Sea Ice Classification: What Can We Learn From Airborne Data?
When asked what is important for sea ice classification, one of the most mentioned items is the large spatial coverage that can only be realized with satellites acquiring data in wide-swath or scanning image modes. Nevertheless, the performance of any sea ice classification algorithm is also influen...
| Main Author: | |
|---|---|
| Format: | Conference Object |
| Language: | unknown |
| Published: |
2017
|
| Subjects: | |
| Online Access: | https://epic.awi.de/id/eprint/45982/ https://hdl.handle.net/10013/epic.93cb0d2a-cbf8-447c-bcf4-f6e1303cb03e |
| Summary: | When asked what is important for sea ice classification, one of the most mentioned items is the large spatial coverage that can only be realized with satellites acquiring data in wide-swath or scanning image modes. Nevertheless, the performance of any sea ice classification algorithm is also influenced by the spatial resolution of the imaging instrument. The more details are visible, the easier it is for human analysts to separate different ice types. Hence, airborne SAR data, especially in conjunction with optical and/or thermal images, are extremely valuable for investigating the potential for sea ice classification with radar and to investigate the effects of a coarser spatial resolution typical for wide-swath satellite imagery. In this context, also the high-resolution imaging modes of modern satellite instruments have to be mentioned, which offer similar possibilities. In the presentation, examples from airborne radar and optical/thermal scanners are discussed, complemented by satellite data acquisitions, addressing specifically the potential advantage of using multi-frequency radar data for sea ice classification. |
|---|