Monday, November 9, 2009




            Map projections in GIS project the shape of three-dimensional earth using mathematical formulas onto a two-dimensional surface.  Projections cause the map to be distorted while other characteristics are maintained.  The three different map projections used in this exercise are: Conformal, Equal Area, and Equal Distant.  It is significant to use the right projection for a map because different projections distort different features.  For example, if the map shows the area of snow melting in the Arctic, is it important to use the Equal Area map projection so the area shown is not distorted.   Map projections Sinusoidal and Hammer-Aitoff can be used for mapping snow pack in the Arctic.  Conformal maps, such as Mercator and Gall Stereographic, preserve angles of the surface.  Conformal maps are used for navigating ships. Equidistant maps, like Equidistant Conic and Equidistant Cylindrical, show the correct distance from the center of the projection to any other points.  One use for equidistant maps is for seismic mapping.  Map projections are significant to a variety of different fields and are significant for displaying the data in different ways.  All of the map projections have positive and negative aspects.  It is important to choose the correct map projection for the information that is being shown in the map.

            It is important to know the limitations of the map projections in order to accurately display the information.  One peril to map projections is that not all of the projections can represent the same data.  For example, mapping nautical patterns and ice patterns need different types of projections.  Another problem with map projections is that not all projections within the same category show the same information.  For the Equidistant maps above, Equidistant Conic and Equidistant Cylindrical do not show the same distance from Washington, D.C. to Kabul, Afghanistan.  Even though these maps maintain distance, they show different distance values.  One reason why Equidistant mapping is not consistent in all map projections is because the map is equal distant from the center of the projection to other points.  For example, if the center of the map is Los Angeles, he distance from Los Angeles to any other location will be accurate.  If we used this same map to find the distance from San Diego to Las Vegas, we would not get the correct distance because neither of these points are the center of the map projection.  For the Equidistant maps above, the center of the projections were at different locations which is why the distance between Washington D.C. and Kabul are not the same.  It is important to know which projections correspond to different areas.  Some projections are world projections whereas some projections are specific to a certain continent or country. 

             Conformal maps and Equal Area maps also have issues to be cautious of.  An issue to be aware of for Conformal maps is that the angles of the map are preserved, but the shape of the map is only preserved with small areas.  This can be a problem when mapping the earth since it is dealing with a very large area.  For the two different conformal maps above, the distance between the two locations is different.  The Mercator map above shows the earth as taller and thinner compared to the Gall Stereographic which shows the earth more proportional.  Also the poles on the Mercator map are elongated compared to the Gall Stereographic.   Equal Area projections also have flaws in its design.  The Sinusoidal map projection above shows the poles pointed whereas the Hammer-Aitoff shows the poles rounded.  Although this projection conserves area, the distance between Washington D.C. and Kabul are very close with both projections showing a distance close to 8,000 miles.  One thing to note about these projections is that the parallels are curved for the Hammer-Aitoff and the parallels are straight for the Sinusoidal.  There is no distortion along the equator for the Sinusoidal and Hammer-Aitoff projections.  Different map projections distort different features.  By knowing which features are distorted, the best projection can be used to display the data.

            Although all map projections distort a feature, projections are very useful when mapping different features.  By having different projections, it is possible to see different areas of earth emphasized.  A potential of map projections is to emphasis different features while deemphasizing other features.  By using specific projections for specific topics, we can get more accurate maps.  Having a variety of projections to choose from allows us to pick the projection that will most accurately display the data.  If the only map projection available was Conformal projection for example, then the distance between two locations would never be accurately shown on the map.  The same is true for Equal Area; if the only map projection available was Conformal, then the area in the poles would always be distorted and the poles would always seem significantly larger than they are.  Another potential of map projections is to use them in physics and engineering.  By having different map projections, engineers can choose the projection that gives them the most reliable information.  This helps to reduce engineering problems.  If engineers need to know the exact distance to a specific location, they would use Equal Distance projections and not Equal Area or Conformal projections.  Another potential and one of the most significant potentials of projections is for Climate Change data.  Having different map projections allows us to map a variety of different factors related to Climate Change including: ice and glacier melting, temperature changes, precipitation patterns, and sea level among others.  Map projections can help us predict changes and helps us to analyze current patterns.  They are essential in showing areas of concern and areas that are relatively stable.  Although there are many different types of map projections, the possibilities in mapping important geographic and environmental data are endless.


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