined at −1.8°C. Finally, the test results are discussed, including thermal vacuum, vibration, total ionization dose, and the effect of exposure to direct sunlight on the CMOS sensor.
This paper presents a study to identify the relationship between vegetation phenology and landslide using remote sensing to access landslide prone areas in an event of an earthquake. A landslide triggered after the April 2015 earthquake in Manaslu Conservation Area in Gorkha District of Nepal was used as a study site. The method proposed in the paper uses pre-and post-event LANDSAT8 Operational Land Imager (OLI) images and uses Normalized Difference Vegetation Index (NDVI) for understanding the correlation between vegetation phenology of the study site to the landslide. Comparative study of the result shows lower NDVI mean value after the earthquake and shows that a slope with NDVI mean value lower than 0.247 could be landslide prone. Implication of the result, if confirmed, could aid in identifying landslide prone areas and implementing mitigation programs to either re-vegetate the slope or relocate residents directly under threat.
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