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Chinese Scientists Develop Revolutionary Multi-Dimensional Data Format for Remote Sensing
After more than a decade of dedicated work, Zhang’s team at AIR has become the first in the world to develop a fully integrated approach to managing multi-dimensional spatial-temporal-spectral data. This approach unifies spatial, temporal, and spectral data into a single format, making data organization, visualization, and extraction more streamlined than ever. The new MDD format brings remarkable gains in efficiency and accuracy to remote sensing analysis.
Nov 12, 2024
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OCANet: A Powering Tool for Accurate Building Identification in Satellite Imagery
A new study introduces OCANet, a powerful tool for accurately identifying buildings in satellite images, marking an advancement in urban mapping technology. Published in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing on October 21, the study highlights how OCANet can make city planning, disaster response, and environmental monitoring more effective.
Nov 08, 2024
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High-Resolution Population Mapping Achieved for Greater Bay Area with SDGSAT-1 Imagery and Deep Learning
A new study published in the International Journal of Digital Earth on October 20 utilizes the advanced capabilities of the Sustainable Development Science Satellite-1 (SDGSAT-1) to produce an unprecedented high-resolution population map of the Guangdong-Hong Kong-Macao Greater Bay Area. Researchers from the Aerospace Information Research Institute (AIR) under the Chinese Academy of Sciences employed SDGSAT-1’s innovative glimmer imaging and advanced deep learning techniques to deliver a more accurate population distribution at a fine scale, offering valuable insights for urban planning, disaster preparedness, and sustainable development.
Nov 05, 2024
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Low-Curvature Microelectrode Arrays Offer Insights into Spatial Cognitive Information Coding of Ventral Tegmental Area
The“Micro-Nano Sensing Technology”creative research group of NSFC from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences, led by Professor CAI Xinxia, has developed a new method for fabricating high-precision, low-curvature microelectrode arrays (MEAs). The MEAs are designed for recording neuronal activities in brain's deep, small volume region. Published in the Microsystems & Nanoengineering on October 14, the study implanted the low-curvature MEAs into the ventral tegmental area (VTA) of rats, employing a modified T-maze to highlight the VTA's important role in reward processing and spatial information coding during goal-directed navigation.
Oct 31, 2024
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Drug-Loaded Hydrogel Microelectrode Arrays Significantly Boost Brain-Computer Interface Performance：Study
The“Micro-Nano Sensing Technology” creative research group of NSFC from the Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences, led by Professor CAI Xinxia, has made a breakthrough in brain-computer interface technology. The team developed a novel drug-loaded hydrogel-coated microelectrode array (MEA), which allows for long-term, high-quality detection of neural activity. The study was published in the journal Biosensors and Bioelectronics.
Oct 24, 2024
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