Watershed transformation is a powerful image segmentation tool recently dev
eloped in mathematical morphology. In order to segment images initially ove
rsegmented by watershed transformation, two approaches are considered: one
is the thresholding of the gradient image proposed by us which is capable o
f keeping more salient image contours; the other is the well known centroid
linkage region growing algorithm which merges regions with certain statist
ical similarities. By choosing suitable thresholds in the two approaches, h
ierarchical image segmentation algorithms can be constructed. A Ratio of Av
erages (ROA) edge detector is proposed to replace the morphological edge de
tectors prior to watershed transformation when applied to Synthetic Apertur
e Radar (SAR) images. Applications to SAR agricultural image segmentation w
ith these hierarchical segmentation algorithms are presented. It is demonst
rated that the algorithms are efficient in the segmentation of the SAR imag
es and appropriate for land use applications when the land cover is made up
of individual plots.