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Showing posts from April, 2022

M6: Isarithmic Mapping

  Above is a map of the average precipitation in Washington State. It was compiled in ArcGIS Pro using data from the U.S. Department of Agriculture. Our assignment focused on Isarithmic flow maps and we were required to make one map (not featured here) with continuous symbology and one with hypsometric tinting (seen above). To create the dataset containing rainfall measurements was converted into integers using the Int Spatial Analyst tool and symbolized using classes defined in the legend. The contour lines were added using the contour list tool and added lines to fit the classes set in our symbology of the rainfall.

M5 Lab: Choropleth Mapping

  This weeks lab required the creation of a choropleth map visualizing the population density and wine consumption in Europe. Population density has been symbolized by using a graduated color scheme from light blue to purple, and wine consumption per capita has been symbolized using graduated symbols (small to large and light to dark green). We were tasked with choosing between graduated or proportional symbols,  I chose graduate as the proportional symbols blocked many of the smaller European countries from view. To isolate the specific countries I wanted to symbolize and label, which varied between the primary and inset map, the data exclusion section of the symbology window was used and a query was written to omit unnecessary or redundant data. The graduated symbols used to represent wine consumption were sent through the Feature to Point tool which allowed my to move their individual positions. Similarly the country labels were converted to annotation so they could be positioned. S

M4 Lab: Data Classification

  This weeks module was about the different methods of data classification. The lab was designed to take these methods and apply them to a choropleth map, or more specifically two presentations of four maps each. Each presentation containing one map of Natural Breaks, Equal Breaks, Quantile, and the Standard Deviation classification methods. The above maps display these methods by analyzing the senior citizen distribution in Miami Dade County, FL. The top map was created in ArcGIS Pro first, it displays the percentage of senior citizens in each census tract and shows how the data is displayed differently using each of the classification methods. The bottom map was created by saving a copy of the top map and changing each frame to show the total population of senior citizens per square mile. Once these were finished we were tasks with determining what each method hides or reveals and which presentation was most accurate. I believe the total population per square mile is the least mislea

M3 Lab: Cartographic Design

      The object of the lab in module 3 was to take the data provided and create a map of the schools in Washington DC's Ward 7. During the design of the map it was required that Gestalt's Principles of Cartographic Design were implemented to accurately display the data while maintaining visual hierarchy     The map above used a thumbtack symbol to represent the schools in the subject area. Both increasing size and a color gradient from least to most intense were used to symbolize that schools from elementary to high school respectively. The red color for the symbols was chosen to visually emphasize the school locations in regard to the basemap. This was an implementation of Gestalt's contrast principle. To reduce school label clutter a table was used (top left)  to display the school names with their corresponding identifier. An inset map was used (bottom right) to display Ward 7's national location.     This map was created using ArcGIS Pro. Once all layers in the pro