May 16, 2017

Lab 4

Introduction: The question that was decidedly to pursue in this lab was "What is or are the safest places to hike in Wisconsin". The main objective is to find a place in a National Forests  in which if someone were to get injured hiking help would be most able to get to them and save them. The secondary objective was to avoid places with records of fire in these forests. This Map would most likely be used by beginner hikers whom are cautious, or older hikers who are at a higher risk of injury.

Data Sources: In order to answer this question one needs lots of general information on Wisconsin. Most the information needed was taken from the Wisconsin DNR database, a database linkable through ArcMap and ESRI. The rest was found within the information provided by course. The data was three years old which was somewhat concerning, but the largest data concern was the shear amount of data provided for the question being asked, as there was little issue finding the required information. There was so much data in some of the features that the computer was slowing down and becoming difficult to use.

Methods: In order to answer this question a number of methods were employed. First all of the appropriate feature classes were added to the map, including a map of Wisconsin. Then all of the data sets were queried and new feature classes were created to ensure that all displayed data was within the border of Wisconsin. After this a series of buffers were created around hospitals, roads, and recorded locations of fires. After the area around fire areas was removed using the Erase tool the remaining buffers were intersected with the National Forests to find a safe location in which to hike. The areas that all three buffers intersected were such places.



Results: The results of this question were actually quite surprising. There were a number of large areas that fit the criteria of safety that was required. All the areas were fairly far north, and were 10km away from any recorded fire, within 10 km of major roads so help can get there quickly, and finally all locations are within 25km of a hospital.
Evaluations: I enjoyed the project as it shows me I can make my own maps interesting to me which gets me excited for future GIS classes and potential jobs. Additionally I found that if I were to do it again I would likely choose an even more complicated question as it would be more fun to create the map and the end result would be more satisfying. My only challenges were with what order to use various tools. Because some of the feature classes were big if I did something in an odd order it would slow everything down. So I would avoid that.



May 8, 2017

Lab 3
Goal:
The goal of this lab was to teach the ability to use a series of geoprocessing tools in ArcGIS in order to determine suitable habitat for bears in Marquette, Michigan.

Background:
The purpose of this exercise is to create a map of suitable bear habitat in Marquette, Michigan using a number of geoprocessing tools.

Methods:
The first step was importing the study set of bears.  The XY coordinates of the bears were in an Excel spreadsheet that needed to be imported to ArcGIS.  In order to bring the coordinates into ArcGIS, they had to be imported as an XY event theme.  The issue was that with event themes there was no ObjectID field.  Making it impossible to do nearly anything with the data.  Because the data needs to be manipulated, the data was exported into a feature class and then re-imported into the map. The second step was locating the best bear habitat in Marquette County.  The first step for this was to determining what kind of land cover the bears were frequently found. This was done by summarizing the table by minor type. The top three habitat types were Mixed Forest Land, Forested Wetlands, and Evergreen Forest Land. The second step to do this was to create a buffer of 500 meters around the streams feature class, and then intersect it with the bear habitat locations.  The pieces where bears were then cleaned up using the dissolve tool. The third and final step was to find the best bear habitat that did not fall into any area 5km from urban or built up areas. The Urban and Built Up major type was selected, turned into a separate feature class, and then buffered with a distance of 5 kilometers. To finish, the erase tool was used to erase the DNR land from this buffered zone.

Results:
The results show that there are a number of different DNR management areas, and that they center around areas with a high concentration of steams, as that is where the most bears seem to be found.

Figures:


Sources:
"GIS Open Data." State of Michigan Coat of Arms. N.p., n.d. Web. 09 May 2017.

Information, Michigan Center for Geographic. "Michigan 1992 NLCD Shapefile by County." Michigan Center for Geographic Information, 01 Nov. 2002. Web. 09 May 2017

Resources, Michigan Department of Natural. "Wildlife_mgmt_units." DNR. Michigan Department of Natural Resources. Forest, Mineral and Fire Management Division. Natural Resource Information Services., 01 Aug. 2001. Web. 09 May 2017.

Center for Shared Solutions and Technology Partnerships. "Michigan Geographic Framework: Marquette County." Center for Shared Solutions and Technology Partnerships, 01 June 2014. Web. 09 May 2017

Apr 9, 2017

Lab 2

Introduction: The goal of this lab was to gain an understanding of how to import information from the internet into ArcGIS and use it, as well as how to publish our work from ArcGIS and ArcGIS Online.

