A Modified Inhomogeneity Measure in Spatial Distribution

In this paper, we investigated the traditional inhomogeneity measure and proposed a modified inhomogeneity measure. The traditional inhomogeneity measure adopted absolute value as norm. However, it was not accurate enough when used in sparse spatial distribution. The modified inhomogeneity measure adopted Euclidean distance instead of absolute value. An example was taken to compare the traditional inhomogeneity measure and the modified inhomogeneity measure, and verified the modified inhomogeneity measure was more accurate in sparse spatial distribution. Simulation compared the inhomogeneity measured by different method, and the results showed that the modified inhomogeneity measure better fits human perception.