Project 7 GIS

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Dec 6, 2023

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Buffers: Project 7 Alternate: Network Analysis and Mobile GIS Steven McHugh School of Graduate, Online and Continuing Education, Fitchburg State University SP23_GIS and Decision Making-52 Dr. Davis March 6, 2023
Project Summary This week’s reading brought us full circle the prevalence and importance of GIS in today’s society. It was noted that “we have far more smartphones, tablets, and wearable devices than desktops and laptops” (Fu, 2022, p.109). Technology has advanced in such a manner that people now have the capability to access information at any point. Not only have we come to accept this, but we’ve come to expect it as well. As discussed in previous projects, this advancement has proved to be very beneficial to the growth and availability of geographic information systems. Whether they have been employed for operation context or just for making life easier, GIS have found themselves becoming a significant aspect of society. Chapter 4 illustrates the use of several mobile GIS applications ArcGIS offers and further our understanding of their importance in everyday life. The alternative project for week 7 wasn’t as interactive as the primary project but it did implement a very useful tool called Buffer. As mentioned in the project’s prompt, this tool is very useful for supply chain professionals in supporting logistical decisions and facility location decision. As with the focus of my future degree being supply chain management, I found this project to be a good example of what a situation that demands good supply chain logistics could entail. How resources are allocated is one of the most important facets of supply chain. This project centered on adding information in a fashion that can later be useful in creating a survey, and subsequently making performing addition analysis and making decisions as to how better to expand coverage in health emergencies. The data for Project 7 pertained to COVID-19 and called upon us to use the Buffer tool to analyze where acute care hospital coverage is provided versus operational COVID sites. As noted in the first statement of this paragraph, this data can then be used to create a survey in which people can offer input and other
up to the minute information, providing the necessary parties vital data on how to proceed in the next direction in order to remedy whatever issue the data pertains to. Propos ed Map https://smfsu.maps.arcgis.com/apps/mapviewer/index.html? webmap=e52931ff9fea43168cbf5d759ec03ad8 The first step in this project was the same as the preceding projects and that was selecting a basemap. Unlike some of the other projects where I just kept the default topographic basemap, with this project, I selected the streets basemap. Choosing this map was important because the analysis for this task pertains to addresses, especially when implementing the map notes. Map 1.1 shows this basemap zoomed in to show the defining factor of this basemap. Next, I added the required feature layers which were Acute Care Hospitals, GISCorps COVID-19 Testing Locations in the United States Symbolized by Status, and Massachusetts City/Town Boundaries (Survey-Derived). The first two layers contain our relevant COVID-19 data and will be our bases for comparative analysis. The third layer establishes town and city borders, creating some context for any relationships the analysis may provide. Map1.1 Streets Basemap Map 1.2 Acute Care Hospitals Layer
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Map 1.3 COVID-19 Testing Locations Layer Map 1.4 MA Town/City Boundaries Layer The next step was to use the Buffer analysis tool to create a new feature layer. The intent of this layer is to distinguish the areas where acute care hospitals provide coverage in relation to the COVID-19 Testing Locations. For this specific project, the buffer zone was a five mile parameter around each acute care hospital on the map. After selecting Buffer analysis, I set the radius to the given distance from each hospital. Map 1.5 shows each hospital’s buffer. Once this layer has been added to the basemap with all of the other layers, we can see the relationships the data and analysis offer. Map 1.5 Buffer of Acute Care Hospitals Layer Map 1.6 Project 7 Map with Featured Layers The final step was to add map notes. Here we highlighted COVID-19 operational sites that did not fall within the five-mile radius of any acute care hospital. After selecting seven operational sites, I edited the map notes to reflect the name of the operational site as well as
displaying its current address, municipality, and that municipality’s population. Presenting this data allows for those researching it certain determinations such as how many resources to divvy to a certain location based on that location’s surrounding population for example. Based upon the data, and as expected, we can see that the acute care hospitals and there buffer zones are very saturated in the eastern portion of the state where the majority of its population is located while they are more spread out the further west we move out. Map 1.7 Map Notes Layer Figure 1.1 Operational Site Map Notes Example Recommendations As previously stated, due to the more analytic nature as well as its relevance to supply chain logistics, I chose to partake in the alternate project rather than the primary. With the instructions and date provided, I found it fairly easy to complete. While the alternate projects haven’t seemed to contain the aesthetics of the primary projects, I feel they still have presented the data at hand in a visually comprehensive way. My only concern with this project was the appearance of the map after all of the layers were added; it is overly cluttered. Without the buffer layer in place, it is very hard to distinguish where the acute care hospitals on the map are as the COVID-19 layer’s data points overpower the other layers. However, due to the nature of the case and all of its associated data points,
everything is pertinent and therefore, none of the attributes can be removed. Doing so will not yield the desired analysis. Also, even though cycling layers on and off are an option, the full picture, the full analysis, would not be there without all of them being displayed. The only remedy to this predicament would to edit the layer so everything but the operation sites attribute was filtered out. However, as the layer was predefined, I did not have the option to do so. Furthermore, it could possibly just be semantics, but when editing the map notes, the prompt noted to include the population of the location. I wasn’t sure if that entailed the population of the municipality the specific location was in or if the directions intended for the population to be a certain radius around the operational site. Due to this and the fact I wouldn’t be able to determine the latter, I listed the town’s/city’s count. Conclusion This project caps the course and once again draws attention to the importance of geographic information systems. We were introduced to another valuable analytical tool, one that can prove to be useful in many circumstances. Buffer analysis gave us insight to where there may be disparity of resources and how they can be allocated to resolve the issue the data alludes to. The primary project and the chapter also introduced us to another ArcGIS app, Survey123, which allows for the creation of smart surveys. The use of these surveys keeps information as accurate as possible through the means of an interactive interface. The apps we’ve encountered over the last seven weeks have assisted in giving better representation to spatial data. Additionally, Chapter 4 doubled up on the ways geographic information systems have permeated everyday life in both personal and professional affairs. It should be noted again that the progression of technology has helped to thrust geographic information systems into the mainstream. People now have the power of a computer in the palm of their hand, a major
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development and a vast difference from the technological world of even ten years ago. As we’ve learned throughout this course, access to real time data is now available wherever and whenever and this is something society has come to expect. This parlays to the utilization of mobile apps such as Survey123 and Field Maps for data analysis. It contributes to location-based services such as Google Maps and Uber for personal use. Understanding the role and importance of geographic information systems has helped me gain better insight into how technology has greatly become an important aspect of supply chain logistics and I hope to be able to employ them more in my future down the road.
References (n.d.). Massachusetts Cities by Population. Massachusetts Demographics by Cubit. Retrieved March 4, 2023, from https://www.massachusetts-demographics.com/cities_by_population Fu, P. (2022). Getting to Know Web GIS (5th Edition). ESRI Press.