Tongwen Li
Orcid: 0000-0001-7197-3713
According to our database1,
Tongwen Li
authored at least 20 papers
between 2016 and 2022.
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Bibliography
2022
An Enhanced Geographically and Temporally Weighted Neural Network for Remote Sensing Estimation of Surface Ozone.
IEEE Trans. Geosci. Remote. Sens., 2022
A Locally Weighted Neural Network Constrained by Global Training for Remote Sensing Estimation of PM₂.₅.
IEEE Trans. Geosci. Remote. Sens., 2022
IEEE Geosci. Remote. Sens. Lett., 2022
An attention mechanism based convolutional network for satellite precipitation downscaling over China.
CoRR, 2022
Deriving gapless CO<sub>2</sub> concentrations using a geographically weighted neural network: China, 2014-2020.
Int. J. Appl. Earth Obs. Geoinformation, 2022
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, 2022
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, 2022
2021
Hourly PM<sub>2.5</sub> Concentration Monitoring With Spatiotemporal Continuity by the Fusion of Satellite and Station Observations.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021
Estimating daily full-coverage surface ozone concentration using satellite observations and a spatiotemporally embedded deep learning approach.
Int. J. Appl. Earth Obs. Geoinformation, 2021
2020
A Validation Approach Considering the Uneven Distribution of Ground Stations for Satellite-Based PM<sub>2.5</sub> Estimation.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020
Remote. Sens., 2020
Recovery of the Carbon Monoxide Product from S5P-TROPOMI by Fusing Multiple Datasets: A Case Study in Hubei Province, China.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
2019
Monitoring the Variation of Vegetation Water Content with Machine Learning Methods: Point-Surface Fusion of MODIS Products and GNSS-IR Observations.
Remote. Sens., 2019
Estimating Surface Soil Moisture from Satellite Observations Using Machine Learning Trained on In Situ Measurements in the Continental U.S.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Validation of MODIS 1-Km MAIAC Aerosol Products with AERONET in China During 2008-2016.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Estimating Snow-Depth by Fusing Satellite and Station Observations: A Deep Learning Approach.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
2018
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., 2018
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
2016
Mapping PM2.5 distribution in China by fusing station measurements and satellite observation.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016