The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Timeline
X Demographics
Mendeley readers
| Title |
Assessment of a Spatiotemporal Deep Learning Approach for Soil Moisture Prediction and Filling the Gaps in Between Soil Moisture Observations
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, March 2021
|
| DOI | 10.3389/frai.2021.636234 |
| Pubmed ID | |
| Authors |
Mohamed ElSaadani, Emad Habib, Ahmed M. Abdelhameed, Magdy Bayoumi |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Saudi Arabia | 1 | 50% |
| Switzerland | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 59 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 15% |
| Student > Master | 7 | 12% |
| Researcher | 7 | 12% |
| Student > Doctoral Student | 5 | 8% |
| Lecturer | 4 | 7% |
| Other | 6 | 10% |
| Unknown | 21 | 36% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 13 | 22% |
| Environmental Science | 7 | 12% |
| Earth and Planetary Sciences | 5 | 8% |
| Computer Science | 4 | 7% |
| Unspecified | 3 | 5% |
| Other | 3 | 5% |
| Unknown | 24 | 41% |