Hierarchical clustering for spatial data, which requires clustering
results not only homogeneous in non-geographical features among samples but
also geographically close to each other within a cluster. It modified typically
used hierarchical agglomerative clustering algorithms for introducing the spatial
homogeneity, by considering geographical locations as vertices and converting
spatial adjacency into whether a shared edge exists between a pair of vertices
(Tzeng & Hsu, 2022)