We have estimated full-coverage, daily 1-km PM2.5 data from 2000 to 2020 in China using a random forest-based hindcast modeling method which incorporates historical information into modeling. Multiple sources were used as inputs, including MAIAC AOD, meteorological data from CMA, reanalysis data from ERA-5, and other land-related data. The annual average data during 2000-2020 are released here and free for non-commercial use. This manuscript is under review. If you want use our dataset, please cite the following article at this moment. If you want more data (e.g.daily/monthly data) or further collaborate with us, please contact us via qqhe@whut.edu.cn. If you have any question regarding the dataset, feel free to contact me via qqhe@whut.ed...
The high-resolution (1 km) and high-quality PM10 dataset in China (i.e., ChinaHighPM10 dataset) from...
The high-resolution (1 km) and high-quality PM1 data set in China (i.e., ChinaHighPM1 data set) from...
Background: Machine learning algorithms have very high predictive ability. However, no study has use...
We have estimated full-coverage, daily 1-km PM2.5 data from 2000 to 2020 in China using a random for...
We have estimated full-coverage, daily 1-km PM2.5 data from 2000 to 2022 in China using a random for...
We have estimated daily 1-km PM2.5 data from 2000 to 2020 in China through an adaptive spatiotempora...
This is the monthly PM2.5 estimates across China from 2000 to 2022. If you want daily dataset, pleas...
1. We have estimated daily 1-km PM2.5 data from 2000 to 2018 in China through an adaptive spatiotemp...
We have estimated daily 3-km PM2.5 concentration from 2013 to 2017 in China using a spatiotemporal m...
ChinaHighPM2.5 is one of the series of long-term, full-coverage, high-resolution, and high-quality d...
High spatial resolution PM2.5 data covering a long time period are urgently needed to support popula...
The high-resolution (1 km) and high-quality PM2.5 data set in China (i.e., ChinaHighPM2.5 data set) ...
Fine particulate matter (PM2.5) has altered radiation balance on earth and raised environmental and ...
ChinaHighPM2.5 is one of the series of long-term, full-coverage, high-resolution, and high-quality d...
The aim of our study was to construct random forest models with high-performance, and estimate daily...
The high-resolution (1 km) and high-quality PM10 dataset in China (i.e., ChinaHighPM10 dataset) from...
The high-resolution (1 km) and high-quality PM1 data set in China (i.e., ChinaHighPM1 data set) from...
Background: Machine learning algorithms have very high predictive ability. However, no study has use...
We have estimated full-coverage, daily 1-km PM2.5 data from 2000 to 2020 in China using a random for...
We have estimated full-coverage, daily 1-km PM2.5 data from 2000 to 2022 in China using a random for...
We have estimated daily 1-km PM2.5 data from 2000 to 2020 in China through an adaptive spatiotempora...
This is the monthly PM2.5 estimates across China from 2000 to 2022. If you want daily dataset, pleas...
1. We have estimated daily 1-km PM2.5 data from 2000 to 2018 in China through an adaptive spatiotemp...
We have estimated daily 3-km PM2.5 concentration from 2013 to 2017 in China using a spatiotemporal m...
ChinaHighPM2.5 is one of the series of long-term, full-coverage, high-resolution, and high-quality d...
High spatial resolution PM2.5 data covering a long time period are urgently needed to support popula...
The high-resolution (1 km) and high-quality PM2.5 data set in China (i.e., ChinaHighPM2.5 data set) ...
Fine particulate matter (PM2.5) has altered radiation balance on earth and raised environmental and ...
ChinaHighPM2.5 is one of the series of long-term, full-coverage, high-resolution, and high-quality d...
The aim of our study was to construct random forest models with high-performance, and estimate daily...
The high-resolution (1 km) and high-quality PM10 dataset in China (i.e., ChinaHighPM10 dataset) from...
The high-resolution (1 km) and high-quality PM1 data set in China (i.e., ChinaHighPM1 data set) from...
Background: Machine learning algorithms have very high predictive ability. However, no study has use...