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地理科学与资源研究所 [8]
北京大学 [1]
东北地理与农业生态研... [1]
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期刊论文 [11]
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2018 [4]
2017 [2]
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Encoder-Decoder Full Residual Deep Networks for Robust Regression and Spatiotemporal Estimation
期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 卷号: 32, 期号: 9, 页码: 4217-4230
作者:
Li, Lianfa
;
Fang, Ying
;
Wu, Jun
;
Wang, Jinfeng
;
Ge, Yong
收藏
  |  
浏览/下载:80/0
  |  
提交时间:2021/11/05
Bias
deep learning
encoder-decoder
full residual deep network
non-linear regression
prediction of satellite aerosol optical depth (AOD) and PM2.5
spatiotemporal modeling
A Framework to Predict High-Resolution Spatiotemporal PM(2.5)Distributions Using a Deep-Learning Model: A Case Study of Shijiazhuang, China
期刊论文
REMOTE SENSING, 2020, 卷号: 12, 期号: 17, 页码: 33
作者:
Zhang, Guangyuan
;
Lu, Haiyue
;
Dong, Jin
;
Poslad, Stefan
;
Li, Runkui
收藏
  |  
浏览/下载:17/0
  |  
提交时间:2021/03/16
PM2.5
AOD
XGBoost
prediction
deep learning
ConvLSTM
SARIMA
Estimating Spatio-Temporal Variations of PM2.5 Concentrations Using VIIRS-Derived AOD in the Guanzhong Basin, China
期刊论文
REMOTE SENSING, 2019, 卷号: 11, 期号: 22, 页码: 22
作者:
Zhang, Kainan
;
de Leeuw, Gerrit
;
Yang, Zhiqiang
;
Chen, Xingfeng
;
Su, Xiaoli
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2020/06/05
VIIRS AOD
PM2.5
Guanzhong Basin
Geographically weighted regression
Generalized additive model
Retrieval of Daily PM2.5 Concentrations Using Nonlinear Methods: A Case Study of the Beijing-Tianjin-Hebei Region, China
期刊论文
REMOTE SENSING, 2018, 卷号: 10, 期号: 12, 页码: 17
作者:
Li, Lijuan
;
Chen, Baozhang
;
Zhang, Yanhu
;
Zhao, Youzheng
;
Xian, Yue
收藏
  |  
浏览/下载:96/0
  |  
提交时间:2019/05/23
daily PM2
5concentrations
remote sensing
MODIS AOD
machine learning algorithm
spatial and temporal distribution
Spatiotemporal patterns of PM10 concentrations over China during 2005-2016: A satellite-based estimation using the random forests approach
期刊论文
ENVIRONMENTAL POLLUTION, 2018, 卷号: 242, 页码: 605-613
作者:
Chen, Gongbo
;
Wang, Yichao
;
Li, Shanshan
;
Cao, Wei
;
Ren, Hongyan
收藏
  |  
浏览/下载:41/0
  |  
提交时间:2019/05/23
PM10
AOD
Random forests
China
Estimation of PM2.5 concentrations at a high spatiotemporal resolution using constrained mixed-effect bagging models with MAIAC aerosol optical depth
期刊论文
REMOTE SENSING OF ENVIRONMENT, 2018, 卷号: 217, 页码: 573-586
作者:
Li, Lianfa
;
Zhang, Jiehao
;
Meng, Xia
;
Fang, Ying
;
Ge, Yong
收藏
  |  
浏览/下载:33/0
  |  
提交时间:2019/05/23
PM2.5
MAIAC AOD
High spatiotemporal resolution
Temporal variation
AOD-PM2.5 associations
Spatial effects
Missingness
Machine learning
Estimating spatiotemporal distribution of PM1 concentrations in China with satellite remote sensing, meteorology, and land use information
期刊论文
ENVIRONMENTAL POLLUTION, 2018, 卷号: 233, 页码: 1086-1094
作者:
Chen, Gongbo
;
Knibbs, Luke D.
;
Zhang, Wenyi
;
Li, Shanshan
;
Cao, Wei
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  |  
浏览/下载:34/0
  |  
提交时间:2019/05/30
PM1
Aerosol optical depth
Meteorology
Land use
China
Estimating ground-level PM2.5 concentrations in Beijing using a satellite-based geographically and temporally weighted regression model
期刊论文
REMOTE SENSING OF ENVIRONMENT, 2017, 卷号: 198, 页码: 140-149
作者:
Guo, Yuanxi
;
Tang, Qiuhong
;
Gong, Dao-Yi
;
Zhang, Ziyin
收藏
  |  
浏览/下载:16/0
  |  
提交时间:2019/09/25
PM2.5
Aerosol optical depth
MODIS
Geographically and temporally weighted
regression
Beijing
Evaluating the Use of DMSP/OLS Nighttime Light Imagery in Predicting PM2.5 Concentrations in the Northeastern United States
期刊论文
REMOTE SENSING, 2017, 卷号: 9, 期号: 6, 页码: 16
作者:
Li, Xueke
;
Zhang, Chuanrong
;
Li, Weidong
;
Liu, Kai
收藏
  |  
浏览/下载:40/0
  |  
提交时间:2019/09/25
PM2.5
nighttime light (NTL)
Vegetation Adjusted NTL Urban Index (VANUI)
aerosol optical depth (AOD)
geographically weighted regression (GWR)
VIIRS-based remote sensing estimation of ground-level PM2.5 concentrations in Beijing-Tianjin-Hebei: A spatiotemporal statistical model
期刊论文
REMOTE SENSING OF ENVIRONMENT, 2016
Wu, Jiansheng
;
Yao, Fei
;
Li, Weifeng
;
Si, Menglin
收藏
  |  
浏览/下载:5/0
  |  
提交时间:2017/12/03
PM2.5
VIIRS AOD
NO2
Time fixed effects regression model
Geographically weighted regression
Beijing-Tianjin-Hebei
FINE PARTICULATE MATTER
LAND-USE REGRESSION
GEOGRAPHICALLY WEIGHTED REGRESSION
LONG-TERM EXPOSURE
AIR-POLLUTION
QUALITY
SPACE
CHINA
MODIS
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