For this lab, all distances will be in Miles
Conformal Projections:
Washington D.C to Kabul Distance
Planar: 10,112.12
Geodesic: 6,934.47
Loxodrome: 8,112.061
Great Elliptic: 6,934.48
Washington D.C to Kabul Distance
Planar: 9,878.03
Geodesic: 6,934.48
Loxodrome: 8,112.06
Great Elliptic:6,934.48
Equidistant projections:
Washington D.C to Kabul Distance
Planar: 6,972.5
Geodesic: 6,934.47
Loxodrome: 6,972.5
Great Elliptic: 6,934.48
Washington D.C to Kabul Distance
Planar: 6,648.75
Geodesic: 6,934.47
Loxodrome: 6,648.75
Great Elliptic: 6,934.48
Equal Area
Washington D.C to Kabul Distance
Planar: 8,098.07
Geodesic: 6,934.47
Loxodrome: 8,112.06
Great Elliptic: 6,934.48
Washington D.C to Kabul Distance
Planar: 10,108.05
Geodesic: 6,934.47
Loxodrome: 8,112.06
Great Elliptic: 6934.48
For this lab, six different maps were created using ArcGIS and each map was a different type of projection. Some projections were recognizable and others were very unusual, however each map had its own purpose and fit into a certain category. For this lab, 3 different map projection categories were to be shown, with 2 different projections for each category being put on the page. The three categories are: equidistant, equal area, and conformal. Conformal maps preserve the angles between the longitude and latitude lines and can be recognized by the 90 degree angles of intersection between longitude and latitude lines, equal area projections keep the relative size of countries the same, and equal distance projections keep the distances between points at close to or at exactly their calculated value. For this lab, mercator and stereographic projections are shown for conformal examples, sinusoidal and cylindrical equal area maps were used for examples of equal area projections, and the equidistant conic and the 2 point equidistant projections are used to give examples for equal distance category.
There are some clearly significant things that come with choosing a map projection. The first of which is distance between two points and choosing a type of measurement to find the distance. The earth's imperfection in terms of geometry makes calculating distances tough, and on the 2D projections of the earth, there are 4 different distance measurements that can be given. What is constant between all 6 maps above are the Great Elliptic distances between Washington D.C. and Kabul, which comes out to 6,394.48 mi. When looking at distance, the maps with the most accurate readings are the 2-point Equidistant and the Equidistant Conic because their distances are preserved, with the other types of measurements staying near the calculated distance of 6,394 mi. However if distance is the goal being examined, the conformal and equal area projections are not quite accurate and hence provide an example of one pitfall in the process of projecting the Earth's surface into a 2D model. What that means is that if one needed to use a map, the right projection must be used, and if accurate distances were the goal to strived for, map projections such as the Mercator Conformal, and the Sinusoidal Equal Area projections would not be appropriate choices for this purpose. The problem with limiting the amount of projections that can be used for data collection and observation is that now one other factor has been neglected when choosing that type of map. In this case, if one were to use the 2 Point Equidistant map, the angles between latitude and longitude would no longer be preserved, and some issues can arise, such as in navigation, bearings would be all wrong and the heading of a ship can be in the wrong direction. What matters is that each projection contains both potential and pitfalls, and in that case the proper projection must be used with a certain goal.
As seen before, the importance of map projections is clearly stated, and there are some overall potentials to having map projections. For starters, map projections allow users to easily read and access information in a 2D platform. That means computers are not necessarily needed to read and scrutinize map projections, and therefore are available to a much larger demographic. Next, map projections can specialize the information on a map to only what is desired by the user. For instance, if the user wanted to find the relative areas of countries in Africa, the Cylindrical Equal Area projection can be used because the areas between land masses are kept equal with respect to one another. That means what can be seen from this projection is the comparative size of countries in Africa to countries of Europe. For equal areas, the user would not want to use the map not designed to keep relative areas accurate, such as the Mercator projection or the Stereographic projections because the data given would be inaccurate. When looking at the Stereographic projection, the USA looks bigger than all of Africa, however in the Cylindrical Equal Area projection and the Sinusoidal Projection, the USA is clearly much smaller than Africa, which is the more accurate representation of the land masses. Overall, there are problems with map projections however the potential of easy to read and well presented data are very much a part of map projections.
Overall, there are potentials and problems with map projections in general. All of which stem from the fact that the earth is a 3D object trying to be projected onto a 2D space. On top of that, the Earth is full of lumps and does not make a perfect geometrical shape that is easy for projecting onto a 2D surface. It is because of this that these projections must sacrifice the accuracy of one aspect to ensure the accuracy of another. That means a clear goal must be focused on when trying to choose a certain map projection because if the wrong projection is chosen, the data that is obtained could be inaccurate. However when analyzing the different projections in ArcGIS, choosing a certain projection is much easier as shown by this exercise because ArcGIS allows multiple maps to be compared and contrasted in order to find the right projection without too much of a technical struggle. This exercise was concise, and provided a good introduction into the powerful uses of ArcGIS as a tool.
