TABLE 2 Input Parameters for 38 Trial Cluster Analyses on Land-Use Distress,,,,,,
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Case,Distance,Linage,Standardization,No. of clusters,Comments,
 1,Euclidean,Single,None,20,Produced single large clusters of over 300 districts with no cluster larger than 5 districts; chaining effect took place,
 2,Euclidean,Single,None,15,,
 3,Euclidean,Single,None,25,,
 4,Euclidean,Average,None,20,Smaller main clusters and larger minor clusters but not much diversity in residential scenarios,
 5,Euclidean,Average,None,30,,
 6,Euclidean,Average,None,18,,
 7,Euclidean,Centroid,None,20,Relatively poor distribution of cluster sizes and poor diversity in residential scenarios,
 8,Euclidean,Centroid,None,30,,
 9,Euclidean,Complete,None,20,Somewhat more diversity in residential scenarios,
10,Euclidean,Complete,None,17,,
11,Euclidean,McQuitty,None,20,Little diversity in residential scenarios,
12,Euclidean,Median,None,20,"Large mega-cluster, like with single linkage",
13,Euclidean,Ward,None,20,Relatively equal cluster sizes; good diversity,
14,Pearson,Average,None,20,Pearson and Squared Pearson linkages created mega-clusters; Manhattan seemed almost as good as Euclidean; Squared Euclidean was nearly identical to Euclidean
15,Manhattan,Average,None,20,
16,Sq. Euclidean,Average,None,20,
17,Sq. Pearson,Average,None,20,
18,Pearson,Complete,None,20,Pearson and Squared Pearson linkages created identical mega-clusters; Manhattan created slightly more diversity than Euclidean; Squared Euclidean identical with Euclidean
19,Manhattan,Complete,None,20,
20,Sq. Euclidean,Complete,None,20,
21,Sq. Pearson,Complete,None,20,
22,Pearson,McQuitty,None,20,Changing the distance measure has similar effects as with average and complete linkages
23,Manhattan,McQuitty,None,20,
24,Sq. Euclidean,McQuitty,None,20,
25,Sq. Pearson,McQuitty,None,20,
26,Pearson,Ward,None,20,Pearson and Squared Pearson produced slightly less diversity in residential and agricultural scenarios; Squared Euclidean lumped agricultural scenarios together; Manhattan similar to Euclidean
27,Manhattan,Ward,None,20,
28,Sq. Euclidean,Ward,None,20,
29,Sq. Pearson,Ward,None,20,
30,Sq. Euclidian,Ward,Z-scores,20,Similar diversity to case without standardization (case 28) but oddly distributed variables better represented
31,Euclidean,Complete,Z-scores,20,Much poorer diversity than in case 9
32,Euclidean,Average,Z-scores,20,Forms mega-cluster; worse than case 4
33,Euclidean,Ward,Z-scores,20,More diverse in some areas than with case 13
34,Sq. Euclidean,Ward,Z-scores,30,Improved diversity over case 30
35,Euclidean,Ward,Z-scores,30,More diverse than case 33
36,Euclidean,Ward,None,30,"Similar diversity to case 35 but oddly distributed variables like R3, R4 not as well represented"
37,Euclidean,Ward,Scaled percentages,30,Oddly distributed variables well-represented but not enough of an improvement in variable bounds
38,Sq. Euclidean,Ward,Z-scores,35,Number of clusters increase to 35 to separate a few odd groupings