In 13 states where districts could be redrawn in the near future for the 119th Congress, we are delaying the release of estimates.īeneath each map are bar charts displaying the results for every question at whichever geographic scale is currently selected. You will find that not all congressional districts have data due to pending litigation regarding the adoption of new redistricting plans. The Congressional District Map reflects the 118th Congress (2023-2025). Meanwhile 71% in neighboring Grand County, Utah believe global warming is happening.Įxplore the maps by clicking on your state, congressional district, or county and compare the results across questions and with other geographic areas. Our new YCOM model estimates, however, show that only 49% of people in Emery County, Utah agree. Our national surveys show that 72% of Americans think global warming is happening. We can now estimate public opinion across the country and a rich picture of the diversity of Americans’ beliefs, attitudes, and policy support is revealed. Our team of scientists, however, has developed a geographic and statistical model to downscale national public opinion results to the state, congressional district, and county levels. So why would we rely on just one national number to understand public responses to climate change at the state and local levels? Public opinion polling is generally done at the national level, because local level polling is very costly and time intensive. Public opinion about global warming is an important influence on decision making about policies to reduce global warming or prepare for the impacts, but American opinions vary widely depending on where people live. Also see some nice work by Alasdair Rae who has produced some excellent 3D visualisations using GHSL.This version of the Yale Climate Opinion Maps is based on data through fall 2023. Change over time animations would definitely be an interesting approach to explore in the future. So far I have only visualised 2015, but have calculated statistics for all the years (turn the interactive statistics on at the top left of the website- I’ll post more about these statistics later). The comprehensive nature of the GHSL data means it can be analysed and applied in many ways, including as a time series as data is available for 1975, 1990, 20. This reflects rich agriculture and prospering cities, but like many urban regions is vulnerable to sea level changes. There is a massive concentration of population along the coast in South India. Huge rural populations surround the delta lands of West Bengal and Bangladesh, focused around the megacities of Kolkata and Dhaka. The intense settlement of Cairo and the Nile Delta is in complete contrast to the arid and empty Sahara. There are around 147 million people living on Java. The term desakota was originally coined by McGee in relation to Java in Indonesia, which has an incredible density of settlement as shown above. This emerging megaregion, including Tianjin, is sometimes termed Jingjinji. The form of Beijing’s wider region is quite different, with a huge lower density corridor to the South West of mixed industry and agriculture which looks like the Chinese version of desakota (“village-city”) forms. Population estimates range from 50-70 million depending on where you draw the boundary. The Yangtze Delta is also home to another gigantic polycentric megaregion, with Shanghai as the focus. The megaregions of China are spectacularly highlighted, above the Pearl River Delta including Guangzhou, Shenzhen and Hong Kong amongst many other large cities, giving a total population of around 50 million. Above is the northeastern seaboard of the USA, with urban settlements stretching from Washington to Boston, famously discussed by Gottman in the 1960s as a meglopolis.Įurope’s version of a megaregion is looser, but you can clearly see the corridor of higher population density stretching through the industrial heartland of the low countries and Rhine-Ruhr towards Switzerland and northern Italy, sometimes called the ‘blue banana’. The GHSL is great for exploring megaregions. A few highlights are included here and I will post in more detail later when I have explored the dataset more fully. There are clearly many applications of this data in understanding urban geographies at different scales, urban development, sustainability and change over time. The World Population Density map is exploratory, as the dataset is very rich and new, and I am also testing out new methods for navigating statistics at both national and city scales on this site. As usual, my first thought was to make an interactive map, now online at. This is the first time that detailed and comprehensive population density and built-up area for the world has been available as open data. A brilliant new dataset produced by the European Commission JRC and CIESIN Columbia University was recently released- the Global Human Settlement Layer (GHSL).
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