%0 Journal Article %1 journals/remotesensing/ZhangLDPLZR20 %A Zhang, Guangyuan %A Lu, Haiyue %A Dong, Jin %A Poslad, Stefan %A Li, Runkui %A Zhang, Xiaoshuai %A Rui, Xiaoping %D 2020 %J Remote. Sens. %K dblp %N 17 %P 2825 %T A Framework to Predict High-Resolution Spatiotemporal PM2.5 Distributions Using a Deep-Learning Model: A Case Study of Shijiazhuang, China. %U http://dblp.uni-trier.de/db/journals/remotesensing/remotesensing12.html#ZhangLDPLZR20 %V 12

@article{journals/remotesensing/ZhangLDPLZR20, added-at = {2020-10-06T00:00:00.000+0200}, author = {Zhang, Guangyuan and Lu, Haiyue and Dong, Jin and Poslad, Stefan and Li, Runkui and Zhang, Xiaoshuai and Rui, Xiaoping}, biburl = {https://www.bibsonomy.org/bibtex/2090dd764c7b1e0dbfdfc7e8f64dc833a/dblp}, ee = {https://doi.org/10.3390/rs12172825}, interhash = {40079052345749d31aa7d0a9db154491}, intrahash = {090dd764c7b1e0dbfdfc7e8f64dc833a}, journal = {Remote. Sens.}, keywords = {dblp}, number = 17, pages = 2825, timestamp = {2020-10-07T11:34:26.000+0200}, title = {A Framework to Predict High-Resolution Spatiotemporal PM2.5 Distributions Using a Deep-Learning Model: A Case Study of Shijiazhuang, China.}, url = {http://dblp.uni-trier.de/db/journals/remotesensing/remotesensing12.html#ZhangLDPLZR20}, volume = 12, year = 2020 }