A geostatistical method for automated seafloor classification is devel
oped and applied to bathymetric data for a 150 x 100 km area at 26 deg
rees N on the western flank of the Mid-Atlantic Ridge. The objective o
f seafloor classification is to characterize seafloor properties quant
itatively, and to use such spatial characteristics to distinguish roug
hness provinces, and geologic and morphologic units automatically. The
method presented here is based on the calculation of directional vari
ograms as spatial structure functions. Parameters determined from filt
ered variogram functions are used to compose Feature vectors, which ar
e shown to be characteristic of morphologic prototypes and surface rou
ghness types, and therefore facilitate a classification. Discriminatio
n Criteria include spacing and strike of abyssal hill terrain, smoothn
ess resulting from sediment cover, and parameters related to complexit
y and morphological significance of abyssal hills and their slopes. Co
mplications of automating the process concern robustness of parameter
estimation, optimal window size, and subselection of data. By moving t
he classification operation through the study area and color-coding pr
operty classes, seafloor classification maps are obtained. The concept
s of characteristic parameters, feature vectors and discrimination cri
teria are illustrated in applications to bathymetric data from the wes
tern flank of the Mid-Atlantic Ridge. Resultant classification maps ar
e presented, with classes including roughness provinces and morphologi
c units.