The information of an interconnected world redrawn in this map was assembled by Globaïa, an organisation which raises awareness concerning the global changes that characterise the Anthropocene. The individual layers that emerge in the image show build up areas and the light pollution of cities (white/yellow over land), roads (green), railway lines (orange) shipping routes (white/blue over sea), pipelines (red), transmission lines (blue) and submarine cables (yellow over sea).
In this gridded population cartogram the most populated areas get most space (reducing the depopulated areas), re-projecting the layers of human action and interaction accordingly. The cartogram puts a special focus on the dense network of links within the areas where people live.
Rather than being a mere image of densely built up areas with a clutter of infrastructure, this map highlights some significant differences: The distribution of lights from the brightest cities where all the global connections merge dominates the wealthier parts of the world. In addition, areas such as the east of the United States show a complex cobweb of all other elements displayed in the map. The African continent is characterised by having far fewer communication lines and even far less railways than many other parts of the world. Similar characteristics emerge in the shipping routes, giving an indication of the unequal connections of global trade routes and the imbalance of the underlying patterns that have such a high impact on the planet’s resources.
The human impact affects the entire planet, but for a large part of the world’s population the planet is far less a global village than a one way street that channels their resources such as oil or gas to the spaces that are the real worlds of the Anthropocene.

In the 21st century, time has been described as being a commodity itself, affecting everything from manufacturing and trade, to financial flows and global transport links.

The general geographic distribution of time zones is based on the general concept of dividing the world into zones of equal time following a 24-hour day around the world. In theory, this means that there are 12 time zones of 15° width in which each differs by one hour’s time difference.

The necessity of time zones was closely linked to growing needs of transport and communication links during industrialisation. British railway companies began adopting Greenwich Mean Time (GMT) which helped to coordinate timetables. In 1880, GMT became standard across Britain and time differences of tens of minutes between cities in the country started vanishing. At a global level, time zones became established in the first decades of the 20th century.

But as much as time zones are legal, commercial and social constructs, they are also highly political issues which find their expression in the spatial patterns of today’s time zones. The adoption of the Greenwich meridian itself can be seen as a highly political act that helped in manifesting a Euro-centric world view. Furthermore, many of the time zone boundaries do not follow the geographical pattern of each zone. Most boundaries follow political boundary lines such as country or state borders. While in some cases this can be practical minor deviations, more often the political decisions for time zones have a considerable impact on people’s everyday lives.

The most extreme example for geographical distortion through time can be seen in the case of China which covers the extent of five time zones, but only uses one, orientated on the location of Beijing (at UTC +8 hours). At the most extreme ends of the country, people use the same time even if sunrise is approximately four hours apart. India made a similar decision to continue using only one time zone by adjusting Indian time half way between the two time zones that used to divide the country (now at UTC +5:30 hours), with only approximately two hours solar difference appearing between the outermost parts of the country.

Another political decision was North Korea’s creation of Pyongyang Time in 2015, creating a 30-minute distance to its southern neighbour. Also a political decision was Iceland’s move to abolish changing the clocks between summer and winter time in 1968. Iceland’s decision meant a move towards adopting Greenwich Mean Time and becoming the westernmost country in that zone. On GMT’s eastern edge, almost all of the western European countries that would geographically fall into this zone instead adopted Central European Time (GMT +1), which has become equally large, touching the geographic extent of almost four time zones.

Larger populations are not always affected by such deviations from the theoretical time zone: The most extreme deviation was created by Kiribati’s decision to realign the zone for the Line Islands with the same date as its territory, meaning that the sparsely populated islands follow the same time as Hawai’i but are one day ahead as the ‘easternmost land’ with the earliest time zone (GMT +14 hours).

The above cartogram shows time zones from the perspective of an equal-population projection – a gridded population visualisation where each small area is proportional to the population living there. The map highlights how these geopolitical considerations have an effect on the impact that time has on people and the functioning of the world. Globalisation is far from having resulted in a compression of space and time. On the contrary, time defines our contemporary world because it has put a new meaning to the spaces of humanity, or, as Tennessee Williams describes it in The Glass Menagerie: ‘Time is the longest distance between two places.’ In an interconnected world, time is equally the longest distance between two people.

