Problem statement: Great attention had been paid on spatial data quality by the scientific community. This was due to the negative impact that a poor spatial data quality had on the competitiveness of an organization. On other hand, we can never obtain good quality data from a poor quality data. In this study, we demonstrate the effects of the different processing and preprocessing on the quality of spatial data. As we know each type of processing introduces errors and deformations at the original spatial data. Approach: Field applications and real samples were presented to prove the effect of data processing on data quality. We used spectrally and spatially processed satellite images which present the following areas: (i) Greater Amman area, (ii) Walla and Habisse basins. Different types of processing using different scales and resolutions were applied to field applications to evaluate the effect of scale, resolution and electronic transfer from vector to raster. Results: The vector layers extracted from these spatial data at different scales and resolutions were compared to each other. The comparison showed a great deformation in shape and value. This research demonstrates the influence of the scale, the resolution and transformation from vector to raster of spatial data base on the accuracy. Conclusion: We concluded that scale, resolution and electronic transfer have great effects on data quality. This effect should be considered in building any data base and all data base must have history file for evaluating its accuracy quality.