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VIIRS reference dataset


The Visible Infrared Imaging Radiometer Suite (VIIRS) Surface Type (ST) validation database is based on a stratified random sample of 500 5x5 km blocks globally. The strata from which these sites have been sampled were derived from an intersection of a modified Köppen climate classification with a human population density layer (Olofsson et al., 2012). The allocation of samples within each stratum was targeted towards heterogeneous and complex land cover types that are more difficult to map. At each sample block a very-high spatial resolution (<2-m) image was obtained through partnerships with DigitalGlobe™, Google, and the USGS. These images are targeted towards recent, peak growing season conditions and minimal cloud cover.
Following pre-processing and orthorectification of these very-high spatial resolution data, a 1-km sinusoidal grid is overlain on images. This grid is common both to the Collection 4 MODIS Land Cover (MOD12Q1) product and the VIIRS ST product currently in development. At each 1-km grid cell within each sample block, manual interpretation was performed to identify the correct class according to the International Geosphere-Biosphere Programme (IGBP) legend for the year 2013. Ancillary information from high-resolution historical imagery from GoogleEarth™ and aggregated 12-year 500-m resolution MODIS time series were used to improve the interpretations. The first version of the VIIRS ST map will be released sometime in the year 2013 and this dataset will be used to immediately assess the accuracy of this product. In the future, these images will be classified into an object-oriented FAO-LCCS compatible legend. These classifications will allow for a more robust accuracy assessment and comparison across map products and legends.

Olofsson, P., Stehman, S. V., Woodcock, C. E., Sulla-Menashe, D., Sibley, A. M., Newell, J. D., Friedl, M. A., & Herold, M. (2012). A global land-cover validation data set, part I: fundamental design principles. International Journal of Remote Sensing, 33 (18), 5768-5788.

Stehman, S. V., Olofsson, P., Woodcock, C. E., Herold, M., & Friedl, M. A. (2012). A global land-cover validation data set, II: augmenting a stratified sampling design to estimate accuracy by region and land-cover class. International Journal of Remote Sensing, 33 (22), 6975-6993.

Access to the data

We provide an access to a subset of the current version of the dataset. A stratified (by IGBP class legend) random selection of 70% of the samples has been done.

Spatial distribution of the randomly selected sample plots of the VIIRS dataset available on the the portal

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