20170508
15315100
1.0
TRUE
The image 2006 mosaic is composed of 2 multi-temporal coverages of in total roughly 3800 SPOT 4/5 and IRS-P6 LISS-III scenes. Each of the scenes provide four spectral bands. They have been geometrically corrected towards European Map Projection (LAEA-ETRS89) with 20m resolution and National Map Projection for each country with 20m resolution. For the final re-sampling cubic convolution interpolation is applied. The overall geometric accuracy is better than 10m RMSE, i.e. better than half a pixel.
High Resolution Image
Image 2006 Coverage 2
<a target='_blank' href='http://www.eea.europa.eu'>EEA</a>
Image2006Cov2
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