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Global land cover classifications at 8 km spatial resolution: The use of training data derived from Landsat imagery in decision tree classifiers

This paper reports a study which aims to (i) develop methodologies for global land cover classifications that are objective, reproducible and feasible to implement as new satellite data become available in the future and (ii) provide a global land cover classification product based on the National Aeronautics and Space Administration/National Oceanic and Atmospheric Administration Pathfinder Land (PAL) data that can be used in global change research. The spatial resolution for the land cover classification is 8 km, intermediate between our previously published coarse one degree by one degree spatial resolution and the 1 km global land cover product being developed under the auspices of the International Geosphere Biosphere Program. We first derive a global network of training sites from Landsat imagery, using 156 Landsat scenes mostly from the Multispectral Scanner System, to identify over 9000 pixels in the PAL data where we have high confidence that the labelled cover type occurs. We then use the traini...