AIR Builds Ground Network to Validate Satellite Vegetation Products

A ground network, which contains a canopy analyzer and a leaf area index (LAI) wireless sensor system has been built and passed the acceptance check, according to the National Engineering Laboratory of Remote Sensing Satellite Applications at the Aerospace Information Research Institute (AIR) on September 14, 2020.

Oct 13, 2020

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Researchers Reveal Relationship of Global Soil Respiration with Climate and Land Cover Changes

A research team led by Prof. NIU Zheng from the State Key Laboratory of Remote Sensing Sciences, Aerospace Information Research Institute (AIR) of the Chinese Academy of Sciences (CAS), and their cooperators proposed a remote-sensing driven model to estimate global Rs and analyzed its relationship with climate and land-cover.

Oct 09, 2020

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3.5 Billion Years Old---Geologic Age of Finsen Crater on Farside of Moon Determined

The absolute model age (AMA), or geologic age of Finsen crater on the Moon’s farside is determined to be about 3.5 billion years (Ga) based on crater counting method, according to a research paper titled “Absolute model age of lunar Finsen crater and geologic implications” which was published online in the journal of Icarus. The research is conducted by the planetary mapping and remote sensing team led by Prof. DI Kaichang from the State Key Laboratory of Remote Sensing Sciences under the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS).

Sep 04, 2020

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Satellite-based Remote Sensing Monitoring in Support of Forestry and Grassland Pest and Disease Control of China

"Thanking to the dynamic monitoring and early warning reports routinely provided by the Aerospace Information Research Institute (AIR) on pests and diseases, China has realized effective prevention and control of biological pests and diseases over forests and grasslands recent years”, according to the National Forestry and Grassland Administration.

Aug 27, 2020

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CAS Scientists Propose Deep Learning Method for Atmospheric Aerosol Retrieval

A research team led by Prof.LI Zhengqiang from the Aerospace Information Research Institute (AIR),Chinese Academy of Sciences (CAS),together with their cooperators proposed an artificial Neural Network method for AEROsol retrieval (NNAero) to jointly retrieve FMF and AOD derived from MODIS data. The research was published in Remote Sensing of Environment.

Aug 26, 2020

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