Name
Abstract | ||
|---|---|---|
Soil can be used as a damage indicator of landslides and flooding, which expose soil from vegetation canopy. It can also be used as an indirect indicator of illegal tunnel digging activity. This letter presents a sparsity-based approach to soil detection using multispectral satellite images, where both original and synthetic bands have been used. Spatial and spectral information has then been jointly used in soil detection. Extensive experiments clearly demonstrated the feasibility of our approach. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LGRS.2019.2911923 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Soil,Satellites,Terrain factors,Dictionaries,Training,Spatial resolution,Geology | Computer vision,Remote sensing,Artificial intelligence,Mathematics | Journal |
Volume | Issue | ISSN |
16 | 12 | 1545-598X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Minh Dao | 1 | 121 | 11.14 |
| Chiman Kwan | 2 | 440 | 71.64 |
| Sergio Bernabe | 3 | 135 | 12.45 |
| Antonio Plaza | 4 | 83 | 17.35 |
| Krzysztof Koperski | 5 | 10 | 1.27 |