As I mentioned in a previous post, last September I participated to the Recent Advances in Quantitative Remotes Sensing Symposium. I presented several posters there. One of them was about the assessment of the classification accuracy of Venus and Sentinel-2 sensors for land cover map production.
The idea here is to find a good balance between image synthesis (low accuracy) and physically sound simulation (need for ancillary data and computational complexity). The choice made here is to use a real time series of Formosat-2 images (only 4 spectral bands) in order to simulated Venus and Sentinel-2 time series with the same temporal sampling but with more than 10 spectral bands.
The Formosat-2 time series is used in order to:
- Estimate the LAI (leaf area index) for each pixel
- Give a spatial distribution using a land-cover map
The poster presented at RAQRS 2010 is here.
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