Improved representation of Arctic tundra landcover in global data sets

Landsurface cover and hydrology is crucial information in modelling attempts on local to global scales. Arctic tundra regions are distinct in their plant communities and composition from Boreal or temperate regions and often underserved by globally available landcover data sets. Recent advances in mapping landcover units in Arctic tundra regions have allowed researchers to study and quantify landscape composition and wetness gradients on different scales. The Circumarctic Landcover Units (CALU) data set provides landcover information based on Sentinel – 1 and Sentinel – 2 at 10m resolution (ESA CCI+ Permafrost landcover). It also provides tundra specific landcover units not present in conventional data sets which improves the overall representation of tundra landscapes.

Global landcover data sets, such as the CCI Landcover, are available at coarser scales. To harness the potential of the CALU data set for usage in global applications, it is necessary to aggregate the 10m resolution to a coarser scale (300m in this case). In addition, the CCI Landcover includes different classes compared to the CALU data sets, which requires additional harmonization.

Here we present a harmonization effort between CALU and ESA CCI Landcover data sets. The result is a global landcover data set at 300m scale, with Arctic regions based on the dedicated CALU data. As a second step, novel classes in addition to the existing CCI Landcover classes are being suggested to improve representation of tundra landscapes in the harmonized data set. This harmonized landcover data set will allow for a more realistic representation of the Arctic landcover in land models which has the potential to improve the model estimate of the land carbon sink. Applications of the harmonized data set will be discussed.