Dot density mapping uses raw total data to display distribution patterns. After carefully choosing an appropriate size and value, dots are distributed on the map in such a way that they most accurately reflect actual distribution on the ground. Limitations can be placed on the data so that dots are not displayed in areas where they wouldn't actually be. For example, population dots in the map above are not placed in lakes, ponds, marshes, etc. Instead they are confined to areas selected specifically to match the type of data (population) that is the focus of the map - in this case, urban areas are an attribute that relates to population density and distribution, so using a mask, the dots were only included in urban areas.
Dot size and value are also important aspects of making a map of this type. The goal is to display the data in a way that enhances understanding of the data in an accurate way. When the dots are too large or too small, patterns can be missed or misinterpreted.
This method is especially suited to some types of data. The text illustrates this with maps of wheat harvests, and the map above with population data. I have also seen it used successfully in archaeological contexts, and I hope to learn more about this in future courses.
No comments:
Post a Comment