Name
Title | ||
|---|---|---|
Atmospheric scene classification using CALIPSO spaceborne lidar measurements in the Middle East and North Africa (MENA), and India. |
Abstract | ||
|---|---|---|
•The high performance of the CALIPSO satellite LiDAR data was confirmed for atmospheric scene classification.•Particle density as a proposed feature has had great influence on the classification results.•The consistency of the results of the automatic training samples selection was demonstrated.•Support vector machine successfully classified the cloud and aerosol in 4 different datasets. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.jag.2018.07.017 | International Journal of Applied Earth Observation and Geoinformation |
Keywords | Field | DocType |
Aerosol,CALIOP,SVM,MENA,Classification,VFM | Pathfinder,Satellite,Brightness temperature,Feature selection,Support vector machine,Remote sensing,Lidar,Ground truth,Geography,Statistical hypothesis testing | Journal |
Volume | ISSN | Citations |
73 | 0303-2434 | 0 |
PageRank | References | Authors |
0.34 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Foad Brakhasi | 1 | 0 | 0.34 |
| Ali Akbar Matkan | 2 | 2 | 1.43 |
| Mohammad Hajeb | 3 | 0 | 0.34 |
| Kourosh Khoshelham | 4 | 65 | 12.67 |