Methods:  In this lab a number of skills were developed. From Importing information, to using that information in a map, as well as how to share and publish that data. This was done by first going to the US Census Bureau's Fact Finder Website and retrieving the population information required on Wisconsin. This was done by setting various parameters in the site and narrowing down the search to more easily access the desired information. After the data was retrieved, and the data imported into the ArcGIS software a blank ArcMap was opened and the tabular as well as spatial data was added. From here data tables were merged to allow for the visual spatial representation of population in Wisconsin. After forming this map further data on Wisconsin was pulled from the Census Bureau's website and in a similar fashion added to a separate map in a separate data frame. Both maps were then improved and finished by adding legends, scales, north arrows, etc... creating a cartographically pleasing layout. After this was completed the map was saved and a new goal was introduced. The original map was copied into a new document and changed to remove the second map and be properly formatted. After ArcGIS Online was signed into and a series of steps including labels, descriptions, and tags were added, the map was analyzed for errors, the map was then published to UW-Eau Claire – Geography and Anthropology. The final step was create a web map from the feature service. In a web browser ArcGIS the UWEC enterprise was signed into and this opened up the UWEC Geography & Anthropology ArcGIS Online account. After this the shared map from before is reconfigured through a series of menus and tools. Finally after reformatted, with popups added, the new map is then saved and shared.

Results: The results of this lab are that the created map was shared in two places in two different forms for different purposes. The patterns on the maps show a few things. The general population WI map shows that the highest concentration of people is in the south east of the state. The rural population map shows how rural populations are clustered away from the large city clusters, but still represented in the other map.

Sources:
Data Access and Dissemination Systems (DADS). "American FactFinder - Search." American FactFinder - Search. N.p., 05 Oct. 2010. Web. 09 Apr. 2017.            

ArcGIScom News. N.p., n.d. Web. 09 Apr. 2017.       

                

Mar 12, 2017

Lab 1

Goals and Background: The context of this lab is that I am put in the shoes of an intern working at Clear Vision Eau Claire. I have been tasked with helping to produce a series of basemaps with GIS programs for the Confluence Project in downtown Eau-Claire, using a variety factors and features such as voting districts and zoning codes to produce the maps using ArcMap.
The goals of this project are to become familiar with a series civil spatial data sets and to prepare base maps for the Eau Claire Confluence Project showing different data sets and visual outputs. 



Methods: The first step in the lab exercise was to use ArcCatalog to go over the features located in the two Lab 1 Geodatabases. The first Geodatabase for Eau Claire County and second for the city of Eau Claire.  After looking over and analyzing the various features within each of the Geodatabases, ArcMap was then opened and used to create a new Geodatabase in which a feature class was added with a baseman of the location of the proposed site for the Confluence Project. The parcel feature of the Confluence project was added through the editing toolbar. After the Confluence Project feature was made, time was spent looking at the Public Land Survey System or PLSS for short. The Geodatabases contained PLSS data like townships, sections, and quarter-quarter sections among other things. Adding various sections and quarter sections, the Confluence Site was located in its most specific section, making it easy to locate and use later as well as gave an idea of how PLSS can be used.The next objective was the writing of a legal description for the Confluence Project sites. The description included the owner of the land and an in-depth description of the site including its specific PLSS location and the size of the site. The information needed for the legal description was obtained through the City of Eau Claire's website by creating a search of the PLSS information that we had found associated with the Confluence Project. Finally, six individual maps were created in ArcMap in order to visualize and show the detail a series of different ways that were relevant to the Clear Vision Eau Claire Confluence Project. The six different ArcMap maps showed Census Boundaries, Public Land Survey System, Civil Divisions, Voting Districts, Zoning Data, and City of Eau Claire Parcels in distinct yet comprehendible and informational ways. Each of the maps of the proposed site for the Confluence Project has the Confluence Project as a separate stand out feature to give perspective on where it is on each map as well as how it relates to and interacts with the other data.  Finishing off the map artistic changes were made to the various maps in order to make them more visually pleasing, a legend and scale bar were added for ease of use and understandability as well they are part of any well rounded and constructed map. 

Figure 1


Sources:

https://www.youtube.com/watch?v=p5UZYebNqJU&feature=youtu.be

Christhupy. "Lab 1 Example." YouTube. YouTube, 17 June 2013. Web. 12 Mar. 2017.

http://www.sco.wisc.edu/plss/legal-descriptions.html

Hemstead, Brenda. "PLSS - Legal Descriptions | PLSS." PLSS - Legal Descriptions | PLSS. N.p., n.d. Web. 12 Mar. 2017.

https://www2.uwec.edu/News/more/confluenceprojectFAQs.htm

"Frequently Asked Questions: The Confluence Project." BluGold News. N.p., n.d. Web. 11 Mar. 2017. 

http://communityfortheconfluence.org

"You Have a Role to Play in Building Eau Claire's Future." Community for the Confluence. N.p., n.d. Web. 12 Mar. 2017.

http://www.eauclairewi.gov/departments/public-works/engineering/mapping-services

"Mapping Services." City of Eau Claire, Wisconsin : Mapping Services. N.p., n.d. Web. 12 Mar. 2017.