# Posts for Tag: geography

### Assembling the USA state-by-state with state-level statistics

Posted In: Maps

#### Watch the United States assemble state by state based on statistics of interest

Based on earlier popularity of the country-by-country animation, this map lets you watch as the world is built-up one state at a time. This can be done along a large range of statistical dimensions:

• Name (alphabetical)
• abbreviation
• Date of entry to the United States
• State Population (2018)
• Population per Electoral Vote (2018)
• Population per House Seat (2018)
• Land Area (square miles)
• Population Density (ppl per sq mi) (2018)
• State’s Highest Point
• Highest Elevation (ft)
• Mean Elevation (ft)
• State’s Lowest Point
• Lowest Point (ft)
• Life Expectancy at Birth (yrs)
• Median Age (yrs)
• Percent with High School Education
• Percent with Bachelor’s Degree
• Residential Electricity Price (cents per kWh) (2018)
• Gasoline Price ($/gal) Regular unleaded (2019) • State Gross Domestic Product GDP ($Million) (2018)
• GDP per capita ($/capita) • Number of Counties (or subdivisions) • Average Daily Solar Radiation (kWh/m2) • Birth rate (per thousand population) • Avg Age of Mother at Birth • Annual Precipitation (in/yr) • Average Temperature (deg F) • These statistics can be sorted from small to large or vice versa to get a view of the US and its constituent states plus DC in a unique and interesting way. It’s a bit hypnotic to watch as the states appear and add to the country one by one. You can use this map to display all the states that have higher life expectancy than the Texas: select “Life expectancy”, sort from “high to low” and use the scroll bar to move to the Texax and you’ll get a picture like this: or this map to display all the states that have higher population density than California: select “Population density, sort from “high to low” and use the scroll bar to move to the United States and you’ll get a picture like this: I hope you enjoy exploring the United States through a number of different demographic, economic and physical characteristics through this data viz tool. And if you have ideas for other statistics to add, I will try to do so. Data and tools: Data was downloaded from a variety of sources: • Population https://en.wikipedia.org/wiki/List_of_states_and_territories_of_the_United_States_by_population • Admission to union https://simple.wikipedia.org/wiki/List_of_U.S._states_by_date_of_admission_to_the_Union • Educational attainment https://nces.ed.gov/programs/digest/d18/tables/dt18_104.88.asp • Highest points https://geology.com/state-high-points.shtml • Life expectancy https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_life_expectancy • Median Age http://www.statemaster.com/graph/peo_med_age-people-median-age • Land area https://statesymbolsusa.org/symbol-official-item/national-us/uncategorized/states-size • Mean elevation https://www.census.gov/library/publications/2011/compendia/statab/131ed/geography-environment.html • Electricity price https://www.chooseenergy.com/electricity-rates-by-state/ • Gasoline price https://gasprices.aaa.com/state-gas-price-averages/ • GDP https://www.bea.gov/data/gdp/gdp-state • Sunlight North America Land Data Assimilation System (NLDAS) Daily Sunlight (insolation) for years 1979-2011 on CDC WONDER Online Database, released 2013. Accessed at http://wonder.cdc.gov/NASA-INSOLAR.html on Jun 14, 2019 1:37:15 PM • Births United States Department of Health and Human Services (US DHHS), Centers for Disease Control and Prevention (CDC), National Center for Health Statistics (NCHS), Division of Vital Statistics, Natality public-use data 2007-2017, on CDC WONDER Online Database, October 2018. Accessed at http://wonder.cdc.gov/natality-current.html on Jun 14, 2019 1:53:58 PM • Precipitation North America Land Data Assimilation System (NLDAS) Daily Precipitation for years 1979-2011 on CDC WONDER Online Database, released 2013. Accessed at http://wonder.cdc.gov/NASA-Precipitation.html on Jun 26, 2019 3:30:40 PM • Temperature http://www.usa.com/rank/us–average-temperature–state-rank.htm The map was created with the help of the open source leaflet javascript mapping library ### What are the highest mountains on Earth? Measuring from sea level vs center of earth Posted In: Geography #### The Highest Mountains On Earth Depend On How You Measure “High” Mount Everest is famous for being the highest mountain on Earth. The peak is an incredible 8,848 meters (29,029 ft) above sea level. But that is only one way to measure the height of a mountain. Chimborazo, a mountain in Ecuador, holds the distinction for the mountain whose peak is the furthest from the center of the Earth. How is that possible? This is because the Earth is not a perfect sphere. Rather, due to the spinning of the Earth around it’s axis, the centrifugal force causes the equator to bulge out slightly. This flattened shape is called an oblate spheroid and makes the radius of the earth at the equator about 22 km (about 0.3%) larger than the radius to the poles. Mountains close to the equator will “start” further away from the center of the earth, than those at higher latitudes. This graph plots over 800 of the highest mountains on Earth with their peak height above sea level on the x-axis and their peak distance from the center of the earth on the y-axis. Each point represents one mountain. The colors of the plots correspond to the latitude of the mountain. These mountains range from 3000 meters in height to 9000 meters in height. You can hover over a data point (or click on mobile) to get more information about the mountain. You can also switch from metric to imperial units with the button on the graph. For a given mountain range at a certain latitude, you can see that as the mountain heights above sea level increases, so does their distance from the center of the Earth. Mountains in the southern hemisphere are colored in blue, those around the equator are green and yellow, and those in the northern hemisphere are red and orange. The mountains with the highest peaks above sea level are shown on the right side of the graph in red and orange (mostly in the Himalaya), with Mt Everest as the right most point on the graph (nearly 9000 meters tall). Mountains with peaks the greatest distance from the center of the earth are found near the equator in light green/yellow and are found at the top of the graph. You’ll notice that a number of these mountains are higher than Mt Everest when looking at the distance from the center of the earth. The Himalayas are the “highest” mountains on earth if you are measuring height from sea level, while the Andes are the “highest” if you measure from the center of the earth. #### Calculating Distance from Earth’s Center to Mountain Peak The distance from the center of the Earth is calculated from the following formula: $$D_{mountain} = H_{mountain} + R_{lat}$$ where$D_{mountain}$is the distance from center of earth to the top of the mountain,$H_{mountain}$is the mountain height above sea-level and$R_{lat}$is the radius of earth at the mountain’s latitude. The height is data that was downloaded from a list of mountain heights. and the radius of the earth for a given latitude is calculated using the formula: $$R_{lat}=\sqrt{a^2cos(lat)^2+b^2sin(lat)^2\over acos(lat)^2+bsin(lat)^2)}$$ where$a$and$b\$ are the equatorial and polar radii (6378.137 km and 6356.752 km respectively).

