Lab 4: Final Project

Introduction:

For this lab, you have to create and answer a spatial question by using the skills you've learned throughout the semester. The spatial question in this blog asks where is the best potential place to put a campground in Eau Claire county. You need to use at least three spatial layers feature classes and four tools. You can also pick one tool to perform a second time for it to count as the fourth.

Sources:



Data was found from the ESRI2013.DBO.USADATA database, and the Wisconsin DNR database.

Methods:

To obtain the best area for a campground in Eau Claire county you should find an area inside of a national park and a county forest as well as within 1 kilometer of a lake and 3 kilometers near a major road. The tools utilized to obtain those specific parameters are the buffer, dissolve, and intersect tools in order to find the most suitable area for a campground. 

Begin by clipping the Parks, Forests, Water Features, and Major Roads in Eau Claire. Next create a 1 km buffer for all the lakes, and dissolved them to get one polygon. After that make a 3 km buffer for all major roads, and dissolved that to get one polygon as well. Then I intersected the Lake buffer, the major roads buffer, the parks feature class, and the forests feature class which gives the areas you could put camp grounds.

Results:

Figure 1 below shows my flow chart of the tools and functions performed to get my potential campgrounds.

Figure 1 shows the Flow Chart for the Project.

Figure 2 below shows that map that I created showing where the best locations are for potential campgrounds. Those areas are represented in yellow.

Figure 2 shows the map in which I will propose to the audience

Evaluation:

My overall impression for this project was that it is a great way to show the Professor what we have learned. I liked that it allowed us to choose our own spatial question in which all steps were done on our own. I really wouldn’t change the project because I think it has a great layout. The challenges I faced were trying to find all the data I need from ArcGIS, after that the rest of the project flew by.

Lab 3: Vector Anaylsis with ArcGIS

Goals and Background:

The Goal of this lab is to use different geoprocessing tools for vector analyisis in ArcGIS to find suitable habitats for bears in the study area of Marquette County, Michigan. This lab report contains a final map layout and a data flow model. There are eight objectives listed below:

1. To map a GPS MS Excel file of black bear locations in the study area, central Marquette County, Michigan
2. To determine the forest types where black bears are found in the study area based on GPS locations of black bears.
3. To determine if bears are found near streams.
4. To find suitable bear habitat based on two criteria.
5. To find all areas of suitable bear habitat within areas managed by the Michigan DNR.
6. To eliminate areas near urban or built up lands.
7. To generate a digital data flow model of the workflow and cartographic output.
8. Use some python.

Methods:

Objective 1:

For this objective we unzip the marquette_bear_study file. Then add the bear_locations_geog% to the make, so you can add it as an event theme. Once its in ArcMap, export the data and save it in your lab 3 folder.

Objective 2:

In this objective you add all feature classes in the bear_management_area feature dataset, and change make the landcover symbology a unique color map for the "minor type" field. Now intersect bear_locations and landcover renaming the new feature class bear_cover. Next you summarize the Minor_type field with the FID_bear_locations (Max) and the Area (Max) statistics. Then open the attribute table where you will find the top 3 land covers with the most bears.

Objective 3:

This objective requires you to find out the how many bears are within 500 meters of a stream. In order to figure this out create a query by location. Create a buffer with a buffer with streams and a distance of 500 meters than dissolve the new layer to get one individual polygon. Add bear_locations to target layers, and use the dissolved stream buffer layer as your source layer. You will find that 49/68 (72 percent) of bears are located within 500 meters of streams. Note that the distance of streams is definitely an important habitat characteristic.

Objective 4:

For this objective you need to find suitable areas of bear habitat based on your research. Use the intersect tool, and input for the dissolved stream buffer layer and the suitable land cover top layer. Then dissolve the new layer to clean things up a bit.

Objective 5:

In order to make recommendations to the Michigan DNR for a bear management plan you need to find a bear habitat located in their management lands. Bring in the dnr_mgmt layer from the political boundaries dataset. Again use the intersection with the suitable land area near streams layer and the dnr_mgmt layer. Dissolve the internal boundaries for a better look.


Objective 6:

For this objective you need to find bear management areas that are away from Urban or Built up land. You need to exclude all areas that are within 5 kms of Urban or Built up lands in a 3 step process. First create a query by attribute to select Urban or Built up land then make it it's own layer. Second buffer urban or built up land with a distance of 5 km, and dissolve the boundaries when you're done to get a single polygon. Third and last, use the erase tool to get all of the suitable DNR managed land areas outside of 5 kms from urban or built up land.


Objective 7:

In this Objective you will create a cartographically pleasing data flow model of your workflow from all the steps/tools used as well as a cartographically pleasing map.

Objective 8:

In the final Objective you will work with Python Code.

Results:

Objective 2:

The three most populous land types with bears is listed below:

1) Mixed Forest Land - 31 bears
2) Forested Wetlands - 17 bears
3) Evergreen Forest Land - 14 bears

Objective 7: 

Your Suitable Bear Habitats in Marquette County, MI should like like Figure 1 below:

Figure 1 is the Final map you are proposing to the DNR for suitable bear habitats. It includes the location of the bears, streams, the three most populous bear land covers, and the DNR managed land that is more than 5 km from urban or Built-up land.

Objective 8:

Your Data Flow Model should look like Figure 2 below:

Figure 2 is a Data Flow Chart of all the functions performed to reach the final product

Your Python Code should look Figure 3 below:

Figure 3 shows the Python Code you should have done to introduce yourself to the Python tool

Sources:


Data Management:

The data for this lab is downloaded from the lab3.zip file.

Data Sources: 

State of Michigan open GIS data.

USGS NLCD

DNR Management Unit