GEOG360_EX7_W24_updated
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Oregon State University – Geography and Geospatial Science
GEOG 360 Exercise 7: Exploring Raster Datasets through the Syrian Refugee Crisis
Due dates:
GEOG 360 400 students: This assignment is due by Tuesday midnight (11:59 PM) PT in Week 8. GEOG 360 001 students: This assignment is due before the start of your lab session in Week 8.
Total points:
30 points
Deliverables:
The deliverables for this exercise are highlighted below in yellow. As you work through the exercise, include all requested information and screenshots in a Word document to be handed in via Canvas to the Modules > Week 7 > Exercise 7. Your document should be named <LastNameFirstName>_EX7.docx
Overview
: Location: Syria
We are beginning raster-based analysis this week by working through a hypothetical scenario where we will identify suitable locations for refugee camps along the Syrian/Turkish border. About 5.4 million people have become refugees since the start of the Syrian civil war in March 2011 -- the largest refugee crisis for nearly a quarter century -- and a further 6.9 million internally displaced people remain within Syria. Of Syrian refugees, the majority are currently in
Turkey; the placement of these refugee sites is the focus of this exercise.
To learn about this conflict and its causes, see the following articles on the current situation in Syria and the status and geographical distribution of the refugee crisis:
1. The Syrian Refugee Crisis Explained (updated 03/14/23): https://www.unrefugees.org/news/syria-refugee-crisis-explained/
2. Center for Preventive Action, Global Conflict Tracker (updated 2/13/24): https://www.cfr.org/global-conflict-tracker/conflict/conflict-syria
3. BBC: Why has the Syrian war lasted 12 years? (05/02/23):
https://www.bbc.com/news/world-middle-east-35806229
We’ll be using three criteria for finding suitable refugee camp locations:
A.
Must be within 100km of the Syrian border
Data source: Natural Earth Vector (
https://github.com/nvkelso/natural-earth-vector/blob/master/10m_cultural/
ne_10m_admin_0_countries.shp
)
B.
Cannot be located on land that has a slope greater than 10%
Data source:
Topographic DEM derived from Shuttle Radar Topography Mission (SRTM).
More info on these elevation raster data here: https://www2.jpl.nasa.gov/srtm/
C.
Must have vegetative land cover (plants and trees)
Data source: 2019 land cover dataset from Land Cover Climate Change Initiative, located at http://maps.elie.ucl.ac.be/CCI/viewer/download.php
We’ll process these three datasets into binary (0/1) maps where a value of 0 represents ‘unacceptable’ and 1 represents ‘acceptable’. Then, we’ll add these datasets into a single merged layer, which we will use to identify viable refugee camp locations. The overall effect will
be something like this, with “3” (an area where all three criteria are acceptable) representing a possible refugee camp location:
After identifying possible sites, we will use ArcGIS Pro to find out how many camps we can place
there given the minimum size of each camp. Then we will create a map layout.
You will lead this preliminary refugee camp site planning exercise to identify suitable locations for refugee camps along the Syria-Turkey border for the refugee population in Turkey. Specific learning outcomes for this exercise include:
Learn how to use the raster calculator function.
Become familiar with classifying raster datasets into binary (0/1) maps.
Become more comfortable converting vector data to raster data.
Construct a workflow diagram using Model Builder.
As you go through the exercise, remember to make notes in your GIS Notebook. You should be able to refer to your GIS Notebook to review some of the tools and procedures that we have used in past exercises if you do not remember how to do certain steps.
As part of the exercise, you will also be creating a workflow diagram of all the geoprocessing steps using ModelBuilder. So, for each step in the exercise, make note of the Input filename, the Tool and the Output filename in your GIS Notebook so that you understand the sequential steps that you have taken. If you are having trouble understanding the geoprocessing we will be carrying out in this exercise, take a look at the following ESRI help pages about the Spatial Analyst tool: https://pro.arcgis.com/en/pro-app/latest/help/analysis/spatial-analyst/basics/what-is-the-
spatial-analyst-extension.htm
https://pro.arcgis.com/en/pro-app/latest/help/analysis/spatial-analyst/model-solve-spatial-
problems/using-the-conceptual-model-to-create-suitability.htm
EXERCISE INSTRUCTIONS
1.
Create an EX7 folder in your student folder.
2.
