Geog 335 Lab Four project

G.I.S 1 Mini Project
“Where to Ice Fishing In Forest County Wisconsin”
Intro:
The purpose of this lab was for the student to create a geographic question that could be solved using the G.I.S skills they acquired over the semester. The question needed to be answered using at least three different special tools a total of four times. The question I choose was where would be the best lake to go ice fishing in Forest County, Wisconsin. The inspiration for this project comes from an ice fishing trip my father and I take every year. The tools used in this project include Clip, Buffer, Intersect and Erase.
Methods:
I based my question on three main criteria. The first of these was that the lake needed to be in Forest County, as that is where I go fishing every year. To map this I took a Wisconsin counties feature class from the Wisconsin DNR geodatabase and performed an attribute query to select Forest County and make a separate layer. I then intersected the county outline with a hydrology feature class obtained from the same database. The result was a feature class showing the outline of the county and all waterbodies within it. My second criteria was that lake should not any smaller than 50,000 square meters. Ice Fishing is very popular in northern Wisconsin and lakes can quickly become over crowed. To determine which lakes were too small I performed an attribute query to isolate them and then performed an erase. My third and final criteria is that the lake should be within a quarter mile walking distance from the nearest road. It is often difficult to get vehicles onto the lake and is not possible when the ice is too thin. To find which lakes were close to roads I took a road feature class for the entire state from the DNR geodatabase and selected all roads within Forest County. I then clipped the selected roads. I performed a buffer of a quarter mile on the roads clip and performed a spatial query to select lakes that intersected the buffer. The remaining lakes were the ones deemed best suitable for ice fishing.
Data Sources and Results:
The data for this map was obtained from the Wisconsin DNR geodatabase. The tools were performed using E.S.R.I ArcMap software. Also included is a Dataflow model of my work showing how I got to my results.

Lab 3 Report

Geography 335 Lab 3 Report

Ian Godin

Objective: The objective of this lab was to use various geoprocessing tools to determine the locations of suitable bear habitat within a study area in Marquette County Michigan. Using data that showed the locations of the bears within the study area, geoprocessing tools were used to narrow down the preferred habitat of the bears and locate bear habitat that is in DNR management areas.

The first objective for this map was to determine what would make suitable bear habitat. Using the locations of bears and a shape file of land cover types, an intersect was performed to show which type of land cover the bears preferred. These include mixed forest land, forested wetlands and evergreen forest land. These layers were selected in a query and a separate layer was made from the selection Based on information that bears prefer to live in habitats within 500 meters of a stream or river, a buffer was performed on the streams feature class. This buffer result was then intersected with the land cover selection to further narrow down bear habitats.

                The second part of the assignment asked to locate suitable bear habitat that was within a DNR management zone and at least five kilometers from urban or built up land. First, an intersect was performed using shape files that contained the boundaries of the study area and of DNR managed lands. The result was a map of DNR managed lands within the study area. This result was intersected again with the previously made feature class showing the best bear habitats to create a map showing the best bear habitats within DNR managed areas. In order to determine which habitats were at least 5 km away from urban and built up areas, an attribute query was performed on the land cover feature class to select urban land. A buffer was then performed on this selection. Finally, an erase was performed on the buffer to remove these areas from the map. The final map is shown below.

   

          

Also shown is a data flow model to outline the steps I took to create this map.

               

  This lab also introduced us to Python coding. Using simple code, I performed a buffer analysis of the streams feature class. The code is shown below.

  Overall I enjoyed this lab due to the way it allowed us to us G.I.S in a real world scenario. While the workbook teaches how to use the different components of G.I.S, this lab had us perform tasks that one would actually perform in a workplace setting. 

Lab 2 Report.

Geography 335 GIS Lab 2 Report

Ian Godin

Overview: 

The purpose of this lab was to learn how to gather census data from the internet and map it using ESRI ArcMap. The map was then published to ArcGIS online.

