The models of the accuracy loss during rasterizing landuse vector data with multi-scale grid size

During spatial analysis, the vector data are always changed into raster data because of convenience for spatial analysis. How the area accuracy loses during rasterizing is answered here by rasterizing the landuse vector data of Chongqing City with a multi-scale grid size. Firstly, the landuse vector data are rasterized with the grid of different resolution from 30 m to 1000 m. The value of each grid takes the landuse type code of the dominant area. Secondly, the area for each landuse type is calculated in the grid. Thirdly, the area for each landuse type is also calculated in vectors and used as the actual area. The number and average size of polygons for each landuse type are calculated. Fourthly, the relationship between the accuracy loss, the grid size and the average plot size of each landuse type was analyzed. Finally, models for describing the relationships were formulated. It is shown that the relationship among the accuracy loss (Y), the grid size (X) and the average plot size (S) of each landuse type can be described by such model as, Y=5.366-0.179X-0.978ln(S)+0.0348 Xln(S). The correlation coefficient of the model is 0.93. The model can be used to predict the accuracy loss when the vector data are changed into raster data under the different grid size