Exploring and Creating a Map in ArcGIS Pro

Any business is run with precision. The notation of finite resources defining the balance between investment and profit. Like a business, Earth must also take note of its resources and find a balance between giving, taking, and planning. GIS is a broad piece of technology that can help managers, in many capacities, analyze past and present vector data to help prepare for the future.

During this first laboratory assignment in GIS5050, I learned the basic tools utilized to create a basemap, incorporating two types of shapefiles in the form of world counties and cites.

Image that the map and vector datasets below represent the number of covid-19 cases , reported by countries around the world for the past month.

One might be able to use the data/map to find case hotspots. Those hotspots could be used as a launch point to investigate why those cities are hotspots and what can be done to prevent the rapid spread of cases. The data/map could also be used to determine how to allocate resources to said countries/cities.

The applications of GIS are infinite and I am excited to learn what and how.

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Bivariate Choropleth and Proportional Symbols

In the first part of this lab, we used proportional symbols to represent positive and negative values in job increases/decreases in the USA. Because there were negative values in this data set, I created a new map to "fix" the data. In this new map, I created a new field and copied the negative job loss data. I then used the Calculate field data and multiplied it by one to make it positive. Lastly, I overlaid both maps on the data and was able to accurately represent the increase and decrease of jobs in the USA by state. In the second part of this lab, we delved into how to prepare data for a bivariate choropleth map, choose colors for the legend, and create a good layout. I created three separate fields to analyze the data: Class Obese, Class Inactivity, and Class Final. I used the symbology tool to create 3 Quantile for the Obese and Inactivity classes and used each quantile to set the three classifications in the fields I created using the Select by Attributes...

Positional Accuracy: NSSDA

In this analysis, I compared the street and road intersect data collected for Alburquerque, NM by the City of Alburquerque and the application StreetMaps. I used an orthophoto base layer as the reference for this analysis, to compare and determine the accuracy of both the City and Streetmap layers using NSSDA procedures. The most difficult part of this analysis for me was how to determine what 20% per quadrant looks like. Because the reference map was divided into 208 quadrants, I had to determine how to subdivide all the quadrant's equality into 20%. After multiple trials and error, I decided to subdivide the entire area (208 sub-quadrants) into 4 equal-area subsections. In this way, I could do 5 random right intersection points per subsection or 20% per subsection. Map 1: City of Albuquerque city map data. Map 2: City of Alburquerque SteetMap data When selecting a random intersection to place the points within each quadrant, I choose a location that had data f...

Infographic's

This week was a fun and challenging week as we learned about and created infographics. It was fun to create the infographics themselves, but challenging to figure out the best methods and practices in analyzing raw data. We used 2018 County Health Rankings National Data from countyhealthrankings.org. I chose to move forward with the two values: Unhealthy Mental Days and Premature Dealth. I choose these two variables because those that struggle with mental health die before their time due to depression, anxiety, and/or a combination of similar issues. Both variables are normalized by relating their value to all counties within each state in the USA. For example, the poor mental health days is normalized as the average number of reported mentally unhealthy days per month per ctizen. The normalized premature rate is the “age-adjusted years of potential life lost rate per 100,000.” Below, I created a scatterplot of the normalized data. I choose to k...

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