Here is a dot density map that shows the number of sheep in New Zealand (by province). number of hectares of land treated for weed control in Russia, 1997 (1 dot = 500 hectares).number of people, by county, USA, 2010 (1 dot = 10,000 people).earthquake epicenters across the Pacific for the past 10 years (1 dot = 1 epicenter). the distribution of car dealerships in Belgium (1 dot = 1 dealership).There are at least three big advantages of dot density maps over choropleth maps: (1) on a dot density map you can map raw data / simple counts (e.g., number of farms) or rates and ratios (e.g., number of farms per sq kilometer) (2) your data need not be tied to enumeration units and hence some of the concerns inherent in choropleth maps can be side-stepped with dot density maps (unless, of course, your data are reported by enumeration units-in which case you’re probably stuck with them) and (3) dot density maps work fine in black and white, when color isn’t an option.Įxample datasets appropriate for dot density maps: Albers Equal Area Conic, Sinusoidal, and Cylindrical Equal Area are all good choices. This is critical - using a map projection which does not preserve the size of areas will distort the perceived density of the dots. NOTE: All dot density maps must be drawn on an equal area map projection. There are two basic types: one-to-one dot density maps (one dot represents one object or count) and one-to-many dot density maps in which one dot stands for a number of things or a value (e.g., 1 dot = 1,000 acres of wheat production). Dot density maps have been popular for 150 years because they are easy to understand and, at a glance, show us intuitively where things clump or cluster. While the lowest population density is recorded by No income group available with a population density of only 24.7.Dot density maps are a simple yet highly effective way to show density differences in geographic distributions across a landscape. If we devide the global population into income groups we can see that Lower-middle-income countries has the highest population density of 135.4 people per square kilometer. While the sub-region with lowest population density for the yearĪustralia/New Zealand with only 4.0 people/km². When devided into sub-subregions we can see that Southern Asia had the highest population density of 316.8 people per square kilometer.Ĭlosely followed by Caribbean with a population density of 201.5 people/km²,Īnd Western Europe with 179.8 people living per square kilometer. The geographic region with the highest population densityĪsia with a density of 151.5 people per square kilometer.Ĭlosely followed by Africa with a population density of 49.4 people/km²,Īnd Europe with 33.6 people living per square kilometer. □□ Greenland with 0.1 people per square kilometer.įollowed by □□ Falkland Islands (Malvinas) with a density of 0.3 people/km²,Īnd □□ Western Sahara with 2.2 people living per square kilometer, if said population is spread out evenly across its land mass. The country with the lowest annual population density □□ Monaco with a density of 24360.7 people per square kilometer.Ĭlosely followed by □□ China, Macao SAR with a population density of 22004.7 people/km²,Īnd □□ Singapore with 8806.3 people living per square kilometer, if spread out evenly. The country with the highest population density A population density of 61.7 (people/km²).
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |