LAB 4

LAB 4
Jeff Hessburg

The first thing that needs to be completed is creating a file geodatabase. To do this, Create a lab 4 folder, then open ArcCatalog, and connect to that folder. then right click that folder and click: new file geodatabase.
The next step is to select a county of interest and ask a spatial question about it, then solve the problem. For this particular lab, Multnomah County in Oregon was selected.
To create a question, a made up scenario was created:
A family has recently moved to Mulnomah County to live closer to family. They have children and are deciding which school to put them in. (The data doesn't provide type of school; eg: elementary or middle school, so pretend that all schools apply for any age). Concerned for safty, the family wants the school to be close to a hospital. They also like to go fishing before class some days, so they want to be close to a river. The family needs work, and most jobs are in cities, so they prefer the school to be close to a city. Also for the children, they'd like it if the school was close to a park. Considering all of the requirements, what schools are best for the family.

To answer the question, all of the following questions must be answered:
What schools in Multnomah County are
-Within 1 mile of a river
-Within 1 mile of a hospital
-Within 1 mile of a cities
-Within 1 mile of a park
Then finally what schools apply to all of these requirements.

To answer this question, the Oregon geodatabase from the mgis data for the MAGs can be used. The feature datasets from the geodatabase needed are: counties, hospitals, rivers, cities, and parks.
The Oregon data provides data about every county in the state. The only data needed to answer the question is in Multnomah County, so all data not in Multnomah County must be removed.

To do this first Multnomah County must be created in its own layer.
Open attribute table > Select by attributes > enter expression: NAME = 'Mulnomah'
Then exit the attribute table > Right click counties > Selection > Create Layer from selected features
Now the only county needed is its own layer, it can be renamed to Mulnomah county, and the counties layer can be removed. The Mulnomah County layer then needs to be exported into the LAB 4 geodtabase created earlier.

Now, add the hospital, rivers, cities, and parks layers to the map. They need to be clipped to just Mulnomah county and exported to the LAB 4 geodatabase. To do this is the same process for every feature data set:
ArcToolbox > Analysis tools > Clip > Input Features: hospitals, rivers, cities, parks, or schools > Clip features > Mulnomah County > Output feature class > save in LAB 4 geodtabase.

Now all of the data that is needed to answer the question is ready.
First find out which schools are within one mile of a river. To do this create a 1 mile buffer around the river layer then dissolve the buffer then intersect the schools to see which are within 1 mile of a river.
ArcToolbox > Analysis Tools > Proximity > buffer > input river > distance 1 mile > click OK > ArcToolbox > Data Management Tools > Generalization > Dissolve > input River Buffer > click OK > ArcToolbox >Analysis Tools > Overlay > Intersect > input schools and the 1 mile river buffer >save to LAB 4 geodatabase
The output is a new data set that includes all of the schools within 1 mile of a river

There are 41 schools that are within 1 mile of a river.

Next find out which schools are within 1 mile of a hospital. To do this follow the exact same steps that were used to find out the schools within 1 mile of a river

The output is a new data set that includes all of the schools within 1 mile of a hospital.

There are 77 schools that are within 1 mile of a hospital.

Next find out which schools are within 1 mile of a city. To do this follow the exact same steps that were used to find out the schools within 1 mile of a river and within one mile of a hospital.

The output is a new data set that includes all of the schools within 1 mile of a city.

There are 21 schools that are within 1 mile of a city.

Next find out which schools are within 1 mile of a park. To do this follow the exact same steps that were used to find out the schools within 1 mile of a river and within one mile of a hospital and within 1 mile of a city.

The output is a new data set that includes all of the schools within 1 mile of a park.

There are 66 schools within 1 mile of a park

Now it is time to fine out which schools fit all of the criteria: 

-Within 1 mile of a river
-Within 1 mile of a hospital
-Within 1 mile of a cities
-Within 1 miles of a park

To figure out which schools work, use the intersect tool and set the input features as all of the feature classes that were the results from the previous steps: schools within 1 mile of river, 1 mile of a hospital, 1 mile of a city, and 1 mile of a park.
The results are shown below along with a buffer of all of the features used earlier. It is now easy to visualize all of the schools that fit the criteria.

There are 4 schools that are within 1 mile of a river, 1 mile of a hospital, 1 mile of a city, and one mile of a park: Mulnomath College (historical), Lincoln High School, Cathedral School, and Couch School.
Next, turn it into a map by adding a legend, scale, north arrow, and a description.
Bellow is the final map.

Below is a complete data flow model of all of the steps used to create this map:

Since this was originally completed using three tools a fourth one needed to be used to fit the grade requirements.

the schools should also not be within 49.5 miles of a volcano. 

to do this: 

add volcano layer > create a 49.5 mile buffer  > then erase with the input:schools within 1mi of river, hospital, city, and park and erase as the volcano buffer. 

only 2 schools remain: Cathedral School and Couch School. 

The new data flow model is below:

The new map is below:

For this project the mgis data that was used in the MAGs was used.

The overall impression of this project was that it was very challenging and different from other projects done previously. The biggest challenge was creating a problem and figuring out which data to use. 

Sources:
The data used to complete this lab was used from the Oregon folder in the mgis data. This question did not requite downloading any online metadata. The data concerns can be the age and quality of data. Over time things change so if this question were to be answered with the most current data, the results may be different.