Name
Abstract | ||
|---|---|---|
Flooding is the world's most costly type of natural disaster in terms of both economic losses and human causalities. A first and essential procedure toward flood monitoring is based on identifying the area most vulnerable to flooding, which gives authorities relevant regions to focus. In this letter, we propose several methods to perform flooding identification in high-resolution remote sensing im... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LGRS.2018.2845549 | IEEE Geoscience and Remote Sensing Letters |
Keywords | DocType | Volume |
Remote sensing,Satellites,Task analysis,Image resolution,Support vector machines,Training,Monitoring | Journal | 15 |
Issue | ISSN | Citations |
9 | 1545-598X | 4 |
PageRank | References | Authors |
0.47 | 5 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Keiller Nogueira | 1 | 203 | 9.23 |
| Samuel G. Fadel | 2 | 94 | 5.34 |
| Ícaro C. Dourado | 3 | 5 | 2.54 |
| Rafael de Oliveira Werneck | 4 | 20 | 3.58 |
| Javier A. V. Muñoz | 5 | 5 | 2.20 |
| Otávio A. B. Penatti | 6 | 398 | 18.12 |
| Rodrigo Tripodi Calumby | 7 | 61 | 7.75 |
| Lin Tzy Li | 8 | 67 | 9.30 |
| Jefersson Alex dos Santos | 9 | 350 | 28.43 |
| Ricardo S. Torres | 10 | 14 | 2.19 |