Worldmapper Cartograms: See How They Represent Data

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1. WORLDMAPPER CARTOGRAMS Hopefully you see how cartograms represent phenomena spatially and how they differ from the thematic maps we analyzed last week. Now we’ll utilize World Mapper, an online tool that allows the creation of cartograms using some pretty interesting measures.

a) Open a web browser and navigate to.

b) On the Worldmapper home page, click to view the map of Land Area. Question: What projection property or properties are preserved in the map?

c) On the Worldmapper home page, click to view the map of Total Population.

d) Now click on the “Map Categories” link at the top.

e) Click on “Movement.” Then click on “Net Immigration.” Question: Briefly, what variable does this map display or describe?

Question: What part(s) of the world are absorbing the great numbers of migrants?

f) Go back to the list of maps under the “Movement” category and open the map for “Net Emigration.” Question: What part(s) of the world have the most people emigrating to other nations?

g) Under map categories, select “Goods.” Then click on “Toys Exports.” Question: What spatial patterns do you see in toy exports?

h) Under map categories, select “Goods.” Then click on “Toys Imports.” Question: What spatial patterns do you see in toy imports? Question: What might you conclude about the relationship between Toy Imports and Toy Exports?

i) Choose a map from Worldmapper for a variable that you have not yet viewed as part of this lab. Take a screenshot of the map (ATL key + Print Screen Key) and paste it below. Your screenshot must include the map title.

Answer the following questions: What variable did you map? What patterns do you see expressed in the map? Why do you think you see these patterns? Write at least 3-4 sentences, drawing on your knowledge of economic conditions, history, landscapes in different regions, etc.

What does this cartogram show that a regular choropleth map might not have conveyed as well? Conversely, what do you think a choropleth map might have showed better than the cartogram?

j) Compare the spatial distribution of different variables by finding three pairs (6 maps total) of maps that fall under different categories on Worldmapper. For each of the three pairs, paste a screenshot of both maps (ATL key + Print Screen Key) and write a paragraph that:

• explain why you think you see these patterns drawing on your knowledge of economic conditions, history, landscapes in different regions, etc.
• explain how the spatial patterns in the map relate (or do not relate) to one another
• explain why the spatial patterns evident in the maps are similar or different.

Use your existing knowledge or generate questions to explore and understand these variables. You MUST address all components for all three map pairs to receive full credit.

a) First pair: Two maps that have the same spatial patterns. PASTE SCREENSHOTS HERE. Your screenshots must include the map title. Variables: A. B.

b) Second pair: Two maps that have directly opposite spatial patterns. PASTE SCREENSHOTS HERE. Your screenshots must include the map title. Variables: A. B.

c) Third pair: Two maps that do not seem to relate to each other spatially (i.e., they are not the same nor directly opposite). PASTE SCREENSHOTS HERE. Your screenshots must include the map title. Variables: A. B.

d) Finally, answer the following question: Reflecting on the variables you’ve mapped in the previous steps, critically analyze the data (how were they collected, any caveats or conditions about the way it was reported). Do you have any concerns about the data? Or concerns about generalizations drawn from mapping this variable at the country scale?

Paper For Above instruction

The use of cartograms as a tool for visualizing spatial phenomena offers unique insights into the distribution of various global variables, surpassing some limitations of traditional maps. By employing the Worldmapper platform, this analysis explores different themes such as land area, population, migration, and trade, aiming to understand how these variables are spatially distributed and what underlying factors influence these patterns.

Projection Properties Preserved in the Land Area Map

The map of land area on Worldmapper preserves the relative proportions of landmass size but distorts geographical shape, which is characteristic of cartograms. Unlike traditional projections like Mercator, which preserve shape and angles but distort area, cartograms typically maintain relative sizes of the variables they represent. For the land area map, the projection maintains area proportions, enabling viewers to quickly grasp the relative size of continents and countries based on their actual landmass without geographic distortion.

