%0 Dataset
%T Daily 1-km gap-free AOD grids in China(2000–2020)
%J National Cryosphere Desert Data Center
%I National Cryosphere Desert Data Center(www.ncdc.ac.cn)
%U http://www.ncdc.ac.cn/portal/metadata/3fc0f146-3f29-4036-934a-16c78c8e569f
%W NCDC
%R 10.5281/zenodo.5652257
%A Bai Kaixu
%K AOD;air pollution;LGHAP
%X The long-term gapless high-resolution air pollutant concentration dataset (LGHAP) is of great significance for environmental management and Earth system science analysis. This dataset contains daily data of seamless AOD products in China's land region from 2000 to 2020, with a resolution of 1 kilometer. By seamlessly integrating tensor flow based multimodal data fusion with set learning based knowledge transfer in statistical data mining. The proposed method integrates a group of AOD data tensors obtained from different sensors or platforms and other relevant data sets (such as air pollutant concentration and atmospheric visibility) for high-dimensional grid data analysis through spatial pattern recognition, so as to achieve data fusion and multi-resolution image analysis. Daily seamless AOD is provided in NetCDF format, and data from each year is archived in compressed file format. In addition, Python, Matlab, R, and IDL code are provided to assist users in reading and visualizing LGHAP data.