Importing Tabular Data

The map above is the result of importing tabular data. Initially the parcels shapefile was added to the data view. The claimant and sampling location were also added through the “Add XY Data” option to show the specific location for each using WGS 1984. The parcels table was added next; it was joined to the parcels layer and then converted to a shapefile. A query was carried out from the Attribute selection using the Parcel layer, Market_Val to show the value of the parcels by means of colors. A legend, scale, scale bar and a north arrow were included in the map. 

Georeferencing

The map above depicts the result of Georeferencing. In this exercise two maps were edited separately and later joined to create one map. The first map was done by identifying and matching features of the unreferenced control layer and linking it to common points using a tool in Arc map. Before saving the root mean square error was recorded.  The root mean square error is the difference between the locations that are known and locations that have been interpolated.  The second map went through a similar process. Features of the unreferenced layer were linked to common points however   a second order polynomial was selected for this map. After the linking had been completed the RMS Errors were recorded. A legend, scale, scale bar and a north arrow were also included in the map

Cayo District

The picture above shows the map of Cayo District. The map shows the protected areas under several categories including National Parks, Natural Monument, Nature Reserve etc.  The map also contains names of towns and city as well as major roads and rivers. Note: additional road networks and streams were initially part of the map but it became too congested and so it was removed. Finally, all standard map elements such as scale, title and legend were included. An incept was also made part of the map as it indicates the location of the Cayo District in the country of Belize. Since some data was obtained from an external agency the source is also indicated in a text box.  

GPS Collection

The map above represents a portion of the University of Belize Belmopan Campus. Students were assigned to collect GPS coordinates for three trees which are clearly shown to be a, Cotton Tree, Almond Tree and a Coconut Tree. The second activity was to record the directions, using GPS coordinates, from one point to another. Group #2 recorded coordinates from the Gymnasium to the Bookstore. Lastly students collected GPS coordinates for the library building; note that the area of the building was also calculated here. After the raw data was collected, it was imported into Arc map and a shapefile was created and edited following several detailed instructions. Finally a base map and other standard map elements were added. 

Projections

The map above represents the state of Florida in the United States of America.  On the left hand side the map is showing the use of UTM projection while the map on the right hand side it is using the Albers projection. The map also shows the comparative areas for Alucha, Escambia, Polk and Miami-Dade, which are counties under the state of Florida. This activity covered several topics in map projection. These include re-projecting shape files and raster, defining projections, adding a new attribute field and calculating geometry in an attribute table.  

Mexico

 In this activity we were introduced to Arc catalog but concentrated on Arc map where the work was done. In this map the World Countries map and the Mexico Map layers were used. The activity however was based only on the Mexico’s states and population while the rest of the world map was isolated. The labels for the Mexican map were added which are represented by the different states of the country; note that annotations were also added in order to manipulate the labels. In addition to the labels some color was added to it. This was chosen with the intention that the light yellow areas were states with a low density population while the bright yellow colored areas represent states with a high population density. Finally the legend depicting the population density was included as well as the scale, scale bar, north arrow and labeling of the map.

The map above represents the country of Mexico. This map had several layers added to it, mainly the primary rivers, main rivers, rail roads, urban areas and the federal which is viewed as Mexico City on the map. The map was cluttered at first but each layer was manipulated to select specific features on the map. For example the layer with rivers showed rivers, streams canals and shorelines but by selecting only the primary and major rivers on the add values section under categories and unique values under symbology properties all the other irrelevant data was not included in the map.  Each layer was then given a specific color to represent a different feature in the map. Note that annotations were added to the map in order to manipulate the labels. Finally a data frame was created to show the location of this map in a broader geographic context; to do this a new data frame was selected and the world countries layer was dragged into the new data frame. The map was arranged and activated. As with all maps the legend depicting the rivers, rail roads, urban and federal were included as well as the scale, scale bar, north arrow and labeling of the map.

The map above represents the elevation of Mexico. This map involved only the elevation layer which used the stretch symbology. A color was chosen to depict the elevation in low and high areas of the country. The legend depicting the elevation in high and low areas of the country was then created; note that the red color represents high areas while the blue color represents low areas. The scale, scale bar, north arrow and labeling of the map was done at the final stage. 

World Map