What is measured by the RMSE value in GIS?

The RMSE value, or Root Mean Square Error, is a statistical measure used to assess the accuracy of a set of predictions or measurements in GIS. It quantifies the difference between values predicted by a model or interpolated from data and the actual observed values. Specifically, RMSE measures the square root of the average of the squares of these errors, providing a single number that summarizes the magnitude of the errors across the dataset.

In GIS applications, RMSE is particularly useful when comparing predicted values in spatial analyses, such as when evaluating the accuracy of spatial models or when assessing the quality of interpolation techniques. A lower RMSE value indicates a small deviation between predicted and actual values, suggesting a higher degree of accuracy in the data or the model being analyzed. This makes RMSE a critical metric for understanding how effectively a GIS model mirrors real-world conditions.