Download the “EX7_data.zip” file to your EX7 student folder. Unzip the data into your EX7 folder.
3.
Open ArcGIS Pro. Create a new Project called “EX7” within this folder. This will automatically create the EX7 project folder as well as the EX7.gdb geodatabase to which you can save all your newly created data.
4.
Open a new map. In the Catalog, right-click > add a folder connection to your EX7 folder. 5.
To ensure that all your work is saved into the same coordinate system, when working with a
geodatabase, we can set the output coordinate system
so that all new files written into the geodatabase will be automatically projected into the same Projected Coordinate System. To do this, from within your map, navigate to Analysis > Environments. In the pop-up window, under Output Coordinates, click on the small globe icon. Navigate to the Projected
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Coordinate System and UTM > WGS 1984 > Northern Hemisphere. Set the default output coordinate system to be WGS 1984 UTM Zone 37N. Don’t change anything else here.
In addition, so that we can make measurements on our map later, from the Contents pane, right-click on “Map” and open Properties. Click on Coordinate Systems in the left panel. Under “X, Y Coordinate Systems Available”, navigate through the Projected Coordinate Systems to find “WGS 1984 UTM Zone 37N” and select it. Notice the difference in the map extent. We are now viewing only Zone 37N
in Universal Transverse Mercator.
If you are curious, here is more information on geoprocessing environments settings: https://pro.arcgis.com/en/pro-app/latest/tool-reference/environment-settings/what-is-
a-geoprocessing-environment.htm
6.
It is time to set our first criterion: Must be within 100km of the Syrian border.
To accomplish this, we will simply make a 100km spatial buffer around the Syrian border.
a)
From the EX7_Data folder you have unzipped into your EX7 folder, find the ne_10m_admin_0_countries.shp
file and add it to your map in ArcGIS Pro. These
data came from an open-source data portal called Natural Earth Vector and are the boundaries of all the countries of the world. (
https://github.com/nvkelso/natural-earth-vector/blob/master/10m_cultural/
ne_10m_admin_0_countries.shp
)
b)
Briefly examine the Properties of this shapefile so that you know what spatial referencing system you are working with (Source > Spatial Reference). Thinking spatially
: Is this data in a GCS or PCS? c)
Locate the country of Syria (if you’re not sure where it is, you can do this by increasing the transparency of your new layer until you can see the World Topographic labeling through the new layer). Using the “Select” tool on the Map tab, Selection group, select the Syria polygon:
d)
With the polygon selected (as in the screenshot above), under the Feature Layer contextual menu, navigate to “Data” and click “Export Features”. Adjust the Parameters: Make sure the Input is your ne_10m_admin_0_countries layer, the Output Location is your Ex7.gdb, and the Output Name is “Syria_border” stored within your EX7 geodatabase. “Use the selected records: 1” should be toggled. Don’t adjust the Environments at all.
e)
Hit OK. The new feature class of the Syrian border will be projected and added to
your geodatabase as well as being added to your map. If you like to keep a neat map, uncheck the box for the “ne_10m_admin_0_countries” layer so you can’t see the rest of the countries anymore, but don’t delete it – we’ll need it later.
Review
: In this process, we started with a shapefile of country boundaries. After selecting the Syrian polygon, we exported it to a new feature class (Syria_border)
within our EX7 geodatabase. Since we set the output coordinate system for our geodatabase to a projected coordinate system earlier in Step 5, the newly created layer has been projected into WGS 1984 UTM. Check the properties of the input shapefile (ne_10m_admin_0_countries) as well as the output feature class (Syria_border) to confirm that you understand what we did here.
f)
Using Syria’s geometry, use the Geoprocessing tool called Buffer
(
not
Pairwise Buffer) to construct a buffer around Syria with a distance of 100 km
. (An easy way to locate a geoprocessing tool is to search for it in Analysis > Tools.)
Your Input Features should be the “Syria_border” layer. Your new Output Feature Class should be named “Syria_border_100km_buffer'' and should be saved to your EX7.gdb (click the folder icon on the right to make sure this is where it’s being saved). Make your buffer 100 kilometers in distance and change the Side Type to “Exclude the input polygon from buffer”. This will exclude the Syrian border itself from the new feature class; we want only the area outside of Syria. For Method, we will use the default Planar method which creates a Euclidean straight-line buffer because we are working with a Projected feature class. Dissolve type should be already set to No Dissolve.
