Wednesday, December 11, 2013

GIS I: Lab 5 Mini-Final Project

                Where would be the most ideal location to build a new par 3 9-hole golf course in Outagamie County? Outagamie County already has ten golf courses, so it would be important to plan a course to be in a region of the county where there is not a course. Thus giving this new golf course its own new audience and not stealing business from other courses. In order to find a location for this new golf course I downloaded data off the GIS servers containing information about major roadways, city or town centers, previously built golf courses, and parks. For this lab I will only use park locations as suitable locations to build a golf course instead of available farm land or forestry land due to the fact of time and resources. For this project my intended audience would be the Park and Recreation departments for the cities of Outagamie County, or a private owner who is interested in building a new golf course. But because this golf course is going to be built on land already being used for parks it will have to be for the Park and Rec Departments.
                In order to answer my question on where to build a new 9-hole golf course in Outagamie County, I had to download multiple data sets.


The following paragraphs will work through the data flow model.

These data sets started with the United States and County data. From those two files I was able to export Outagamie County and begin to add additional material to the map for just Outagamie County rather than the whole country. Next I added Cities and Major Highways to the county data. Before adding any other data I created a buffer on both of these data sets. I created a five mile buffer around the cities and a one mile buffer around the major highways. I then intersected the two data sets to come up with the largest area possible for a new golf course to be built. I still have more data to add to the equation before finding the ideal location, but this first area gave me a rough idea on where I could put the course.




 The next step was to import the Recreation areas (the Wisconsin DNR has all golf courses listed under Recreation areas) and perform a query to select just the golf courses. After selecting just the golf courses I created a three mile buffer around them. This area was to inform whoever will be looking at the data that this is an area where not to build a golf course. My next step was to erase the data based on the county data. This then got me my second set of ideal locations (the second set did not take into account of the locations that the first set found, instead that will be incorporated into the third ideal location).




 The light green circles represent the three mile buffer around the golf courses, while the pink area represents any area not inside the three miles and therefore available land to use for the development of a new golf course. The next step I took was to intersect the first and second selected location areas and figure out where using both sets of data the next best location would be.




After intersect the two previous ideal locations, I have a much better understanding on where ideal land would be that is still within five miles of a city and one mile of a major highway, but is still three miles away from any other golf course. On the above image the light yellow/white color is all available area to build this new golf course, while the light blue is any area that does not fit all three categories. The next step was to insert the parks data. The park data will be intersected with the map above and any park that falls within the white area will be available to be selected.


 The available parks to be used in the project show up on the map above in a bright green color. The only down side of this data is that the data does not take into account with what is already in the park. The last step of my project was to create a query on the available parks to find out of the available locations which ones have an area greater than 0.2 square miles of available space to use. The results came up with two available parks that fit all the criteria. These two parks are Shiocton’s Lake Park and Appleton’s Memorial Park. They appear on the map below in a bright yellow color.


All data for this project was downloaded from ESRI servers or Wisconsin Department of Natural Resources servers.
                Working with this data I came across many issues with the data. The first issue I came across was when I imported the data set labeled golf courses only three came up. All three courses were along the US-41 Highway leaving everything but the Southeast corner available for a course. I overcame this issue by importing Recreation Areas and finding out they had ten golf courses in the county, which is a much better number to work with and they were all spread out. My next issue did not take much longer to come across and that was dealing with cities. Outagamie County only has a couple major cities, and those are the only ones which came up with the cities data set. To fix this problem I imported the places data set and performed a query to just get cities in Outagamie County, therefore giving me many more cities to work with.  My next issue I came across was not being able to plan for a course to be built on non-park land because the data for that was not available and would take a much longer time to manually find a location for a golf course. So I had to settle for just the use of the parks. The next issue I had to overcome was the parks not taking into account what was already on the park land. I know from my background knowledge that Appleton’s Memorial Park has an ice rink and many softball fields on it that many youth teams use, along with those they also use the hill in the park for the finish line of a 5k race and use the manmade lake in the park for firework shows. As for Shiocton’s Lake Park there is a manmade lake and beach there that contributes great amounts of revenue to the city as well as baseball fields where local teams play at. The last issue I came across was the not current data sets I worked with.

                My project came up with two ideal locations for a new 9-hole golf course



                Overall I was greatly impressed with this project because we were able to choose our own idea for the project and got to go anyway with it that we wanted. If I was able to change anything about this project I would probably change how much time we were given to do it. I think if we were given much more time we could go into much more detail and go out and get real data for the project. I know for my question I would be able go into land availability much deeper and maybe contact other people about land use, but that may be way too much to handle in GIS 1 and more for an actual job or research project. The only real challenges I came across was using the wrong tool and then having to restart that step.

Monday, December 2, 2013

Lab 4: Vector Analysis with ArcGIS

     The goal in lab 4 was to conduct a vector analysis with ArcGIS using multiple different geoprocessing tools to determine the most ideal place for bears to make into a new habitat for bears in the study area of Marquette County, Michigan.
     The purpose of this lab was to gain a better understanding of using various geoprocessing tools and how they are to be used in the proper way to figure out the problem at hand. We were given multiple sets of data, bear habitat, streams, land type, and the county data, and using our knowledge learned we had to apply multiple geoprocessing tools to figure out where the best place for the bears of Marquette County to be moved to.
     In lab 4 we followed a vague set of guidelines to help us conduct the project. The vagueness was to assure that we as students had a full grasp on the information at hand and would be able to use it in a real world scenario. After importing the county data, streams, and bear data we had to change the landcover feature so it could easily be seen which was what category. After that we conducted a summarize on the data to see which landcover areas had the most bears. These three areas were Evergreen Forests, Residential areas, and Lake regions. The next step was to create a 500 meter buffer, and dissolve, around the streams in Marquette County. About 72% of the bears live within the 500 meters of the stream, making it a very important component in finding a new habitat for the bears. The next step I did was intersect the data around the the streams with the top three bear landcover types and only have those areas selected with the areas around the streams. Next was to incorporate the data with DNR management locations and intersect them. Using the newly added DNR management data I intersected it with the likely areas of the bear habitats. The next step was to use the newly added DNR and landcover bear habitat data and eliminate any areas within 5 kilometers of a Urban or Built up land. Any area within the 5 kilometers of an urban or built up area was erased and not used in finding a new bear habitat. Lastly, after all that I had my ideal location. I then made it  a visually pleasing map with a scale, little picture of Michigan showing the highlighted county, a legend showing all that is on the map and finally the sources used.
    The results found in this lab were all ideal areas for bears is around water(due to the buffer) and away from any built up areas. Several bears live around the new ideal locations, but no so many live in the ideal regions.








Sources
Michigan Geographic Data Library
 Landcover is from USGS NLCD
  http://www.mcgi.state.mi.us/mgdl/nlcd/metadata/nlcdshp.html
 DNR management units
http://www.dnr.state.mi.us/spatialdatalibrary/metadata/wildlife_mgmt_units.htm
Streams from
 http://www.mcgi.state.mi.us/mgdl/framework/metadata/Marquette.html