Methods:

The data for the map was collected from the United States Census Bureau using the American FactFinder tool. The data that was used was from 2010 Summary File 1. The data collected for this lab was the population of Wisconsin at the county level and was downloaded in the form of an Excel spreadsheet. This spreadsheet needed to be edited in order to be used in ArcMap. A shapefile of the Wisconsin counties was also downloaded.

In ArcMap, the attribute table for the shapefile was joined to the census data attribute table. This allowed the census data to be mapped as a variable on the shapefile. The data was mapped as a graduated colors map where a darker color represented a higher population. A second data frame was added to the map and the same process was followed for the second map however that data being mapped was the total number of housing units per county.   The final map was then formatted in ArcMap and published to ArcGIS online. 

Results: 

The final map shows two different demographic totals at the county level. The first map shows total population and the second shows the total number of housing units.  A common pattern is that there are higher numbers of housing units and higher population in counties that contain a major city, such as Milwaukee County. This is not always the case, as certain counties in the north woods region of the state have low population but high numbers of housing. This is probably due to individuals who own vacation homes in this part of the state. 

Overall I enjoyed this assignment and feel that the information I learned from it will be very beneficial. In another course the professor told us that employers will want to look for individuals who are able to gather and work with free data from the census bureau. Through the process of this lab I now have a better understanding of the data gathering process and now know how to access a wide variety of data that can be used in my future maps.

Geog. 335 Lab One Report

Ian Godin

GIS 1

Lab One report

Introduction:

 The purpose of this lab was to act as an intern for Clear Vision Eau Claire and develop a basic report along with base maps that contain information relevant to the ongoing confluence project in downtown Eau Claire. The maps were created using ESRI ArcMap software.

Methods:

A total of seven maps were created in this project, each of the same relative area, however each map displayed different information. The first of these maps was a map showing the parcels of the proposed site. A shapefile containing the locations of all the land parcels in the city of Eau Claire was overlaid on top of an imagery base map. The parcels that would be purchased for the confluence project were then highlighted to stand out from the surrounding area. These highlighted parcels were then converted into their own feature class.

            The second map displays the population per square mile of the area surrounding the proposed project site in relation to the cities census tracts. A shape file of the census tracts was overlaid on top of an imagery base map and the map was symbolized to show population. This information was then normalized to show population per square mile.

            The third map shows location of the proposed project site on the PLSS grid system and displays the PLSS legal description of the site. A polygon feature class showing the PLSS grid network was overlaid on top of an imagery base map. The legal description of the site area was selected from the attribute table using a query expression and the area was then highlighted on the map. The map was then labeled to display the legal description.

            The fourth map shows the location of the project site in relation to the rest of Eau Claire County. A feature class showing the civil divisions throughout the county was overlaid on top of an imagery base map. The feature class showing the proposed site which was created in map one was used again to show the location of the site in relation to the rest of the county.

            The fifth map shows an expanded view of the land parcels for the city of Eau Claire and highlights the location of the proposed project within the city. The same shapefile from map one was overlaid on top of an imagery base map and a graphic marker was added to show the sites location.

            The sixth map shows the zoning of the city of Eau Claire. A feature class showing the zoning areas was added and like areas were grouped together and each represented with a color symbol. A legend was created off to the side to define each area. Again a graphic marker was used to show the site location of the site and what zoning classification it would fall under.

            The seventh and final map displays the voting districts for the city of Eau Claire. This information is important as the confluence project includes student housing and the voting district for these students would need to be determined. This map consists of a feature class showing the boundaries of the cities voting districts. A graphic marker was used to show which district the project site would be in.

Results:

            The results of this report are seven base maps each displaying different information about the same area. Each map uses a graphic marker to show the location of the project site in relation to the information being mapped. These maps each indicate that the proposed project site is in an excellent location as it is centrally located in downtown in an area of high population that would also pull in visitors from the surrounding residential areas. Additionally, the site has potential to draw in visitors from the other townships within Eau Claire County. The fact that the site is located in the center of a commercial district also means that visitors will potentially spend money at other local businesses, thus stimulating the economy and benefiting the local community.

Source: This report was generated using information from the both the City of Eau Claire and Eau Claire County 2013 Geodatabases.