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After you run the tool, go to the Map tab > Measure
(you did this in EX4 to measure distances between cities!) to make sure the width of this buffer region is indeed 100km. Click the back arrow at the top of the Geoprocessing window to
return to the Toolbox, where we will select a different tool next.
g)
Convert “Syria_border_100km_buffer” to a raster using the Polygon to Raster (Conversion Tool).
(Be sure you are not using Raster to Polygon!) Your Input Feature is your Syria buffer polygon, of course. Your output raster should be saved to your EX7 geodatabase (it will default to the name “Syria_border_100km_buffer_PolygonToRaster”,
this is fine). Change the cell size
to 100 (it’s in meters). Leave the remaining settings alone, and run the tool.
h)
We now have a binary
raster layer (the only values are 0 and 1) to help guide our
refugee camp siting. All the values in our resulting raster are 1 (“acceptable”), because we excluded the Syrian polygon itself. If you uncheck all the layers except for your new binary raster and the basemap, it should look like this (except your buffer will likely be white; I changed it here for visibility):
If it does not look at all similar, carefully re-read the instructions to try and figure
out what may have gone wrong. Go ahead and close the Geoprocessing window when you are satisfied that you have correctly created the first binary raster.
Reminder: save your project!
Deliverable 1: Compare your vector inputs and raster outputs (toggle one layer on / off and zoom in closely to see the differences, changing symbology/color if you need to). How do the raster and vector buffer boundaries
differ? Deliverable 2: a. What are some potential land cover issues for developing refugee camps within the buffer? b. Are there land cover types that should logically be excluded from consideration when siting a
refugee camp? (Hint: toggle the buffer raster layer on/off; examine the underlying landscape).
7.
We will now set our second criterion: Cannot be located on land that has a slope greater than 10%.
Although this doesn’t seem like that much, steeper slopes would complicate construction and make refugee camp maintenance and operation quite difficult.
To accomplish this, we will import two elevation data tiles for the area, merge them into one layer and make a slope raster, then reclassify it into a binary raster.
a)
In your internet browser, navigate to this site, which provides an easy way to locate and download the SRTM data: http://dwtkns.com/srtm/
Note
: The website will give a warning “This tool doesn't work as of January 2021,
because the data paths it pointed to on external mirrors have changed” - ignore it, you are still able to download the data as 2/18/2024.
b)
Click and drag to spin the globe and locate the two DEM tiles that cover the Turkey-Syria border: srtm_44_05.zip and srtm_45_05.zip. Download both using the green “Download GeoTIFF” button.
c)
Drag these files into your EX7 folder and unzip them, then add both into your map in ArcGIS Pro. It should add two elevation tiles. Note #1:
Sometimes if files you intend to use have been added to a folder after
your project was started, you may not be able to see them in the Catalog pane because it does not auto-update – you have to do that. In the Catalog pane, navigate to the folder where your data is stored (here, your two new DEMs), right-click the folder, and select Refresh. The files should now show up.
Note #2
: when you add raster layers to your map for the first time, you may be asked if you want to calculate the statistics for the raster. Check the box to “Always use this choice” and click Yes.
Briefly examine the Properties of these rasters. Be sure to check the Raster Information in the “Source” submenu as well as the Spatial Referencing.
Deliverable 3: What is the spatial resolution
of the DEM tiles in meters? What is the X and Y cell size and what are its units of measurement? Hint: For the former, refer back to the site from which you downloaded the data. The latter can be found entirely within the raster properties. Deliverable 4: Given what you know about the properties of these rasters, and the data compatibility requirements needed to carry out an analysis, can we combine these DEM rasters with the “
Syria_border_100km_buffer_PolygonToRaster
” layer we made in step 6 without further processing
?
d)
Now we need to merge the two DEMs into a single DEM that spans the border. Open up the Geoprocessing pane again and search for Mosaic to New Raster (Data Management Tools)
. The two Input Rasters are simply the two DEM tiles. The Output Location should be in your EX7 geodatabase again, and the name of your output raster (Raster Dataset Name with Extension) is “srtm_DEM_mosaic”.
Tip
: If your EX7 geodatabase doesn’t show up in the folder, change the file type dropdown to ‘File Geodatabases’.
Assign the Pixel Type to “16_BIT_UNSIGNED” if it isn’t already, and the Number of Bands to 1. Leave the spatial reference as WGS_1984_UTM_Zone_37N, and click Run.
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Check that your combined DEM was created successfully by unchecking the boxes for its component layers, srtm_44_05 and srtm_45_05, and observing the new layer. Close the Geoprocessing window. Now we have a single combined DEM that we can use to find regions with a suitable slope for refugee camps.
Personal knowledge check
: What does DEM stand for?
e)
In Properties, check the coordinate system for the newly merged DEM. It should be WGS_1984_UTM_Zone_37N because this is what we’d previously set as the projection of the EX7 geodatabase. f)
Recall that slope (whether on a graph or on a map) is simply Rise / Run (vertical distance divided by horizontal distance). For more information on the Slope tool:
https://pro.arcgis.com/en/pro-app/latest/tool-reference/spatial-analyst/
slope.htm
g)
We have rise (elevation) and run (spatial distances), so we can now calculate a slope raster from our combined DEM. To do this, find the geoprocessing tool Slope (Spatial Analyst Tools
). Do not use “Surface Parameters” – it can be more exact, yes, but requires a lot more processing time. Input raster is the combined DEM we just made, and the Output raster should be saved within your EX7 geodatabase as “srtm_DEM_mosaic_slope”. Use “Percent Rise” as the Output measurement and do not change the other settings. Click Run.
Note
: This one may take a while to run – be patient! Clicking all around because you think it is “stuck” does not help and usually makes it take even more time.
●
Your output that may have extreme slope values in the color legend (even if they don’t exist on the map). This can be fixed by accessing the new raster layer’s Symbology (either through the “Raster Layer” contextual tab or by simply right-clicking the layer in the Catalog).
●
Change the Primary Symbology to “Stretch” and the Stretch Type to “Minimum-Maximum”. Change the statistics from “Dataset” to “Custom” and adjust the maximum and minimum values to 100 and 0, respectively. Since we have calculated the slope based on Percent Rise, we are now viewing the raster symbolized using values of 0% – 100%. To make sure it worked, look in the Contents pane and see that the gradient under the new layer now goes from 0 to 100. Close the Symbology pane.
h)
Now we need to convert this slope data layer into a binary layer (0/1). The slope raster is a continuous
dataset with a range of slope values going from 0-100%. For our purposes, any pixels with a slope >10% are too steep (unacceptable) and should be classified as ‘0’. Pixels with slope ≤ 10% are acceptable and should be classified as ‘1’.
To do this, we will use the
Raster Calculator (Spatial Analyst) tool. First, name the output raster “border_slope_class” and make sure it will be saved in your EX7 geodatabase.
Since we need a binary rule (a pixel is either too steep or not), we only need to perform one calculation in the Raster Calculator. In the Raster Calculator Window, double-click “srtm_DEM_mosaic_slope” and the appropriate Tools to compose the following equation EXACTLY:
“srtm_DEM_mosaic_slope” <= 10
TIP
: Use the buttons in the Raster Calculator window to compose your equation instead of typing it to reduce error risk. Make sure you put a space between each part of your equation.
Click Run. We now have a binary (0/1) layer based on topography,
specifically percent slope, to help guide refugee camp siting.
i)
Next we will create a hillshade raster to better visualize the landscape using the Hillshade
tool. Your input will be your srtm_DEM_mosaic from step 7d (
not
the binary slope layer you just made in step 7h). The output raster name should be “srtm_Hillshade_mosaic”, within your EX7.gdb. Click Run, and be patient!
j)
When this hillshade layer has been created, move it underneath your binary slope raster layer (border_slope_class) in your Contents and change the transparency of your binary slope raster to 50% transparency (this can be done from the Raster Layer contextual tab on the top ribbon).
You may also want to change the symbology of the binary slope raster to get a better 2.5D elevation representation if your colors aren’t contrasting enough. Example of what your binary slope raster + hillshade should look like: Reminder: save your project!
8.
We will now set our third criterion: Must have vegetative land cover (plants and trees).
Even if an area is close enough to the border and relatively flat, we can’t place a refugee camp in a body of water, an existing urban area, a wetland, etc.
a)
To map suitable land cover, we will use the European Space Agency’s Global Land Cover map from 2019. This data came from the European Space Agency’s website
. The original data contains multiple rasters of land cover from 1992 to
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2020. For this exercise, one raster layer has been extracted to show only data from 2019 in the region of interest. The land cover raster can be found in your unzipped EX7_Data folder. Do not drag it directly onto the map.
TIP
: If you don’t see it in the Catalog, it might be that you haven’t unzipped it yet. The landcover_2019 has its own zipfile as well – check in File Explorer. Remember to Refresh your EX7 folder in the Catalog so it shows up there.
In addition to the landcover_2019 raster, confirm that you also have the file named “ESACCI-LCMapsColorlegend.lyr” as well as the “ESACCI-LC-Legend.xls” in
your EX7_Data folder.
b)
Use the Raster to Geodatabase
tool to import your 2019 landcover raster to your
EX7.gdb. Note that landcover_2019 won’t be in the dropdown – you have to navigate to it, because it isn’t in your project yet. For the Output Geodatabase, navigate to and choose your EX7 geodatabase. Click Run.
In the Catalog pane, expand the EX7.gdb to see that it contains landcover_2019. Right-click and Add To Current Map. (If you don’t see it, refresh the folder again.)
Note
: when you do this, you may be asked if you want to build the pyramids. Technology sure has made construction projects easier! Check the box to “Always use this choice” and click Yes.
c)
[[Optional content]]
If you would like to see a time series visualization of how global land cover has changed from 1992 – 2020, go to Catalog pane > Portal > Living Atlas. Search for “Global Land Cover 1992-2020”. When you have located the imagery layer, right-click on it and Add to Current Map.
When you select the Global Land Cover raster in your Contents pane, a new tab appears along the top: “Time”. The software recognizes this as a time series raster dataset. In the “Current Time” group, set the Start as 1/1/1992 and the End as 1/1/2020. With these parameters set, zoom in to any location in the world (Dubai, UAE is an interesting one!) and hit the Play button. Note that red pixels indicate urban areas, which have increased worldwide since 1992. What types of land cover are likely being lost in this transition?
This is not the raster that we are going to be working with for EX7, this is simply
to allow you to explore the visualization of time series rasters because they are interesting. After you are done exploring global landcover change 1992 – 2020, go ahead and turn this layer off. [[End optional content]]
d. Returning to our landcover_2019 raster, when you added it to your map, you may have noticed that the land cover categories are not labeled. Instead, you have a continuous grayscale display of cell values ranging from 10 – 210.
The process that was used to extract the landcover_2019 raster did not bring with it the symbology for the global data set. To reset the symbology for these numeric categories of land cover, we will use the .lyr file in your EX7_Data folder.
e)
In the Contents pane, right-click on the landcover_2019 layer > Symbology. In the top right corner, click on the 3 horizontal bars (hamburger menu) and select “Import From Layer File”. Navigate to your EX7_Data folder and select the “ESACCI-LEMapsColorLegend.lyr” file that you downloaded. f)
Note the colorful change in your map! The raster’s values are now set to specific numeric landcover classes with integer values rather than a continuous grayscale. The range of color-coded numeric values (labels) each represent a land cover type. ●
Briefly refer to the ESACCI-LC-Legend.xls that you downloaded earlier (you can open it from Windows File Explorer) to understand what kind of land cover each numeric value represents. In our case, the land covers listed below are considered acceptable
for hosting a refugee camp. a.
40: Mosaic natural vegetation
b.
50-90: Tree Cover
c.
100: Mosaic tree and shrub cover
d.
110: Mosaic herbaceous cover
e.
120-122: Shrubland
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f.
130: Grasslands
g.
140: Lichens and mosses
h.
150: Sparse vegetation
i.
151: Sparse tree
j.
152: Sparse shrub
k.
153: Sparse herbaceous cover In other words, pixels with values ranging between 40-153 should be given a value of “1” (acceptable for refugee camp siting).
f. Open the Raster Calculator tool again. This time, we have a range of values to consider (rather than just one, as we had when making a binary slope raster) so we have to create a compound equation with two calculations in parentheses, joined by
a Boolean “&” operator. Input EXACTLY this expression:
(“landcover_2019” >= 40) & (“landcover_2019” <= 153)
Your output raster should be named “landcover_reclass” within your EX7 geodatabase. Verify that the expression is accurate and click Run.
Personal knowledge check: What is this equation saying, in plain speech?
TIP
: Remember to use the buttons in the Raster Calculator window to input the names of features in your equation instead of typing to reduce error risk. Make sure you put a space between each part of your equation. If you would like more
information on the various Map Algebra Operators, see https://pro.arcgis.com/en/pro-app/latest/arcpy/spatial-analyst/an-overview-of-
the-map-algebra-operators.htm
We now have our final binary layer (0/1) needed to determine our acceptable potential refugee camp siting. To stay organized, uncheck all the layers you are not using and/or minimize them so you cannot see their symbology in Contents.
Reminder: save your project!
Deliverable 5: Spatial extent
is the smallest rectangular boundary containing each dataset. It is also one of the important properties related to the spatial
resolution
(X and Y cell size) of raster data. You can find this information in the Properties for each layer. For each of the three binary rasters you created, what is the spatial extent and resolution? Round to the nearest whole number. Use this table to answer this deliverable.
Binary raster Top
Bottom
Left
Right
Resolution
Syria buffer
<10% Slope
Landcover
9.
Mathematically add our classified buffer, slope, and land cover rasters together a)
At this stage, we have three separate raster data layers, each of which contains cells values of either “1” (suitable) or “0” (not suitable/no data). Now we can assemble these layers together to answer our ultimate spatial question: where are appropriate places to build refugee camps?
b)
Using the Raster Calculator again, mathematically add
(use the “+”) together these three data layers (you shouldn’t need to type anything):
Layer1 + Layer2 + Layer3
Layer1 should be your slope raster - “
border_slope_class
”
Layer2 is your reclassification of the buffer around Syria’s border - “Syria_border_100km_buffer_PolygonToRaster”,
Finally, Layer3 is your new land cover layer - “
landcover_reclass
”
TIP
: Again, use the listed files and buttons in the Raster Calculator window to compose your equation. Make sure you put a space between each part of your equation. If you would like more information on the various Map Algebra Operators, see https://pro.arcgis.com/en/pro-app/latest/arcpy/spatial-analyst/an-overview-of-
the-map-algebra-operators.htm
Name your output raster “
criteria_3
” in your EX7 geodatabase and click Run.
c)
After running the calculation, a new raster is added to your map. This raster has three different output values. Cells with a value of “3” indicate locations that meet all three of our criteria. To isolate only these pixels, open the tool Reclassify (Spatial Analyst Tools)
. The Input raster is “criteria_3”, of course. Change the New Values
for cells with Old Values
of 1 and 2 to “NODATA” – we will be ignoring them because they don’t meet all three criteria. Name the Output raster “
potential_3
” and ensure it’s in your EX7 geodatabase. IMPORTANT: Double-check that the New values are what they should be! You have to hit the Enter
key after inputting each one, or sometimes they don’t take. d)
Click Run.
Deliverable 6: a. What is the spatial extent and resolution of the output map “potential_3”?
Top
Bottom
Left
Right
Resolution
Potential_3
b. Which of the three binary input layers dictate (i.e. limit) the top, bottom, left, and right extents of the potential_3 layer? (Could be a different answer for each one).
Hint
: You can change the symbology to see the rectangle boundary of each raster and then turn
each layer on / off to visually explore their spatial extents. 10. Finding viable sites in Turkey
a.
We have one more step to complete: trimming away all sites outside of Turkey. Open the geoprocessing tool Clip Raster (Data Management Tools)
. Clip the “
potential_3
” raster layer by the Output Extent of the Turkish border.
But wait, we don’t have a file for the Turkish border! How can we obtain a polygon that represents the boundary of Turkey? Think back to how you got a boundary polygon for Syria in step 6c… b.
Once you’ve got the Turkish boundary polygon, go back to the Clip Raster tool. Make sure you have specified the Turkish border to be your Output Extent. Name the output raster dataset “
potential_sites_Turkey
” and confirm it’s in the EX7 geodatabase. Below this, there is a checkbox to “Use Input Features for Clipping Geometry” – it’s very important you check this box so that the actual border of Turkey drives our clip raster process! Click Run. NOTE: Sometimes, for reasons we are trying to figure out, the new layer will refuse to be named potential_sites_Turkey and will be named potential_3 instead, so it looks like it just copied potential_3, but it didn’t. You can manually rename the layer in the Contents pane.
