For many applications satellite time series with both a high spatial and a high temporal resolution are required. However, most satellites provide global coverage of the Earth either with a high spatial resolution or with a high temporal resolution, but not both.
Satellite sensors with a high spatial resolution have a rather low revisit time. Examples are Landsat (30 m, 16 days) and Sentinel-2 (10 or 20 m, 10 days). With two identical satellites Sentinel-2 increases the revisit time to 5 days. On the other hand, satellite sensors with a high revisit time have a rather low spatial resolution. Examples are MODIS (1-2 days, 250/500 m) and Sentinel-3 (1-2 days, 300 m). A major step forward would be the development of a robust methodology to fuse these different data sources, providing synthetic images with both a high spatial resolution and a high revisit time. One of the major factors to take into account is the fact that the nominal revisit time mostly will not be achieved because of cloud cover.
- Develop a methodology to fuse satellite images with different spatial and temporal resolutions
- Quantify the improvement in comparison to the single images
- Determine the influence of cloud cover on the developed methodology
- Zhu et al. (2018), Spatiotemporal fusion of multisource remote sensing data. Remote Sensing 10(4), no. 527.
- GRS-20306 (Remote Sensing)
Theme(s): Sensing & measuring