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Tongwen Li
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2020 – today
- 2024
- [j13]Shuting Jin
, Tianxing Wang, Huabing Huang
A self-adaptive wildfire detection algorithm by fusing physical and deep learning schemes. Int. J. Appl. Earth Obs. Geoinformation 127: 103671 (2024) - 2022
- [j12]Jingan Wu
Fusing Landsat 8 and Sentinel-2 data for 10-m dense time-series imagery using a degradation-term constrained deep network. Int. J. Appl. Earth Obs. Geoinformation 108: 102738 (2022) - [j11]Jiajia Chen, Huanfeng Shen, Xinghua Li, Tongwen Li
Ground-level ozone estimation based on geo-intelligent machine learning by fusing in-situ observations, remote sensing data, and model simulation data. Int. J. Appl. Earth Obs. Geoinformation 112: 102955 (2022) - [j10]Lingfeng Zhang
Deriving gapless CO2 concentrations using a geographically weighted neural network: China, 2014-2020. Int. J. Appl. Earth Obs. Geoinformation 114: 103063 (2022) - [j9]Yinghong Jing
Cascaded Downscaling-Calibration Networks for Satellite Precipitation Estimation. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j8]Tongwen Li
A Locally Weighted Neural Network Constrained by Global Training for Remote Sensing Estimation of PM₂.₅. IEEE Trans. Geosci. Remote. Sens. 60: 1-13 (2022) - [j7]Tongwen Li
An Enhanced Geographically and Temporally Weighted Neural Network for Remote Sensing Estimation of Surface Ozone. IEEE Trans. Geosci. Remote. Sens. 60: 1-13 (2022) - [i1]Yinghong Jing, Liupeng Lin, Xinghua Li, Tongwen Li, Huanfeng Shen:
An attention mechanism based convolutional network for satellite precipitation downscaling over China. CoRR abs/2203.14812 (2022) - 2021
- [j6]Tongwen Li
Estimating daily full-coverage surface ozone concentration using satellite observations and a spatiotemporally embedded deep learning approach. Int. J. Appl. Earth Obs. Geoinformation 101: 102356 (2021) - [j5]Jingan Wu
Hourly PM2.5 Concentration Monitoring With Spatiotemporal Continuity by the Fusion of Satellite and Station Observations. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 14: 8019-8032 (2021) - 2020
- [j4]Tongwen Li
Remote Sensing Estimation of Regional NO2 via Space-Time Neural Networks. Remote. Sens. 12(16): 2514 (2020) - [j3]Tongwen Li
A Validation Approach Considering the Uneven Distribution of Ground Stations for Satellite-Based PM2.5 Estimation. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 1312-1321 (2020) - [c7]Yuan Wang, Qiangqiang Yuan, Ruixue Xiao, Tongwen Li
Recovery of the Carbon Monoxide Product from S5P-TROPOMI by Fusing Multiple Datasets: A Case Study in Hubei Province, China. IGARSS 2020: 5529-5532
2010 – 2019
- 2019
- [j2]Qiangqiang Yuan, Shuwen Li, Linwei Yue, Tongwen Li
Monitoring the Variation of Vegetation Water Content with Machine Learning Methods: Point-Surface Fusion of MODIS Products and GNSS-IR Observations. Remote. Sens. 11(12): 1440 (2019) - [c6]Jiwen Wang, Qiangqiang Yuan, Tongwen Li
Estimating Snow-Depth by Fusing Satellite and Station Observations: A Deep Learning Approach. IGARSS 2019: 4109-4112 - [c5]Hongzhang Xu
Estimating Surface Soil Moisture from Satellite Observations Using Machine Learning Trained on In Situ Measurements in the Continental U.S. IGARSS 2019: 6166-6169 - [c4]Shuwen Li, Qiangqiang Yuan, Linwei Yue, Tongwen Li
Downscaling GNSS-R Based Vegetation Water Content Product Using Random Forest Model. IGARSS 2019: 6720-6723 - [c3]Yuan Wang, Qiangqiang Yuan, Haotian Wang, Tongwen Li
Validation of MODIS 1-Km MAIAC Aerosol Products with AERONET in China During 2008-2016. IGARSS 2019: 7610-7613 - 2018
- [j1]Hongzhang Xu
Quality Improvement of Satellite Soil Moisture Products by Fusing with In-Situ Measurements and GNSS-R Estimates in the Western Continental U.S. Remote. Sens. 10(9): 1351 (2018) - [c2]Tongwen Li
Deep Learning for Ground-Level PM2.5 Prediction from Satellite Remote Sensing Data. IGARSS 2018: 7581-7584 - 2016
- [c1]Tongwen Li
Mapping PM2.5 distribution in China by fusing station measurements and satellite observation. IGARSS 2016: 5761-5764
Coauthor Index
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