A comparison of the IGBP DISCover and University of Maryland 1km global land cover products

Two global 1 km land cover data sets derived from 1992-1993 Advanced Very H igh Resolution Radiometer (AVHRR) data are currently available, the Interna tional Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) DISCover and the University of Maryland (UMd) 1 km land cover maps. This p aper makes a preliminary comparison of the methodologies and results of the two products. The DISCover methodology employed an unsupervised clustering classification scheme on a per-continent basis using 12 monthly maximum ND VI composites as inputs. The UMd approach employed a supervised classificat ion tree method in which temporal metrics derived from all AVHRR bands and the NDVI were used to predict class membership across the entire globe. The DISCover map uses the IGBP classification scheme, while the UMd map employ s a modified IGBP scheme minus the classes of permanent wetlands, cropland/ natural vegetation mosaic and ice and snow. Global area totals of aggregate d vegetation types are very similar and have a per-pixel agreement of 74%. For tall versus short/no vegetation, the per-pixel agreement is 84%. For br oad vegetation types, core areas map similarly, while transition zones arou nd core areas differ significantly. This results in high regional variabili ty between the maps. Individual class agreement between the two 1 km maps i s 49%. Comparison of the maps at a nominal 0.5 degrees resolution with two global ground-based maps shows an improvement of thematic concurrency of 46 % when viewing average class agreement. The absence of the cropland mosaic class creates a difficulty in comparing the maps, due to its significant ex tent in the DISCover map. The DISCover map, in general, has more forest, wh ile the UMd map has considerably more area in the intermediate tree cover c lasses of woody savanna/woodland and savanna/wooded grassland.