What is the primary purpose of 'data normalization' in GIS?

Data normalization in GIS primarily involves adjusting values in a dataset to a common scale. This process is essential because it allows for fair comparisons between data points that may be on different scales or units. By normalizing data, you can maintain the relative differences among the values while ensuring that they fit within a consistent framework. This is particularly important when integrating datasets from different sources or when conducting analyses that involve multiple variables that may otherwise skew results due to varying ranges.

For instance, if one dataset includes measurements in centimeters and another in meters, normalizing these values allows analysts to compare them directly without bias introduced by their different scales. Consequently, normalization plays a crucial role in ensuring the accuracy and reliability of spatial analyses, which is fundamental to making informed decisions based on geographic data.