GIS Concepts

REPROJECT
      For this project, we did not use any obscure/hidden GIS Operations that ESRI is famous for hiding within their software programs.  Our project only required a few simple GIS Operations that most novice users would be familiar with.  For example, we started off by creating a central folder [Ethiopia Reprojected WGS 1984] in which we placed all the Ethiopia Data we had at our disposal for this assignment (IT WASN’T MUCH).  As the folder title indicates, we Reprojected all the spatial data into:
WGS84 UTM 37N.  This is very simple, first open ArcCatelog, then open the ArcToolbox, next, double click on Data Management Tools, then double click on Projections and Transformations.  Under Projections and Transformations, double click on Feature, then double click on Batch Project.  Under Batch Project, load all your spatial data you want to reproject.  Once you do so, follow down the list and select the Output Folder as the folder you created above describing your Reprojected Data.  After that, select the Output Coordinate System you want your data Reprojected into.  Hit OK and let Arc do its thing.  This is very simple and especially important in maintaining common projection throughout your dataset.

CLIP
     Yet again, we used another simple operation that most GIS novices would be familiar with.  For our project, we needed to set a boundary around the shapefile Bale Mountains National Park, and we determined that this would be our Study Area. This study area was used in clipping out the MODIS Land Cover File that we obtained online.  When we received it, the MODIS Land Cover File was for most of Eastern Africa, but we were only concerned with a small portion of Southern Ethiopia.  In Particular, we were only concerned with the area in and around Bale Mountains National Park.  Even though the MODIS file was in a Raster format, it could be clipped using our Vector Study Area Shapefile and our Bale Mountains National Park Shapefile.  Don’t get confused, but we had to do a series of Clips to accomplish this.  First, we started with the 2001 MODIS Land Cover File and the Study Area Shapefile (THAT WAS ALREADY REPROJECTED INTO WGS84 UTM Zone 37N).  Open ArcCatelog, Open ArcToolbox, like we did for the Reprojection described above, This time double click on Analysis Tools, then double click on Extract.  Below Extract, double click on Clip.  Once the Clip window is open, we have a decision to make: what do we put into the Input Features?  If you get confused easily like myself, there is a nice diagram under the ArcDesktop Help section that every Arc user should be very familiar with.  Moving on, we want to put the MODIS Land Cover File into the Input Features and use the Study Area Shapefile in the Clip Features option.  The output file is automatically created for you, but you can change the name and the output destination by selecting the browse button within the Clip Window.  Hit OK and you have a clipped out version of your original file.  For our Project, I clipped out the MODIS Land Cover Files (2001 and 2004) using the Study Area as the Clip Features Option.  Again, I used the MODIS Land Cover Files (2001 and 2004), but this time I wanted an even smaller clipped out region, so I used the Bale Mountains National Park(THAT WAS ALREADY REPROJECTED INTO WGS84 UTM Zone 37N) as the Clip Features Option.  When finished, I had 4 new files, a clipped out Study Area_Land Cover File from 2001, another from 2004, a clipped out Bale Mountains National Park_Land Cover File from 2001, and another from 2004.  Like the Reproject Function, Clip is a handy tool to familiarize yourself with in using Arc.

ATTRIBUTE MANIPULATION
      Another important tool that we all should be very familiar with: Attribute Manipulation.  Make sure you have the Editor tool properly docked within ArcMap.  First, open ArcMap, load in the layers that you want to work with.  In our case, we manipulated the attributes for the 4 clipped files mentioned above.  To open the Editor Toolbox, Click Tool and then click on Editor Toolbar and dock it into the Toolbars.  Open the attribute table of the first layer you want to manipulate.  Now, you must decide how you will manipulate the data to prove your findings.  In our case, it was as simple as adding a Field we called CoverType (we used the same name for all four files to keep it simple)  To add a field, click on Options and select Add Field, properly name the field and decide if you want a text field, an integer field(short or long), a Float  with 7 significant digits, a Double with 15 significant digits, etc.  In our case, I created a text field with 55 units in length (50 is the default).  Once you created your field, Now Click on the Editor to Start Editing. Very Important, Make Sure the layer you want to Edit appears under the Target location.  Once, you are certain you are editing the correct layer, you can add values into your new field.  Our case was simple, we Named the Cover Type from the Medadata file we received with our Land Cover Files and placed the Pixel Count in parenthesis, for example, the first row entry looked like this: Water (2,270,081).  Once you filled in all the values, Click again on the Editor Button and Save Edits, THEN Click STOP EDITING, it is Very Important that you Click Stop Editing, so that you do not add or delete any more edits to the attribute table.  For our project, it was important to show the change in Pixel Values between 2001 and 2004, so when we added the Cover Type within the 2004 File, we did something slightly different, we labeled it like before, but we subtracted the Pixel Values from 2001 to get the Net Difference between the two Datasets.  This was also duplicated under the two Bale Mountains National Park Land Cover Datasets for consistency.  For example, the Water Field under Study Area 2004 looked like this: Water (Net Loss 393).  This was done for the remaining values to show either a Net Loss or a Net Gain within the CoverType field.  As mentioned before, This was also repeated for Bale Mountains National Park Land Cover 2004 to show either a Net Loss or Gain in relation to Bale Mountains National Park Land Cover 2001.  This is a very simple was to show differences within the attribute values of the Datasets and you can display this in the Legend of the corresponding maps you create to show your results.

