Development of the Statistical Errors Raster Toolbox with Six Automated Models for Raster Analysis in GIS Environments

Abstract

The Statistical Errors Raster Toolbox includes models of the most popular error metrics in the interdisciplinary literature, namely, root mean square error (RMSE), normalized root mean square error (NRMSE), mean bias error (MBE), normalized mean bias error (NMBE), mean absolute error (MAE) and normalized mean absolute error (NMAE), for computing the areal errors of any raster file in .tiff format as compared with a reference raster file. The models are applicable to any size of raster files, no matter if no-data pixels are included. The only prerequisites are that the two raster files share the same units, cell size, and projection system. The novelty lies in the fact that, to date, there is no such application in ArcGIS Pro 3/ArcMap 10.8. Therefore, users who work with raster files require external software, plus the relevant expertise. An application on the reference evapotranspiration (ETo) of Peloponnese peninsula (Greece) is presented. MODIS ET products and ETo raster files for empirical methods are employed. The results of the models (for 20,440 valid values) are compared to the results of external software (for 1000 random points). Considering that the different sample sizes can lead to different accuracies and the inhomogeneity of the area, it is obvious that the results are almost identical.

Keywords

• ArcGIS Pro
• ArcMap
• statistical errors
• RMSE
• MBE
• MAE