A geographic information system for working with maps
and other geographic information. The software is used for
creating, visualizing, editing and sharing spatial information.
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Consumable, user-friendly maps that simplify the process of overlaying and comparing data
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Quick identification of “hot spots” or “clusters” allow health departments to determine causation or provide an appropriate response or to address issues such as pollution levels
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Improved responsiveness to public concerns by reporting the location of an issue (water leaks, abandoned vehicles, etc.)
Constraints
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Open government: information produced by the government is public and therefore should be inexpensive and easy to access
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Individual privacy: privacy of citizens is paramount and data cannot be made public
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Security: security of the state is a major factor and data that compromise that security cannot be made public
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Fiscal responsibility: government should be entrepreneurial in its approach to data that have a market value.
How Can GIS Aid in Policy Making and Planning?
Public participation geographic information systems (PPGIS) pertains to the use of geographic information systems (GIS)
to broaden public involvement in policy making as well as to the value of GIS to promote the goals of
nongovernmental organizations, grassroots groups, and community‐based organizations.
Perks
Incorporating U.S. Census Bureau Data
into the Analysis
The U.S. Census Bureau's mission is to serve as the nation’s leading provider of quality data about its people and economy.
Its goal is to provide the best mix of timeliness, relevancy, quality and cost for the data they collect and services they provide.
Benefits
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U.S. Census Bureau data can be easily accessed via ArcGIS, which eased the mapping process. The data required no alterations, therefore limiting incidental manipulation while trying to convert it to a layer.
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It was assumed to be the most accurate given its variety of surveys between one, three, five, and ten years.
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Most smaller data sets refer back to the U.S. Census Bureau, so it was more logical to go to the initial source.
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The project focuses on an array of community aspects. It was assumed that the U.S. Census Bureau would host a majority of the required data given its diverse data topics such as income and poverty, employment, health, and populations and people.
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Some datasets are available by the census tract and census block group level, which are the two smallest geographical units. The project’s small scale requires data at these levels, as data at a larger geographical unit may not be as accurate or applicable.
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Limits
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A majority of the data came from the American Community Survey for 2018 or 2019. It cannot be guaranteed that all residents of each census block group complete the ACS in a correct and timely manner. Therefore, estimates of the magnitude of sampling errors – in the form of margins of error – are provided with all published ACS data. Sampling error is the difference between an estimate based on a sample and the corresponding value that would be obtained if the entire population was surveyed (as for a census).
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Some data topics are collected more frequently than others. There is a possibility of gaps in assumptions if the years of data sets vary.
The below maps were created to portray potential relationships between municipal waste management sites and community aspects in Baltimore City, Maryland. First, the creation of a base layer allowed the map to center around Baltimore City and its census block groups. Next, the overlaying of each relevant category worked to show potential effects from the waste sites. The relevant categories are educational attainment, median household income, mobility, diversity of building age, diversity index, unemployment rates, renter-occupied housing units, and the average age in households. Lastly, the top-most layer contains the locations of each municipal waste management. The map’s color scale is various shades of blue and green, or orange in the case of an uneditable dataset, to portray the sequential data of each liveability aspect. Each municipal waste site is represented by a bright red marker to distinguish them from the rest of the map. The map is intended to directly deliver Camden's findings, including minimizing distractions such as a poor color scheme (Velez, 2020). During the accumulation of data, there was little available data regarding the location of municipal waste management sites in the United States. Therefore, the layer that identifies the locations of the three municipal waste sites was created by Camden.
Mapmaking Using ArcGIS
Popular Demographics
This dataset is a feature layer that provides Esri 2018 demographic estimates from block group level for popular variables. They include 2018 Household Population, 2018 Median Age, 2018 Median Household Income, 2018 Diversity Index, and many more. Each variable will be laid underneath the locations of solid waste landfill facilities. The goal is to identify negative impacts that the facilities may have on aspects of the community such as diversity and median age.
Summary
Communities near a municipal waste site have fewer people over the age of 25 with a Bachelor's Degree in comparison to communities that are further away from a municipal waste site.
Mobility
Source: ACS Geographical Mobility Variables - Boundaries
The data set is a polygon layer about residence one year ago for those 1 year and older shown by tract. The layer can be filtered to show specific populations, such as the mobility of people between states, counties, or cities and towns. There is significantly less mobility in communities surrounding the solid waste landfill facilities. The below map portrays population one year and older who lived in a different county one year ago is portrayed. The darker the shade of blue, the higher the mobility between the selected population.
Summary
Communities near a municipal waste site have fewer people over the age of 1 who lived in a different county 1 year ago in comparison to communities that are further away from a municipal waste site.
Educational Attainment
This data set is a layer that shows the predominant education level attained by the U.S. population, aged 25 or over, by age and gender. There are six categories: Less than 9th grade, 9th to 12th grade [no diploma], High school graduate [includes equivalency], Some College [no degree], Associates degree, Bachelor's degree, and Graduate or professional degree. The education level is significantly lower in block groups and tracts that contain a solid waste landfill site. The darker the shade of blue, the higher the educational attainment of the population aged twenty-five years and older.
Note: Only one category can be shown at a time. This map portrays the educational attainment of a Bachelor's Degree; however, it can be filtered to portray the other categories.
Summary
Communities near a municipal waste site have fewer people over the age of 25 with a Bachelor's Degree in comparison to communities that are further away from a municipal waste site.
Diversity of Building Age
Source: Atlas of ReUrbanism
This data set is a polygon layer that portrays the character scores for buildings in Baltimore City, MD. A zoomed-in view of the map identifies that buildings surrounding the solid waste landfill facilities are similar in age. Currently, the age of each municipal waste landfill facility is unknown.
Note: Although the orange is visibly distracting, the color scale is uneditable due to restrictions
placed by the owner of the dataset.
Summary
Communities near a municipal waste site have buildings more similar in age in comparison to communities that are further away from a municipal waste site. These neighborhoods probably not seen local real estate development since the construction of the facilities.
Median Household Income
This dataset is a shapefile that shows median household income by race and by age of householder by tract, county, and state boundaries level and is based on income in the past 12 months of the survey. The analysis requires data by tract, as it is the second smallest geographic unit.
Summary
Communities near a municipal waste site have a lower median household income in comparison to communities that are further away from a municipal waste site. These neighborhoods probably not seen local real estate development since the construction of the facilities.