TIP:
To easily confirm that it worked, uncheck all layers except for potential_3 and potential_sites_Turkey. Uncheck the visibility for potential_3 off and on. Your map should look similar to this:
Note that there are no sites in Iraq; just Turkey.
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Reminder: save your project!
Deliverable 7: Open the layer’s attribute table and note that all its pixels have values of 1. a. How many pixels remain in this clipped output? b. How much land area is viable for refugee camp siting? Hint
: Use your answer from 7a and the resolution you found in question 6a plus your own multiplication skills. Note that 1km^2 = 1000m x 1000m; it’s a two-dimensional conversion that may be easier to do if you convert meters to kilometers first.
11.
A refugee camp needs a minimum amount of space, and some of these pixels are all alone, so they wouldn’t work (too small of a space). Let’s find out how many distinct refugee camps could be found in Turkey if each camp needs 100 km
2
minimum in area. a)
This question is easiest to answer if we convert the raster layer to polygons. With
the raster, we can’t single out certain groups of cells, but using polygons, we can see how much area is in each group of adjacent selected cells.
b)
Open the Geoprocessing tool Raster to Polygon (Conversion Tools)
. Your input should be the “potential_sites_Turkey” layer. Name the output something suitable, like, “sites_Turkey_poly”. Uncheck “simplify polygons” and click Run to create your new polygon feature class.
Curious? More about how this tool works:
https://pro.arcgis.com/en/pro-app/latest/tool-reference/conversion/raster-to-
polygon.htm
c)
Now we will use Select to pick out only the polygons that fit our criteria and are larger than 100km
2
. Find Select (Analysis Tools)
in the geoprocessing toolbox. As the Input Features, use the feature class that you just created. Name the output something distinctive. Add two expressions: one to select for gridcode (value 3) and one to select for area (Shape_Area) greater than or equal to 100,000,000 (one hundred million) square meters.
Personal knowledge check
: Why are we using that number?
d)
Run the tool. This will create a new feature class with only suitable polygons of the appropriate size. Uncheck all layers except this new one to see if it worked!
e)
Open the attribute table of this new feature class and check out how many polygons there are in the feature class (there should only be a few), and what kinds of areas they have. Some of these areas might have enough room for multiple 100km
2
refugee camps.
f)
For each of the polygons, divide the Shape_Area by 100 km
2
converted to the units of the projection (meters). You can do this by adding another field called Camp_Capacity and using the field calculator (shown below), or you can do the division by hand.
Round the values down
to ignore remainders of the division (i.e. a shape that is 289 km
2
would have room for 2 camps, not 2.89 or 3 camps.) Again, you can type
this in a new field, or just do it on a sheet of paper.
Deliverable 8: Add up the potential number of camps all the polygons could contain.
If each refugee camp requires 100 km
2
, how many distinct refugee camps could be built in total? Deliverable 9: What other siting criteria do you think might be important in considering acceptable locations? Hint
: You may want to change your basemap to Streets and to Imagery with labels so that you can examine other parameters that may be important in siting camps. Deliverable 10: Looking at the final result, which of the three types of input seemed to ‘drive’ the location of these viable sites (i.e, which input layer seems to be the most important)? Why do you think this is? Deliverable 11: Please make a final map layout showing acceptable camp locations in Turkey (cells with values of 3) overlaid atop this driving layer from Deliverable 10 (the layer that you deem the most important). Export this as a PNG file and include in your Word document. Remember to focus on the cartographic principles of good map design in creating your map: include a North arrow, scale bar, legend, title, etc.
Deliverable 12: For the entire data processing of this exercise, construct a workflow diagram, using the Geoprocessing history and Model Builder, for each section’s inputs, tools, and outputs, clearly identifying the data input, output and any linkage between outputs of one tool becoming the inputs to another tool. Model Builder is located in the Analysis tab, Geoprocessing group:
Note
: Refer back to the information that was provided in EX 6 for information on how to create a workflow diagram using Model Builder. The Geoprocessing history is accessible from the Analysis tab, then click on the History icon to open the Geoprocessing History pane that will help guide you through the creation of a Model. Take a screenshot
of the model you developed
that outlines the steps you have taken in this exercise and include it here.
Congratulations! You have finished EX7!
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