Lei Xu
Orcid: 0000-0002-6454-2963Affiliations:
- Wuhan University, State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan, China
According to our database1,
Lei Xu
authored at least 13 papers
between 2019 and 2024.
Collaborative distances:
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Bibliography
2024
Flood Inundation Probability Estimation by Integrating Physical and Social Sensing Data: Case Study of 2021 Heavy Rainfall in Henan, China.
Remote. Sens., August, 2024
Incorporating spatial autocorrelation into deformable ConvLSTM for hourly precipitation forecasting.
Comput. Geosci., February, 2024
Geographically Weighted Convolutional Long Short-Term Memory Neural Networks: A Geospatial Deep Learning Model for Monthly NDVI Prediction.
IEEE Trans. Geosci. Remote. Sens., 2024
Monthly NDVI Prediction Using Spatial Autocorrelation and Nonlocal Attention Networks.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024
2023
Hybrid Deep Learning and S2S Model for Improved Sub-Seasonal Surface and Root-Zone Soil Moisture Forecasting.
Remote. Sens., July, 2023
Applicability Analysis and Ensemble Application of BERT with TF-IDF, TextRank, MMR, and LDA for Topic Classification Based on Flood-Related VGI.
ISPRS Int. J. Geo Inf., June, 2023
Rice Yield Prediction in Hubei Province Based on Deep Learning and the Effect of Spatial Heterogeneity.
Remote. Sens., March, 2023
Monthly Ocean Primary Productivity Forecasting by Joint Use of Seasonal Climate Prediction and Temporal Memory.
Remote. Sens., March, 2023
Exploring the Relationship between the Eco-Environmental Quality and Urbanization by Utilizing Sentinel and Landsat Data: A Case Study of the Yellow River Basin.
Remote. Sens., February, 2023
Spatiotemporal Dynamics of Remote-Sensed Forel-Ule Index for Inland Waters Across China During the COVID-19 Pandemic.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023
2022
Detecting Spatially Non-Stationary between Vegetation and Related Factors in the Yellow River Basin from 1986 to 2021 Using Multiscale Geographically Weighted Regression Based on Landsat.
Remote. Sens., December, 2022
2020
Using Multi-Temporal MODIS NDVI Data to Monitor Tea Status and Forecast Yield: A Case Study at Tanuyen, Laichau, Vietnam.
Remote. Sens., 2020
2019
A spatiotemporal deep learning model for sea surface temperature field prediction using time-series satellite data.
Environ. Model. Softw., 2019