Articles | Volume 14, issue 2
https://doi.org/10.5194/essd-14-907-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-907-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
LGHAP: the Long-term Gap-free High-resolution Air Pollutant concentration dataset, derived via tensor-flow-based multimodal data fusion
Key Laboratory of Geographic Information Science (Ministry of
Education), School of Geographic Sciences, East China Normal University,
Shanghai 200241, China
Institute of Eco-Chongming, 20 Cuiniao Rd., Chongming, Shanghai
202162, China
Ke Li
Key Laboratory of Geographic Information Science (Ministry of
Education), School of Geographic Sciences, East China Normal University,
Shanghai 200241, China
Mingliang Ma
School of Surveying and Geo-Informatics, Shandong Jianzhu University,
Jinan 250101, China
Kaitao Li
State Environmental Protection Key Laboratory of Satellite Remote
Sensing, Aerospace Information Research Institute, Chinese Academy of
Sciences, Beijing 100101, China
Zhengqiang Li
State Environmental Protection Key Laboratory of Satellite Remote
Sensing, Aerospace Information Research Institute, Chinese Academy of
Sciences, Beijing 100101, China
State Key Laboratory of Severe Weather, Chinese Academy of
Meteorological Sciences, Beijing 100081, China
Ni-Bin Chang
Department of Civil, Environmental, and Construction Engineering,
University of Central Florida, Orlando, FL 32816, USA
Zhuo Tan
Key Laboratory of Geographic Information Science (Ministry of
Education), School of Geographic Sciences, East China Normal University,
Shanghai 200241, China
Di Han
Key Laboratory of Geographic Information Science (Ministry of
Education), School of Geographic Sciences, East China Normal University,
Shanghai 200241, China
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Latest update: 09 Dec 2023
Short summary
The Long-term Gap-free High-resolution Air Pollutant concentration dataset, providing gap-free aerosol optical depth (AOD) and PM2.5 and PM10 concentration with a daily 1 km resolution for 2000–2020 in China, is generated and made publicly available. This is the first long-term gap-free high-resolution aerosol dataset in China and has great potential to trigger multidisciplinary applications in Earth observations, climate change, public health, ecosystem assessment, and environment management.
The Long-term Gap-free High-resolution Air Pollutant concentration dataset, providing gap-free...
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