Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data

A. A. Masrur Ahmed, Ravinesh C. Deo, Nawin Raj, Afshin Ghahramani, Qi Feng, Zhenliang Yin, Linshan Yang. Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data. Remote Sensing, 13(4):554, 2021. [doi]

@article{AhmedDRGFYY21,
  title = {Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data},
  author = {A. A. Masrur Ahmed and Ravinesh C. Deo and Nawin Raj and Afshin Ghahramani and Qi Feng and Zhenliang Yin and Linshan Yang},
  year = {2021},
  doi = {10.3390/rs13040554},
  url = {https://doi.org/10.3390/rs13040554},
  researchr = {https://researchr.org/publication/AhmedDRGFYY21},
  cites = {0},
  citedby = {0},
  journal = {Remote Sensing},
  volume = {13},
  number = {4},
  pages = {554},
}