Here is a calculator for determining the radius of Earth at a given latitude:

You can use this to calculate the distance from the center of the earth to sea level at your latitude.

Data and Tools:
Data on the heights of over 800 mountain peaks over 3000 meters in height was downloaded from Wikipedia. There ended up being alot of google searching and data cleaning to get it into suitable format for plotting. The calculations were made with javascript and plotted using plotly, the open source javascript graphing library.

### Visualizing The Growth of Atmospheric CO2 Concentration

Posted In: Environment

The current CO2 concentration in the atmosphere is over 400 parts per million (ppm). This has grown about 46% since pre-industrial levels (~280 ppm) in the early 1800s. The growing concentration of CO2 is a big concern because it is the most prevalent greenhouse gas, which is increasing the temperature of the planet and leading to substantial changes in the Earth’s climate patterns.

This graph visualizes the growth in CO2 concentration in the atmosphere (mainly from CO2 emissions due to human activities, such as burning fossil fuels for energy production, deforestation and other industrial processes). The graph starts at 1980 when CO2 concentration in the atmosphere was around 340ppm. It has grown significantly since then.

One of the interesting aspects of CO2 concentration is that it is not identical all around the globe, as it takes awhile for the atmosphere to mix. The graph shows geographic differences in CO2 concentration as well as seasonal ups and downs, that underly an overall growing trend in annual average (mean) concentration.

Seasonal trends in CO2 concentration occur due to differences in the amount of plant growth across different months. Spring and summer plant growth in the northern hemisphere causes a significant amount of photosynthesis, and CO2 absorption, relative to the fall and winter. This plant growth causes a very large amount of CO2 to be absorbed by plants and a noticeable reduction in the amount of CO2 in the atmosphere. The southern hemisphere spring and summer (northern hemisphere fall and winter) aren’t as obvious because there is much less land in the southern hemisphere and the land that is there is close to the tropics and green all year round.

CO2 concentration can change by about 4-5 ppm due to the “breathing” of plants, which is pretty significant. The total weight of CO2 in the atmosphere is about 3 trillion tonnes of CO2, so 4-5 ppm is about 1% of this or 30 billion tons of CO2 removed by plant life each spring/summer.

Data and Tools:

Data comes from the US National Oceanic and Atmospheric Administration (NOAA). Data was downloaded using an automated python script and the graphs were made using javascript and the open-sourced Plot.ly javascript engine.