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.

LAB 3

Jeffrey Hessburg
Lab 3

Lab 3 has several objectives:
   The first objective is to map a GPS MS Excel file of black bear locations in the study area, central Marquette County, Michigan. To complete this objective, use arc help to search and learn how to add x,y coordinate data as a layer. Then add the x,y table of bear_locations_geo$ and set the x field to Point_x and the Y field to Point_Y. Make sure that the z field is left blank. Next the coordinate system needs to be edited and set to NAD 1983 HARN Michigan GeoRef (Meters). Once the tool runs. points will appear on the map as shown below. These points are the bear locations and needed to be exported into the lab3 geodatabase in order to complete objective one.

   The second objective is to determine the forest types where black bears are found in the study area based on GPS locations of black bears. To do this all of the data from the bear_management_area feature set must first be added. Next the intersect tool is used with the landcover layer and the bear_locations layer. This intersect creates a layer that show all of the bear locations and the type of land cover that each bear was in. The next thing that needs to be determined is how many bears were in each habitat. To do this, summarize tool Minor_type with FID_bear_locations maximum and area maximum. This shows the count of bears in each site.

    Objective 3 is to determine if bears are found within 500 meters of a stream.  To determine this, use the select by location tool. As the target layer use bear_cover and as the source layer use streams. Then, the spatial selection method for target layer feature can be set to: are within a distance of the source layer feature of 500 meters. 49 out of the 68 bears were within 500 meters of a stream. This is 72% of the bears. This means being close to streams is important for bears. Another way to complete this objective is to use the buffer tool to create a wider stream, then the intersect tool can be used to create a layer of bears that are within 500 m of stream.

      Objective four is to find suitable bear habitat based on two criteria: suitable land cover types and within 500 meters of a stream. Now the Dissolve tool must be used to create one large polygon around the streams. Now shown is a polygon where bear habitat is.

   Objective five is to find all areas of suitable bear habitat within areas managed by the Michigan DNR. First the DNR management lands layer must be added to the map. Then the intersect tool is used to intersect the dissolved 500 m stream buffer and the DNR management land.
Then dissolve tool to make all of the intersect one layer.

Step 6 is to eliminate areas near urban or built up lands from the map. To do this, use the select by attribute tool to select just urban or built up land. create a layer of just urban or built up land. then use the buffer tool to create a 5km buffer around this layer then use the dissolve tool to make the buffer one layer. last. use the erase tool to create an output that just shows what is outside of the buffer

Below is the final map. it shows where all of the bears were located, the streams, the bear habitat on DNR land, and the three most sutible land cover habitats.

   Objective seven is to generate a digital data flow model of the workflow. The circles are the input/outputs and the rectangles are the tools used. This was created using adobe illustrator.

The final thing needed to do is learn how to use python.
by clicking the tool and following the directions then entering the following codes.
>>> arcpy.Buffer_analysis("streams", "streams500m", "1 kilometer", "FULL", "Round", "ALL")
>>> arcpy.Intersect_analysis([streams_buf","suit_land"], "land_stream"




Sources: All of the data were downloaded from the State of Michigan Open GIS Data http://gis.michigan.opendata.arcgis.com/  Landcover is from USGS NLCD o http://www.mcgi.state.mi.us/mgdl/nlcd/metadata/nlcdshp.html  DNR management units  o http://www.dnr.state.mi.us/spatialdatalibrary/metadata/wildlife_mgmt_uni ts.htm  Streams from  o http://www.mcgi.state.mi.us/mgdl/framework/metadata/Marquette.html

LAB 2

 Jeff Hessburg

       The lab presented had several objectives. In order to reach each goal several things were needed to be learned, and steps needed to be accurately followed. Each goal and how they were accomplished, are listed below.
  The First thing that needed to be accomplished was downloading 2010 Census data (total population) from the US Census Bureau. To do this, go on the US Census Bureau website. Once on the website,  pick the appropriate geography needed to to represent what is desired. For this lab, the geography needed are all of the counties in Wisconsin. Then choose the right data set. For this lab the data needed is total population. Once this is downloaded, the excel table that comes with the zip file needs to be modified. There is an unnecessary row of labeling that should not be there. This must be removed so arcgis can read the table. Once the table is completed, it must be re-saved as a MS Excel file. 

        The second thing needed is to download a shapefile of the 2010 Census boundaries from the US Census Bureau. The shapefile needed is all of the counties in Wisconsin. This should be selected on the US Census Bureau website and then downloaded and unzipped. once unzipped there should be the proper shapefile of Wisconsin counties. This can be added in arc catalog and then added to the map.

        The third thing needed to do is join the downloaded data to the Census shapefile. Doing this will allow the user to create a map of population in Wisconsin counties. To join two tables, they must share a common field. In this case the common field is GEO_ID. Join the tables together then the fourth objective can be completed.

        Mapping the data is the fourth objective. It can not be be done right away because there is a missing field in the county shapefile. It must be created by adding a field and using the calculator to add the population data to this new field. 

         Objective 5 is to create another map of the Wisconsin counties, with different data variable that is not population. In order to do this the same steps as 1-4.

         Objective 6 is to display both of these separate maps on the same map document. To do this formatting is necessary, so both of the maps fit. Then basic map elements needed to be added such as a title, legend, and a north arrow.   The results are below. 

     This particular example compares total populating in Wisconsin by county and total housing units in Wisconsin by county. Things to notice are the results are nearly identical. Not surprisingly, there are similar numbers of housing as there are people.

        The final objective that needed accomplishing was to build a web map with one of the variables. To do this only one map was needed, so the total population was used, and housing units was removed. To upload the population map to arcgis online, the first thing needed to do is sign in to arcgis online though arc map. Once signed in, it is possible to share the map and upload it online. After this is completed, the next thing to do is login to arcgis online through a web browser and view the map that was uploaded. Once viewing the uploaded map, things can be configured and removed to display the necessary data desired. In this case, the only thing that needed to be displayed was population of the county and the county name. Everything else was removed.  Once everything looks correct, the map is saved and shared to whoever is desired. In this case it is the UW-Eau Claire-Geography and Anthropology department. 

Above is a screenshot of the page where edits and configurations can take place.

Above is a screenshot of how a user can interact with the created map. By clicking on a colored county, the county name and population of that county appears.

Above is a screenshot of the page that was created after editing the map. This page can be edited to add a description of the map, and a summary of the map creator.

    Sources:
    Data for the creation of this map came from the US Census Bureau 2010.
    ArcMap and ArcGIS online were used for the creation of these maps.