| Improved daily SMAP satellite soil moisture prediction over China using deep learning model with transfer learning Q Li, Z Wang, W Shangguan, L Li, Y Yao, F Yu Journal of Hydrology 600, 126698, 2021 | 90 | 2021 |
| An attention-aware LSTM model for soil moisture and soil temperature prediction Q Li, Y Zhu, W Shangguan, X Wang, L Li, F Yu Geoderma 409, 115651, 2022 | 63 | 2022 |
| Assessment of agricultural drought using soil water deficit index based on ERA5-land soil moisture data in four southern provinces of China R Zhang, L Li, Y Zhang, F Huang, J Li, W Liu, T Mao, Z Xiong, ... Agriculture 11 (5), 411, 2021 | 36 | 2021 |
| A 1 km daily soil moisture dataset over China using in situ measurement and machine learning Q Li, G Shi, W Shangguan, V Nourani, J Li, L Li, F Huang, Y Zhang, ... Earth System Science Data 14 (12), 5267-5286, 2022 | 35 | 2022 |
| Improving soil moisture prediction using a novel encoder-decoder model with residual learning Q Li, Z Li, W Shangguan, X Wang, L Li, F Yu Computers and Electronics in Agriculture 195, 106816, 2022 | 23 | 2022 |
| A causal inference model based on random forests to identify the effect of soil moisture on precipitation L Li, W Shangguan, Y Deng, J Mao, JJ Pan, N Wei, H Yuan, S Zhang, ... Journal of Hydrometeorology 21 (5), 1115-1131, 2020 | 22 | 2020 |
| Using data‐driven methods to explore the predictability of surface soil moisture with FLUXNET site data J Pan, W Shangguan, L Li, H Yuan, S Zhang, X Lu, N Wei, Y Dai Hydrological processes 33 (23), 2978-2996, 2019 | 19 | 2019 |
| A spatial downscaling method for remote sensing soil moisture based on random forest considering soil moisture memory and mass conservation T Mao, W Shangguan, Q Li, L Li, Y Zhang, F Huang, J Li, W Liu, R Zhang Remote Sensing 14 (16), 3858, 2022 | 15 | 2022 |
| Assessment of agricultural drought based on reanalysis soil moisture in Southern China W Shangguan, R Zhang, L Li, S Zhang, Y Zhang, F Huang, J Li, W Liu Land 11 (4), 502, 2022 | 12 | 2022 |
| Multistep forecasting of soil moisture using spatiotemporal deep encoder–decoder networks L Li, Y Dai, W Shangguan, N Wei, Z Wei, S Gupta Journal of Hydrometeorology 23 (3), 337-350, 2022 | 9 | 2022 |
| Causality-structured deep learning for soil moisture predictions L Li, Y Dai, W Shangguan, Z Wei, N Wei, Q Li Journal of Hydrometeorology 23 (8), 1315-1331, 2022 | 6 | 2022 |
| Beyond prediction: An integrated post-hoc approach to interpret complex model in hydrometeorology F Huang, W Shangguan, Q Li, L Li, Y Zhang Environmental Modelling & Software 167, 105762, 2023 | 5 | 2023 |
| A 1 km global carbon flux dataset using in situ measurements and deep learning W Shangguan, Z Xiong, V Nourani, Q Li, X Lu, L Li, F Huang, Y Zhang, ... Forests 14 (5), 913, 2023 | 4 | 2023 |
| Towards interpreting machine learning models for predicting soil moisture droughts F Huang, Y Zhang, Y Zhang, V Nourani, Q Li, L Li, W Shangguan Environmental Research Letters 18 (7), 074002, 2023 | 3 | 2023 |
| Interpreting Conv-LSTM for spatio-temporal soil moisture prediction in China F Huang, Y Zhang, Y Zhang, W Shangguan, Q Li, L Li, S Jiang Agriculture 13 (5), 971, 2023 | 3 | 2023 |
| LandBench 1.0: A benchmark dataset and evaluation metrics for data-driven land surface variables prediction Q Li, C Zhang, W Shangguan, Z Wei, H Yuan, J Zhu, X Li, L Li, G Li, P Liu, ... Expert Systems with Applications 243, 122917, 2024 | 1 | 2024 |
| A novel local-global dependency deep learning model for soil mapping Q Li, C Zhang, W Shangguan, L Li, Y Dai Geoderma 438, 116649, 2023 | 1 | 2023 |
| Plant drought tolerance trait is the key parameter in improving the modeling of terrestrial transpiration in arid and semi-arid regions X Liu, X Lu, S Zhang, Z Wei, N Wei, S Zhang, H Yuan, W Shangguan, ... Atmospheric and Oceanic Science Letters 15 (1), 100139, 2022 | 1 | 2022 |
| Impact of Reservoirs on Local Precipitation‐Temperature Coupling Relationships J Li, S Zhang, O Obulkasim, X Lu, Z Wei, H Yuan, L Li, J Zeng, D Yang, ... Geophysical Research Letters 50 (14), e2023GL103453, 2023 | | 2023 |
| Real-Time Forecast of SMAP L3 Soil Moisture Using Spatial–Temporal Deep Learning Model with Data Integration Y Zhang, F Huang, L Li, Q Li, Y Zhang, W Shangguan Remote Sensing 15 (2), 366, 2023 | | 2023 |
Wei ShangguanSun Yat-sen UniversityVerified email at mail.sysu.edu.cn
