A new grid-cell-based method for error evaluation of vector-to-raster conversion

Error evaluation of rasterization of vector data is one of the most important research topics in the field of geographical information systems. Current methods for evaluating rasterization errors are far from perfect and need further improvement. The objective of this study is to introduce a new error evaluation method that is based on grid cells (EEM-BGC). The EEM-BGC follows four steps. First, the area of each land category inside a square is represented in a vector format. The size and location of the square are exactly the same as those of a grid cell that is to be generated by rasterization. Second, the area is treated as the attribute of the grid cell. Vector data are rasterized into n grids, where n is the number of land categories. Then, the relative area error resulting from rasterization for each land category in the grid cell is calculated in raster format. Lastly, the average of the relative area error for all land categories in the grid cell is computed with the area of a land category as weight. As a case study, the EEM-BGC is applied for evaluating the rasterization error of the land cover data of Beijing at a scale of 1 to 250,000. It is found that the error derived from a conventional method (denoted as y) is significantly underestimated in comparison with that derived from the new method (denoted as x), with y = 0.0014x (2.6667). The EEM-BGC is effective in capturing not only the spatial distribution of rasterization errors at the grid-cell level but also the numerical distribution range of the errors. The EEM-BGC is more objective and accurate than any conventional method that is used for evaluating rasterization errors.