Strugnell, NC, Lucht, W (2001). "An algorithm to infer continental-scale albedo from AVHRR data, land cover class, and field observations of typical BRDFs". JOURNAL OF CLIMATE, 14(7), 1360-1376.
A method to derive bottom-of-atmosphere land surface albedos from Advanced Very High Resolution Radiometer (AVHRR) satellite measurements is presented. The algorithm described uses kernel-based bidirectional reflectance distribution function (BRDF) models of land cover but, in contrast to other kernel-based albedo retrievals, assumes a priori knowledge of underlying surface BRDFs, based on a land cover classification and typical field-measured BRDFs for each class in the land cover classification. The BRDF of each land cover is scaled using AVHRR reflectance measurements to take into account within-class variations of albedo, and the resultant scaled BRDF is integrated to retrieve an albedo. An albedo dataset for North America is produced with this scheme from February and July 1995 monthly maximum normalized difference vegetation index value composite images. Spectral-to-broadband albedo conversion is achieved by using spectral albedos to scale a laboratory-measures vegetation spectral reflectance curve. Both white-sky (bihemispherical reflectance) and black-sky (directional-hemispherical reflectance) albedos are produced. The methodology presented is general and can be used with historical AVHRR. In addition it will be used with data from the moderate-resolution imaging spectrometer sensor aboard the Terra satellite as an ancillary technique to produce global, monthly albedo datasets for use in climatic and atmospheric research.