Graphical data comes in two forms: vector and raster. Vector data is composed of mathematical points, lines and polygons. Since the data is mathematical, it can be scaled to any level without a loss of quality.
Raster data, also known as bitmap data, is composed of different color squares next to each other. In the most simplest form, take a sheet of grid paper and color in the squares; that is a bitmap image. Digital cameras take bitmap images. When you zoom into the image enough, you will start to see squares.
Satellite and aerial images are bitmap images because they are digital photographs. A human can look at the image and see the object made by the pixels. A computer had a harder time since it looks at the pixels on an individual level. The digital photograph must carry meta-data so the computer can understand the basics of the image.
Vector images can be converted to raster images. Just tell the computer how many pixels, and it will handle the rest. Raster images cannot be easily converted into vector images. A computer can draw contour lines at differences in hues, lightness and other color characteristics, but otherwise can’t do much.
When the Haiti earthquake struck, there was no road map of the country. This hampered relief efforts because there was no way for international responders to know what was where. A crowd-sourced project based in Open Street Maps surfaced. Volunteers around the globe were looking at before and after satellite images of Haiti. They drew the vector data by looking at the raster data. They were able to mark the roads, and then add meta-data of the road’s condition, name and other features of importance. This was collaborated online and downloaded directly to responders’ GPS units. The GPS units were able to use this data to navigate the responders. This was continued to be enhanced by loading in building names and layouts prior to the earthquake. Now an accurate pre- and post- map exists of Haiti.
It is better to have accurately captured vector data that is loaded with the meta-data. However, much of the source data that exists is raster information so there are conversions occurring. Converting data either way between raster and vector creates a margin for error and inaccuracies.
It is a good idea to check the data you are using against the source data. A common example is when a road’s vector doesn’t exactly line up well with the raster satellite image of the area. Raw satellite imagery doesn’t include an overlay of the geographical coordinates. Either the system or a person must anchor the image to a geographical location. While the center may be exact, the edge can be slightly off due to the angle of the satellite to the surface plane. This means that we can’t be certain if the variation is caused by an error on placing the satellite image or an error on the location of the vector. These errors are often small and most people won’t notice them … BUT it depends on the level of accuracy needed in the map.