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Blog Post 4

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For my map I used NGIS to produce county level data from 1910 regarding total population, race and poverty (income relative to poverty level). I created layers on the map to show race/nativity demographics in the total population and farm ownership by race/nativity. I chose to join farm ownership data with race/nativity demographics to see how farm ownership could be relative to race and have direct effects on wealth disparities in the country. I most struggled to export my layers to a new geodatabase to make them permanent.  In Chapter 11, Monmonier discusses how the different choices you make when creating your map have a direct effect on how the information is perceived by the audience. In my map I used graduated colors to emphasize the differences of the races of farm ownership in different parts of the country. I chose to keep the colors of the different races the same when shown on the map as to not mislead people into biases or extremes when perceiving the maps.  Race Farm Owner
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Blog Post 3

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First I added a layer to the US 1880 counties birthplace map to visualize the percentage of the population that was born in China. I then added another layer to visualize the percentage of the population that was born in Africa. This showed how people originating from different countries tended to stay in areas similar to others originating from their same country. Lastly, I added a layer that shows where the historical railroads were located throughout the country.  Upon researching the spatial patterns I identified in my map, I discovered that the reason for the high percentages of Chinese population along the west coast was primarily due to the discovery of gold in California. Following the opium wars, many Chinese individuals lost their lands and suffered through years of floods, droughts and economic depression. Thus, upon hearing about the discovery of gold in California, many Chinese began migrating to California to make their fortune. The high percentage of Africans in southern
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Blog Post 2

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 I used ArcGIS to create a map which compared HOLC neighborhood grades to the Hispanic population by block group reported in the 2010 census. This map could help researchers establish if there is a correlation between neighborhood grades and minority populations, specifically Hispanics. This map does well in establishing the density of the Hispanic population (density of red dots) while still clearly being able to see the HOLC neighborhood grades. As one can tell, I found that commonly areas with greater density of Hispanics typically also scored lower HOLC neighborhood grades. However, I did find that some areas with high levels of Hispanic population still scored high HOLC neighborhood grades so it is difficult to establish causality between the two. A limitation of this map is the specification of only Hispanics because a map including both the minority population (Hispanics) and white population could provide further evidence regarding the correlation between HOLC neighborhood grad
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Blog Post 1

 Hey! My name is Gracie Mochizuki and I am a psychology major. This is technically my junior year but I am graduating 3 semesters early so this is actually my last semester here. I was born and raised in Charleston, South Carolina.  My advisor recommended me this class as it fulfilled a necessary requirement to graduate and she said she had heard good things about the class. I honestly came into this class blindly and wasn't sure what this class was even about. I honestly do not have any background knowledge on GIS but I am really excited to be learning something totally new this semester!
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