Name
Title | ||
|---|---|---|
Estimation of total phosphorus concentration using a water classification method in inland water. |
Abstract | ||
|---|---|---|
•A optical classification method was constructed to classify water into phytoplankton or non-algae particles dominated water.•The new optical classification method can effectively improve the precision of TP inversion.•Data regression analysis and fitting (DRF) and machine learning methods were combined to build TP inversion models.•The performance of the new classification and inversion algorithms on Sentinel-3 data was evaluated firstly. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.jag.2018.05.007 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | Field | DocType |
Total phosphorus,Remote sensing,Classification,Inversion models,Sentinel-3 | Inversion (meteorology),Regression analysis,Remote sensing,Back propagation neural network,Total phosphorus,Random forest,Geography,Water quality,Eutrophication | Journal |
Volume | ISSN | Citations |
71 | 0303-2434 | 0 |
PageRank | References | Authors |
0.34 | 6 | 9 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chenggong Du | 1 | 1 | 1.04 |
| Qiao Wang | 2 | 97 | 21.94 |
| Yunmei Li | 3 | 39 | 8.09 |
| Heng Lyu | 4 | 20 | 8.39 |
| Li Zhu | 5 | 2 | 1.50 |
| Zhubin Zheng | 6 | 2 | 1.07 |
| Shuang Wen | 7 | 0 | 0.34 |
| ge liu | 8 | 34 | 4.76 |
| Yulong Guo | 9 | 21 | 3.01 |