2 pages ppt

Lab 4 Exercise your understanding geographic coordinates (i.e., longitude/latitude, hereafter long/lat)

It is well known that the actual coordinates are a combination of several Numbers. Longitudes runs between the North and the south poles measuring east west position while the latitudes ranges from 0o to 90o at the poles. There are different formats for geographic coordinates whose numerical value for the latitudes and longitudes occurs in different formats, one of the formats is Degrees, Decimal, Seconds (DDS). Meaning that this geographic coordinate can be expressed in terms of degrees, minutes, seconds, both for the latitudes and longitudes (Isserlin, 2010). The second format is Decimal Degrees which means that the coordinates of a given location in terms of the latitudes and longitudes. Positive latitudes are the ones that are located north of equator while the negative latitudes ate located to the south (Merico, 2010).

An example of the question DDS from lab 4 a location of Tehran, Iran is Latitude: 35.340503° N Longitude: 51.171875° E Latitude: 35 degrees, 20 minutes, 25.8102 second Longitude: 51 degrees, 10 minutes, 18.75 seconds. And that for Cairo, Egypt Latitude: 30.169648° N Longitude: 31.132812° E Latitude: 30 degrees, 10 minutes, 10.7322 seconds Longitude: 31 degrees, 7 minutes, 58.1232 seconds.

Rescue team searching for light aircraft in UK is one of the situations that required the uses of geographic coordinates in the search of an aircraft that had vanished according to police investigations.

Knowing how to work with the geographic coordinates in this case the longitudes and the latitudes is helpful as location of places and things becomes easier when using the coordinates.

Projection and coordinate systems

Differentiate between different kinds of projection families

Cylindrical projections is a map projection that has straight coordinate outlines that has straight parallels that crosses meridians at right angles. Each of the meridians are spaced and the with a consistent scale along each parallel. this scaling can be used when you want to the parallel lines in mapping distinguishing this map from one another. The parallels and the meridians don’t allow curvature on earth to be taken into consideration as they are straight. They are perfect in the comparison of the latitudes with each other its useful in the teaching and visualizing the world even though its not the most exact way that visualizes how the globe looks like (question 2). Examples of this projections include the polar Mercator projections, Cassini, Gauss-Kruger and Miller (Segal, 1992).

Conical projections on the other hand are distinct by the cone continuous that decrees the distance angular between the meridians. The meridians are equidistant and straight lines and meets at a point along the projections irrespective of if there’s a pole or not. They are planned to wrap around the cone on the top of sphere and its parallels crosses the meridians at the right angles having a continual measure all through (Korobkin,1992). They are best in use as regional or hemispheric maps. Its distortion makes it unsuitable for use as a pictorial of the entire globe but this still doesn’t make it great for use to visualize the template regions, whether maps, and the climate projections. Its examples include the lambert conformal conic and Albers conic.

Azimuthal projections is angular given three points on mapping. Two points shows the angle that someone has to look or travel so as they can get to the third point. The angular relationships referred as the perfect circles arcs, its main feature are straight meridian lines that radiates out from a centre, the parallels that are spherical around this centre point and the intermediate parallel space.

Spatial data analysis

Investigating if there are other relationships between variables in the data set (lab 7)

According to the data that’s presented in the table above, different people of different wealth category have been estimated with the miles where they live. From the data presented, in the table, it shows that people in the wealth category 1 currently live at an average of 47 miles from where they grew up. People from wealth category 2 live at an average of 72 miles, category 3 at an average of 85 miles. Therefore, the data set shows that people from category 1 are the one who live closest from where they grew up (Ghilani, 2017). Those from category 4 currently are the ones that are further away from where they grew up by an average of 119 miles (Gotway, 2017). 

The data is distributed unevenly hence showing that there is no linear relationship between where someone group and places where they currently live (Schabenberger, 2017). 

In real life the relationship between the data set can be used in the, determining of wealth fluctuation in the families economic conditions between different families.

Analyzing this spatial information of the variables in the data set is hectic as in this case figuring out the wealth variables of the individuals and where they lived needs getting personal information which other people may not be willing to give.

References

Schabenberger, O., & Gotway, C. A. (2017). Statistical methods for spatial data analysis. Chapman and Hall/CRC.

Bailey, T. C., & Gatrell, A. C. (1995). Interactive spatial data analysis (Vol. 413). Essex: Longman Scientific & Technical.

Segal, M., Korobkin, C., Van Widenfelt, R., Foran, J., & Haeberli, P. (1992, July). Fast shadows and lighting effects using texture mapping. In ACM Siggraph Computer Graphics(Vol. 26, No. 2, pp. 249-252). ACM.

Kimerling, A. J., Muehrcke, P., Muehrcke, J. O., & Muehrcke, P. M. (2016). Map use: reading, analysis, interpretation. Redlands, CA: Esri Press.

Merico, D., Isserlin, R., Stueker, O., Emili, A., & Bader, G. D. (2010). Enrichment map: a network-based method for gene-set enrichment visualization and interpretation. PloS one, 5(11), e13984.