CREATING SHAPEFILES – TWO DIFFERENT APPROACHES
     The last thing we did for this project was to display the towns and villages around Bale Mountains National Park without all the other thousands of cities, towns, and villages that were also in the eth_towns file we were given for this project.  Once it was Reprojected, we looked in the attribute table for villages and towns that were located near, or around Bale Mountains National Park.  This was not a simple task, of the thousands of cities, towns, and villages, we were looking for only a few towns that were in the Bale region that we could display in our Location Map for our Presentation.  We identifies, Adaba, Dinsho, Dodola, and Goba as residing within the Bale Region.  With the attribute table open, we selected these four towns individually and created a Shapefile for each.  This is accomplished as follows, select the town(make sure it is highlighted), then close the attribute table and click on the Selection feature at the bottom of the ArcMap directory.  Once you click on the Selection feature, it will appear with a parenthesis around the number of features you selected.  Right click on the text and scroll down to Create Layer from Selected Feature(s), click on that and Click back on the Display Tab located beside the Selection tab that you previously clicked on.  Once you click on the Display Tab the highlighted Feature will appear as a layer file within ArcMap.  Next, right click on the layer file and scroll down to create a Data layer from the selected file. Choose where you want to save it and name it properly.  For our project, we created several individual files for the villages and towns surrounding Bale Mountains National Park.

     Yet another way to create a shapefile, or series of shapefiles is done within ArcCatelog.  We did this for a few small towns the resided within the Park.  These small towns appeared in a Journal Article that we were given, but were too small to appear in the eth_towns file that we used to create the other towns listed above.  The small towns were just a few hundred households, but important to show that they were within the National Park.  This was accomplished very easily.  Under ArcCatelog, click on File New, then scroll down to new shapefile, name it properly, decide if you want it to be a polygon, polyline, or point shapefile.  For our example, we wanted a Point shapefile and we set the projection to WGS84 UTM 37N when we created the shapefile.  Once the shape file was created, we loaded it into ArcMap along with the Bale Mountains National Park Shapefile.  Once loaded, the BMNP file was the only file visible within ArcMap, so we needed to add points to the newly created shapefile.  This was created quite simply, we once again Clicked on the Editor Toolbar, and Started Editing.  We made sure the Target was the new created Rira, Ketcha, and How Shapefile. We named it that because those were the three villages with the Park we wanted to identify.  Using the Map located within the Journal Article, we digitized in the three towns as close as visually possible to the corresponding locations within Bale Mountains National Park.  We knew that this was not an exact science, but close enough for the visualization purposes we would be using them for.  Once the three villages were digitized into the shapefile, we saved our edits and stopped editing.  Because we had a household size for these three small villages, we added an attribute within their attribute table, like we described above, to depict the estimated population of these villages.  We decided that each household size ranged between 6 – 10, we calculated the village population using an equal number of household sizes 6, 7, 8, 9, and 10.  When this could not be done equally, we underestimated the household size by multiplying the largest number or numbers by the smaller divisible number.  For example, Rira’s number of households was not divisible by 5, so I multiplied the lower 4 numbers by the larger numerator and the highest number (10) by the smaller numerator.  In doing so, we got a rough estimate of the three small villages that reside within the National Park.