Name
Title | ||
|---|---|---|
Deep learning empowers the Google Earth Engine for automated water extraction in the Lake Baikal Basin |
Abstract | ||
|---|---|---|
•Deep learning empowered GEE automatic water segmentation in the Lake Baikal Basin.•Rapid access to highly accurate spatiotemporal water-body distribution data.•QA bands help solve the challenge of deep learning needing numerous training labels. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.jag.2022.102928 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | DocType | Volume |
Water extraction,Deep learning,Noise correction,Quality assessment bands,Google Earth Engine,Lake Baikal | Journal | 112 |
ISSN | Citations | PageRank |
1569-8432 | 0 | 0.34 |
References | Authors | |
1 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kai Li | 1 | 2 | 4.49 |
| Juanle Wang | 2 | 16 | 11.47 |
| Wenjing Cheng | 3 | 0 | 0.34 |
| Yi Wang | 4 | 1520 | 135.81 |
| Yezhi Zhou | 5 | 0 | 0.34 |
| Ochir Altansukh | 6 | 0 | 0.34 |