This map shows the results of the most recent Happy Planet Index 2016 report from the perspective of people. The gridded population cartogram, showing world resized according to the number of people living in each area, combined with the national HPI score.
The indicators that are used for calculating the HPI score cover life-satisfaction, life expectancy, inequality of outcomes and the ecological footprint. As argued in the report, “GDP growth on its own does not mean a better life for everyone, particularly in countries that are already wealthy. It does not reflect inequalities in material conditions between people in a country.” This explains, why consumption patterns are seen as more important for well-being than production. It also acknowledges that inequalities in well-being and life expectancy are important factors in the overall happiness of the population in a country.
When taking these notions into account, the rich industrialised countries score much worse in achieving sustainable well-being for all. Of the 140 countries included in the HPI, Luxembourg is the most extreme example for a wealthy nation scoring very badly: The country does well on life expectancy and well-being, and also has low inequality, but sustains this lifestyle with the largest ecological footprint per capita of any country in the world. It would require more than nine planets to sustain this way of life if every person on Earth would live the same way, showing that the standard of living comes at a high cost to the environment.
Amongst the positive stories is Costa Rica, which is also highlighted in the map. The country has persistently scored highest in all HPI releases (the 2016 edition is the third, after 2009 and 2012). More of a surprise might be the high score for Mexico (2nd), which is credited to massive efforts into improving health and environmental sustainability. Despite challenges with tackling inequality, well-being is perceived higher than in the wealthier northern neighbour, the United States. Quite a few Central and South American nations, as well as some Asian and Pacific countries do better than many wealthy nations. However, the African continent shows that at the bottom end extreme poverty can be a limiting factor in achieving sustainable well-being.
This change in perspective explains why in the public perception of wealthier societies the world has stopped from becoming an ever better place. The indicators used in the Happy Planet Index acknowledge some of the most pressing global issues in recent years, such as unstable economic developments, rising inequalities, and environmental change. These have become an important element in the well-being of societies. As a consequence, other parts of the world are doing remarkably better in the combination of these indicators. This might lead to the conclusion that there are valuable lessons to be learned from the best scoring countries about how to better achieve sustainable well-being for everyone on this planet, regardless of or beyond the aim for material wealth.

While the rural population has become a minority globally (at approximately 46 per cent), the majority of those are increasingly concentrated in the poorer parts of the world. Sixty-nine per cent of people in the least developed countries live in rural areas, while this number is at only 20 per cent in higher-income countries.

This cartogram shows how the distribution of rural populations compares in absolute and relative terms. The large, main map shows the countries of the world resized according to the total number of each’s rural population as of 2016. The varying green shades show the proportion of a country’s total population that live in a rural area (see key, bottom left).

East Asia dominates this cartogram with its large overall populations. India and China, as the countries with the largest rural populations, particularly stand out. While India is projected to slowly lose rural populations (six per cent between now and 2050), China is set to do so at a much faster pace (47 per cent). The most significant increase in rural populations, however, takes place almost solely on the African continent, where nine out of ten of the largest growing rural populations are located.

The two smaller cartograms look at these developments over a longer time span, showing the absolute changes in rural population between 1950 and 2050. These cartograms are distorted by absolute rural population decline and growth respectively.

Here the above described regional trends become visible in their absolute extent. Most of the absolute decline over that period takes place in countries that today are predominantly urbanised. Only China and mostly Balkan countries in Europe are among the slightly less urbanised countries that are seeing considerable declines in rural populations.

Significant rural population increases, by contrast, are mostly concentrated in those countries that have rural populations of over 50 per cent.

Migration into cities is one major reason for declining rural populations. However, these maps highlight that this affects overall rural population numbers less significantly in some of the poorest parts of the world. Here natural population growth keeps rural regions growing in absolute terms. By contrast, China’s active intervention through the Hukou residence registration system and the one-child policy influenced these developments considerably, making its developments differ from other countries in the region.

Overall, declining rural populations in already very urbanised countries have become a complex governance issue. This is mostly the case in the wealthier parts of the world, especially in Europe. Modern rural flight in the past six decades and its projected continuation well into the 21st century requires rethinking rural development to ensure a balanced economic development between the growing urban and shrinking rural regions.

Calculating the average tree cover in an area allows us to estimate the extent of the world’s forests. Forest landscapes can be mapped in various ways and is often done in conventional maps. However, much of the land area is not covered by forest and the few remaining untouched forest landscapes keep shrinking while deforestation continues.

This visualisation of the global tree cover shows the quantitative distribution of the world’s forests. In a ‘gridded cartogram’, each of the grid cells shown covers an equal physical space and is then resized according to the total amount of space covered by trees in this area. Additional topographic features showing the elevation similar to normal topographic maps (from green for the lowest lying areas to brown and white for the highest regions), and the surrounding bathymetry of the world’s oceans remain as guiding elements in this cartogram.

While conventional maps are ‘equal area’, ‘equal distance’ or other projections, this map gives us a new visual understanding of the distribution of the world’s forests while preserving the geographical accuracy by retaining the topology between each of the grid cells.