Conformal Projections:
Washington D.C to Kabul Distance
Planar: 10,112.12
Geodesic: 6,934.47
Loxodrome: 8,112.061
Great Elliptic: 6,934.48
Washington D.C to Kabul Distance
Planar: 9,878.03
Geodesic: 6,934.48
Loxodrome: 8,112.06
Great Elliptic:6,934.48
Equidistant projections:
Washington D.C to Kabul Distance
Planar: 6,972.5
Geodesic: 6,934.47
Loxodrome: 6,972.5
Great Elliptic: 6,934.48
Washington D.C to Kabul Distance
Planar: 6,648.75
Geodesic: 6,934.47
Loxodrome: 6,648.75
Great Elliptic: 6,934.48
Equal Area
Washington D.C to Kabul Distance
Planar: 8,098.07
Geodesic: 6,934.47
Loxodrome: 8,112.06
Great Elliptic: 6,934.48
Washington D.C to Kabul Distance
Planar: 10,108.05
Geodesic: 6,934.47
Loxodrome: 8,112.06
Great Elliptic: 6934.48
For this lab, six different maps were created using ArcGIS and each map was a different type of projection. Some projections were recognizable and others were very unusual, however each map had its own purpose and fit into a certain category. For this lab, 3 different map projection categories were to be shown, with 2 different projections for each category being put on the page. The three categories are: equidistant, equal area, and conformal. Conformal maps preserve the angles between the longitude and latitude lines and can be recognized by the 90 degree angles of intersection between longitude and latitude lines, equal area projections keep the relative size of countries the same, and equal distance projections keep the distances between points at close to or at exactly their calculated value. For this lab, mercator and stereographic projections are shown for conformal examples, sinusoidal and cylindrical equal area maps were used for examples of equal area projections, and the equidistant conic and the 2 point equidistant projections are used to give examples for equal distance category.
There are some clearly significant things that come with choosing a map projection. The first of which is distance between two points and choosing a type of measurement to find the distance. The earth's imperfection in terms of geometry makes calculating distances tough, and on the 2D projections of the earth, there are 4 different distance measurements that can be given. What is constant between all 6 maps above are the Great Elliptic distances between Washington D.C. and Kabul, which comes out to 6,394.48 mi. When looking at distance, the maps with the most accurate readings are the 2-point Equidistant and the Equidistant Conic because their distances are preserved, with the other types of measurements staying near the calculated distance of 6,394 mi. However if distance is the goal being examined, the conformal and equal area projections are not quite accurate and hence provide an example of one pitfall in the process of projecting the Earth's surface into a 2D model. What that means is that if one needed to use a map, the right projection must be used, and if accurate distances were the goal to strived for, map projections such as the Mercator Conformal, and the Sinusoidal Equal Area projections would not be appropriate choices for this purpose. The problem with limiting the amount of projections that can be used for data collection and observation is that now one other factor has been neglected when choosing that type of map. In this case, if one were to use the 2 Point Equidistant map, the angles between latitude and longitude would no longer be preserved, and some issues can arise, such as in navigation, bearings would be all wrong and the heading of a ship can be in the wrong direction. What matters is that each projection contains both potential and pitfalls, and in that case the proper projection must be used with a certain goal.
As seen before, the importance of map projections is clearly stated, and there are some overall potentials to having map projections. For starters, map projections allow users to easily read and access information in a 2D platform. That means computers are not necessarily needed to read and scrutinize map projections, and therefore are available to a much larger demographic. Next, map projections can specialize the information on a map to only what is desired by the user. For instance, if the user wanted to find the relative areas of countries in Africa, the Cylindrical Equal Area projection can be used because the areas between land masses are kept equal with respect to one another. That means what can be seen from this projection is the comparative size of countries in Africa to countries of Europe. For equal areas, the user would not want to use the map not designed to keep relative areas accurate, such as the Mercator projection or the Stereographic projections because the data given would be inaccurate. When looking at the Stereographic projection, the USA looks bigger than all of Africa, however in the Cylindrical Equal Area projection and the Sinusoidal Projection, the USA is clearly much smaller than Africa, which is the more accurate representation of the land masses. Overall, there are problems with map projections however the potential of easy to read and well presented data are very much a part of map projections.
Overall, there are potentials and problems with map projections in general. All of which stem from the fact that the earth is a 3D object trying to be projected onto a 2D space. On top of that, the Earth is full of lumps and does not make a perfect geometrical shape that is easy for projecting onto a 2D surface. It is because of this that these projections must sacrifice the accuracy of one aspect to ensure the accuracy of another. That means a clear goal must be focused on when trying to choose a certain map projection because if the wrong projection is chosen, the data that is obtained could be inaccurate. However when analyzing the different projections in ArcGIS, choosing a certain projection is much easier as shown by this exercise because ArcGIS allows multiple maps to be compared and contrasted in order to find the right projection without too much of a technical struggle. This exercise was concise, and provided a good introduction into the powerful uses of ArcGIS as a tool.
No comments:
Post a Comment