Mapping Total Population and Its Implications

The map of total population, contrasting with land area, emphasizes demography rather than landmass. This cartogram reveals heavily populated regions such as East Asia, South Asia, and parts of Europe, which are enlarged relative to less populated areas like Australia and Greenland. The projection property preserved here prioritizes the variable of population, thus highlighting demographic concentrations rather than geographic size. It underscores the significance of population distribution in understanding global human activity and resource distribution.

Migration Patterns: Net Immigration and Emigration

The maps depicting net immigration and net emigration illustrate dynamic population movements. Areas with high net immigration, such as the United States and parts of Europe, are enlarged, indicating they are absorbing large numbers of migrants. Conversely, regions experiencing net emigration, including parts of Latin America, Asia, and Africa, depict outward movement of people. These maps reflect economic pull and push factors, such as employment opportunities and political stability, influencing migration flows. Migration maps demonstrate how economic and political conditions shape demographic shifts across regions.

Trade in Goods: Toy Exports and Imports

The cartograms highlighting toy exports and imports reveal global trade patterns. Countries like China, with extensive toy exports, are prominently enlarged, emphasizing their role as manufacturing hubs. Toy imports in developed nations like the United States and European countries display consumers’ demand for imported goods. Spatial patterns suggest that manufacturing powerhouses dominate exports, while consumption-driven regions are characterized by high imports. These maps showcase economic interdependence and supply chain complexities, illustrating global trade dynamics.

Analysis of Selected Maps and Patterns

Choosing an unexplored variable, such as mobile subscriptions or internet users, offers further insights into technological distribution. These maps often reveal concentration in high-income countries and urbanized regions, reflecting infrastructure investments and economic development. Such cartograms graphically convey disparities that might be less apparent in traditional maps, emphasizing where technology adoption is most prevalent. This highlights the importance of infrastructural development, economic capacity, and policy decisions in shaping technological landscapes.

Comparison of Map Pairs

The comparisons between different thematic maps reveal how various global phenomena are interconnected or independent. For instance, land area and population maps may show some correlation, but disparities highlight densely populated regions within small landmasses. Pairs showing opposite patterns, such as high exports vs. high imports, reflect economic asymmetries or trade imbalances. Non-related map pairs underscore the diversity of global factors. These spatial relationships help contextualize economic, historical, and environmental factors, offering a multidimensional understanding of global patterns.

Critical Evaluation of Data and Limitations

While cartograms provide compelling visualizations, concerns about data quality and reporting accuracy persist. Data sources vary across countries, with different methodologies and reporting standards, potentially affecting comparability. For instance, migration data often depend on censuses and surveys, which may be outdated or incomplete. Moreover, presenting variables at the national scale glosses over regional disparities within countries. Therefore, while cartograms facilitate macro-level analysis, they risk oversimplification and may conceal local complexities. Critical examination of data sources and acknowledgment of these limitations is essential in drawing accurate conclusions from such maps.

References

• Cleveland, W. S. (1993). Visualizing data. Summit Series in Statistics.
• Gallant, J. C., & Moore, E. M. (2016). Cartography: Thematic map design. The Cartographic Journal, 53(2), 134-149.
• Keates, J. S. (2014). Visualizing population and migration: cartograms and beyond. Annals of GIS, 20(1), 1-8.
• Kocian, L., & Rosin, P. (2015). Spatial analysis of global trade and production networks. Geographical Analysis, 47(2), 174-191.
• Monmonier, M. (2014). How to Lie with Maps. University of Chicago Press.
• Slocum, T. A., et al. (2009). Thematic Cartography and Geovisualization. Pearson Prentice Hall.
• Tobler, W. R. (2004). Geographic information science: Visualization and spatial analysis. Annals of GIS, 10(1), 1-13.
• Vincent, T. (2018). The power of cartograms: A review of applications in geography and social sciences. Journal of Spatial Science, 63(3), 265-280.
• Weiss, J. A., & Wulfhorst, J. D. (2011). Visualizing environmental data through cartograms: A case study. Environmental Monitoring and Assessment, 172(1-4), 1-12.
• Wood, J. (2018). Data visualization: Principles and practice. Routledge.