The visualisation is an image of the fragile forest-landscapes which make up approximately 31 per cent of our land area. They are the world’s lungs, providing home for a multitude of the most complex and diverse ecosystems on the planet. However, they are also the basis for the livelihoods of many people, and an important economic factor, and are therefore under threat of deforestation – especially in the tropics – which make up a lot of the spaces in this map.

Forest-scapes can also be seen through different lenses, such as how the distribution of tree cover relates to the distribution of people on earth. The following map shows an equal population projection (based on a gridded cartogram transformation where each grid cell is resized according to the total number of people living within that area) superimposed by the same data of global tree cover that is visualised in the above map. What can be here is not where which quantities of trees are in the world, but how much tree cover there is in those spaces where most people live. While there apparently is less tree cover where people live, there are some obvious variations, as this map shows. In regions such as in the Eastern United States of America or the tropical rainforests quite a significant amount of tree cover can be found in the more densely populated areas. The most an unbroken expanse of natural ecosystems within the zone of current intact forest landscapes in the world, however, describing the forest extent which is showing no signs of significant human activity, which take up much of the space in the above map, almost disappear from this map (shown in bright green here):

Gridded population cartogram showing tree cover density proportional to the global distribution of people

Cars are generating the most emissions and pollution per passenger kilometre and also have significantly higher accident rates. Mass transit and public transport, including buses and coaches as well as trains, are therefore regarded as the more sustainable alternatives and have regained importance in urban and regional planning.

Buses rely on the same transport infrastructure as cars, while trains require railway tracks in order to maintain or improve the existing transport capabilities. Recent trends showing a slow but steady revival of passenger transport by train in Europe therefore have to be seen in the context of its existing transport infrastructure. New railway infrastructure is costly and requires time-consuming planning procedures.

A look at the railway infrastructure in Europe (beyond the EU) shows that across the continent there are approximately 250,000 km of tracks, just slightly lower than the length of tracks in the USA, where train travel plays a subordinate role in passenger transport but serves mostly freight transport.

This cartogram shows the share of railway infrastructure in Europe in the form of a so-called ‘rectangular cartogram’. Early forms of this perhaps most classic form of cartogram can be found in the 19th century and have been regular features in school atlases for decades. Their construction is a lot less complex than other cartogram types, although complexities remain with the geographical arrangement of the rectangles, and how each entity is connected to the others. With only four sides, geographic accuracy is hard to preserve. In this map, each country is represented by a rectangle whose area represents the total amount of railway tracks it has. In addition, all countries that have more than 1,000 km of track length are labelled, and the countries are shaded by the relative importance of railway travel in the passenger modal split of that country.

The cartogram shows the important role of train transport in parts of Central and Eastern Europe. Here the network is considerably stronger than the motorway network, a legacy of a strong focus on non-individual means of transport until the 1990s, although they are partly in need of major re-investments. The smaller train networks in Switzerland, Austria, and Denmark stand out. The modal split of train travel in these (equally relatively small) countries is significantly above the European average. The relative importance of the train is much lower in the Baltic states as well as across the Balkan countries. Southern European countries also show a relatively poor network compared to their area.

The future of train transport in Europe remains challenging. While there is an overall revival of railway travel, the differences in the quality and structure of the networks vary. This matters even more in inter-continental travel routes between countries in pan-continental transport corridors. A fully functioning trans-European rail network will be key to a more sustainable transport system across the continent.

Hate and extremism have gained wider attention with the rise in populism and populist politics. The election of Donald Trump was also in part attributed to his rhetoric connecting to far-right extremism in the US. In the UK, a spike in hate crime was linked to the Brexit vote, while a considerable increase in anti-Muslim abuse has also been observed in recent years.

Describing and understanding hate crimes and groups associated with committing (or endorsing and promoting) such crimes is a complex issue and scholarly definitions are still not fully agreed upon. Dr Phyllis Gerstenfeld of CSU Stanislaus describes a hate crime as ‘a criminal act which is motivated, at least in part, by the group affiliation of the victim.’ John van Kesteren of Tilburg University observes that prejudice and hatred of specific social groups ‘characterized by immigrant or ethnic status, race, religion, gender, sexual orientation, or disability’ are therefore at the core of hate-related crimes.

Among the organisations monitoring groups that advocate hatred is the Southern Poverty Law Centre (SPLC) which was founded by civil rights lawyers in reaction to activities by white supremacist groups such as the Ku Klux Klan. Today its scope includes the activities of a broad range of US hate groups and other extremists, including the Klan, the neo-Nazi movement, neo-Confederates, racist skinheads, black separatists, anti-government militias, Christian Identity adherents and others.

