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Remote Sensing Data Products to Facilitate Hainan's Sustainable Development
A database titled “Hainan Resources and Environment Data Product”was released on the website of the CASEarth thematic data system and shared to the public free of charge, according to the International Research Center of Big Data for Sustainable Development Goals.Based on the self-developed remote sensing big data service platform, a research team from the Aerospace Information Research Institute under the Chinese Academy of Sciences has developed a series of remote sensing data products for resources and environment in Hainan Province by integrating remote sensing image radiation and geometric normalization processing algorithms as well as remote sensing monitoring models in vegetation ecology, water environment, agriculture, coastal zone, and urban environment.
Apr 26, 2023
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Remote Sensing of Urban Green Space Published
The English monograph Remote Sensing of Urban Green Space, authored by Prof. MENG Qingyan from the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), was published by Springer Nature Group.This book presents a systematic study of urban green space remote sensing from multi-dimensional and multi-scale technologies.
Apr 20, 2023
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Sunlit Background Visible in Remote Sensing Images Controls Vertical Distributions of Stereoscopic Point Clouds in Forested Area
Forest three-dimensional structure measurement is a key factor in achieving high-precision estimation of vegetation carbon storage. Progress was made on how to use stereoscopic point cloud for forest three-dimensional structure observation,according to the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS).
Apr 20, 2023
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Chinese FY-3 Satellites Enrich Global Soil Moisture Dataset
A study entitled "A global daily soil moisture dataset derived from Chinese FengYun-3B Microwave Radiation Imager (MWRI) (2010-2019)" was published on Scientific Data. The relevant dataset is available online at the National Tibetan Plateau Data Center.Dr. YAO Panpan and Dr. ZHAO Tianjie from the State Key Laboratory of Remote Sensing Science with the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS) and Dr. LU Hui from Tsinghua University developed this new FY-3B global SSM product from 2010 to 2019, with a spatial resolution of 36 km.
Apr 04, 2023
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Study Reveals Influencing Factors on Global Waste Distribution via Deep-Learning Based Dumpsite Detection from Satellite Imagery
A study published in Nature Communications describes an efficient and intelligent dumpsite detection technique and analyses the correlation between the number of dumpsites and social/economic factors.This work is proposed by a research team of the Key Laboratory of Network Information System Technology at the Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS).
Mar 31, 2023
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