Global continuous elds of vegetation characteristics : a linear mixture model applied to multi - year 8 km AVHRR data

As an alternative to the traditional approach of using predeŽ ned classiŽ cation schemes with discrete numbers of cover types to describe the geographic distribution of vegetation over the Earth’s land surface, we apply a linear mixture model to derive global continuous Ž elds of percentage woody vegetation, herbaceous vegetation and bare ground from 8 km Advanced Very High Resolution Radiometer (AVHRR) PathŽ nder Land data. Linear discriminants for input into the mixture model are derived from 30 metrics representing the annual phenological cycle, using training data derived from a global network of scenes acquired by Landsat. We test the stability and robustness of the method by assessing the consistency of results derived independently for each year in the 1982 to 1994 AVHRR data set. For those forested locations where land cover variability would not be expected, the percentage woody estimates displayed standard deviations over the 12 years of less than 10%. Problems with the method occur in high latitudes where snow cover in some years and not others produces inconsistencies in the continuous Ž elds. Overall, the results suggest that the method produces fairly consistent results despite apparent problems with artifacts in the multi-year AVHRR data set due to calibration problems, aerosols and other atmospheric e€ ects, bidirectional e€ ects, changes in equatorial crossing time, and other factors. Comparison of continuous Ž elds with other land cover data sets derived from remote sensing suggests 69% to 84% agreement in the per cent woody Ž eld, with the highest agreement when per cent woody is averaged over the 12 years. In comparison with regional data sets for the US and Bolivia, the method overestimates per cent woody vegetation for grassland and sparsely wooded locations. We conclude that the method, with possible reŽ nements and more sophisticatedmethods to include multiple endmembers, improved estimates of endmember values and nonlinear responsesof vegetation to proportionalcover, can potentially be used to indicate changes in land cover characteristics over time using multi-year data sets as inputs when perfect calibration and consistency between years cannot be assumed.