TY  - Data
T1  - China PM2.5 1km Spatial Distribution Dataset (2015-2018)
A1  - Ye Hong
DO  - 10.5281/zenodo.7857008
PY  - 2024
DA  - 2024-01-29
PB  - National Cryosphere Desert Data Center
AB  - At present, in the simulation of various atmospheric pollutants, the simulation of independent trace gases is constrained by the insufficient resolution of key remote sensing products, resulting in insufficient simulation reliability. This study combines spatial sampling and parameter convolution to optimize LightGBM using ground observations, remote sensing products, meteorological data, aid data, and random IDs. Through the above techniques and simulation of atmospheric pollutant sequences, we obtained seamless products with a daily resolution of 1 kilometer for PM2.5 in most parts of China from 2015 to 2018. Through random sampling, random site sampling, specific area validation, comparison of different models, and horizontal comparison of different studies, we have verified that our simulation of the spatial distribution of various atmospheric pollutants is reliable and effective.
DB  - NCDC
UR  - http://www.ncdc.ac.cn/portal/metadata/a00e30ec-7ad0-4573-a342-958cc01da645
ER  -