Donald Trump’s presidential campaign in 2016 has brought hate groups further into the spotlight. The SPLC attributes this to the divisive and polarising language he is using. A study undertaken in the aftermath of the presidential election indicated evidence for this ‘Trump effect’, with a significant number of hate incidents immediately after the election, and 37 per cent of the 1,094 investigated bias incidents referring directly to the then president-elect or using his campaign slogans.

This cartogram is based on a compilation of a total of 917 hate groups that the SPLC has identified across the mainland 48 states of the USA in the year 2016. It uses ‘hate group publications and websites, citizen and law enforcement reports, field sources and news reports’ for its database and monitors activities such as ‘criminal acts, marches, rallies, speeches, meetings, leafleting or publishing.’

The overall distribution of hate groups is shown in the main cartogram at the top of this page. Here each state is resized according to the total number of groups, overlaid by the proportion of hate groups in relation to the population distribution.

The SPLC categorises a total of 18 hate ideologies of which nine are displayed above in more detail as cartograms distorting the states by the distribution of the respective hate ideology. The colours in the smaller cartograms shown throughout the page refer to four main regions within the USA as shown in the reference map.

This series shows that hate ideologies follow some distinct spatial patterns across the USA. The Ku Klux Klan is rarely represented in the western region, while the neo-Confederates appear even more concentrated following their ideological origins in the south. Christian Identity in contrast, an anti-Semitic and racist theology that rose in the 1980s, is in decline. Today’s anti-Muslim hate groups have started emerging in the aftermath of the 9/11 attacks – 2016 has seen a 197 per cent increase in numbers. The distribution of anti-Muslim hate groups is widespread, looking similar to the overall population distribution.

This picture is only part of the whole phenomenon of hate groups, which has been on a steady rise in the digital world as well. The maps give an indication of the disparate patterns that underlie these extremist views. The geography of hate in the United States is a reflection of the realities that determine the social tensions within the different parts of the country.

The latest version (shown as a small inset map in this cartogram feature) is not only the most accurate picture of light intensity around the globe, but the underlying data also allows a direct comparison of the changes that occurred between 2012 and 2016. For achieving this, the datasets of the two years were corrected for the changing light effects caused by the moon as well as “seasonal vegetation, clouds, aerosols, snow and ice cover, and even faint atmospheric emissions (such as airglow and auroras)” which “change the way light is observed in different parts of the world”. Both datasets also cover the period of a full year to take seasonal changes into account.

This cartogram provides an insight into the changes in night light intensity between 2012 and 2016 by applying a geostatistical approach first described by ESRI cartographer John Nelson. Using night light imagery at a 3km resolution as a basis a geospatial analysis of the differences between each area was performed to calculate how much the intensity has changed over time. The resulting data shown in this map highlights where the intensity has declined (purple) or increased (blue) within the last four years and at what magnitude these changes were. Unchanged intensities remain black, so that unlike in the original Earth at night map here cities and other bright areas do not stand out unless they have seen a significant change in that period.

The cartogram transformation itself depicts an equal-population projection using a gridded cartogram approach in which all areas are proportional to their total population. It therefore serves as a magnifying glass over the most densely populated areas and gives us an idea where changes to economic, social, political and other human activities have led to considerable differences in the distribution of light at night.

At a global level the north of India stands out as a region where a huge increase in brightness has taken place in an area that is also heavily populated. Dense urbanisation as well as economic development make this region stand out when looking at changes in night lights. In contrast, the purple areas in the east of the Mediterranean reaching from the coast inland like a band towards the south mark the effects of war in Syria. Here large stretches of densely populated areas became darker in the past years, while neighbouring Lebanon and Israel along the coast have become brighter just like larger parts of the populated areas in Iraq towards the east. In Europe the picture resembles more of a patchwork of brighter, darker, but also many unchanged areas. In many cities across Europe, from London to Moscow, the ongoing effects of the cities spreading out and the suburban areas becoming brighter can be observed. Unchanged and dark in the change maps as well as in the night light map remains one outlier: Apart from Pyongyang, which has an overall decline in night lights, North Korea remains dark on the world map of light.

NASA’s future plans for this project are an automation of their techniques to provide regular updates to night light data. The future availability of daily data or even the almost instant access opens a wide range of possible applications that range from disaster response to tracking illegal fishing activities or monitoring sea ice movements for climate change research. Different insights into the data, such as cartographic distortions shown in this cartogram, can also contribute to gaining different insights into the underlying complex datasets.