Assessment of a Spatiotemporal Deep Learning Approach for Soil Moisture Prediction and Filling the Gaps in Between Soil Moisture Observations

Assessment of a Spatiotemporal Deep Learning Approach for Soil Moisture Prediction and Filling the Gaps in Between Soil Moisture Observations

Soil moisture (SM) plays a significant role in determining the probability of flooding in a given area. Currently, SM is most commonly modeled using physically-based numerical hydrologic models. Modeling the natural processes that take place in the soil is difficult and requires assumptions. Besides...

Full description

Bibliographic Details
Main Authors: Mohamed ElSaadani, Emad Habib, Ahmed M. Abdelhameed, Magdy Bayoumi
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Artificial Intelligence
Subjects:
deep learning
soil moisture
LSTM
convolutional neural network
Louisiana (United States)
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2021.636234/full

Internet

https://www.frontiersin.org/articles/10.3389/frai.2021.636234/full

Similar Items