This two minute time-lapse reconstructs the 400 year evolution of Lower Manhattan’s skyline. Watch as the city evolves from a small village into a glistening metropolis.
This is also a film about the history of technology. Changing methods of representing urban space influence our perception of time and the city. When New York City was founded, Dutch settlers captured their town’s appearance through 17th-century drawings and paintings. As the city grew, people started using printing presses to reproduce images of the city in the 18th- and 19th-centuries. In the 20th century, photographers started capturing their city from above through aerial photos. For the first time, New Yorkers could view the entire city in a single panoramic photo.
In tribute to this long artistic tradition, this film constructs the city as each generation of New Yorkers would have represented it: through the subsequent technologies of drawing, printing, photography, and film.
2017 by Myles Zhang
Sound effects from Freesound
Water and cloud effects from YouTube
Author’s time-lapse of Lower Manhattan’s street network development from 1609-2020
With help from digital and spatial mapping software, urban historians and geographers are examining city growth over time. Time-lapse evolutions are proliferating online of street network development in cities like New York City, Barcelona, London, and Berlin.
In most time-lapse studies, geographers encounter problems with lack of data. The older the city, the less data there exists about pre-modern population densities, demographics, and street networks. This lack of data is a problem when mapping the geographies of older cities.
A way around this problem is to look at street network development as a proxy for population size. The more streets there are built, the more people this city should have, the logic follows. In theory, this seems to work because cities with larger populations require more streets and occupy more built-up area. Knowing how much surface area a city occupies, coupled with knowing the average size and number of occupants in a typical block or building, allows a simple calculation of total population (people/acre x surface area). In addition, more historical data exists about street networks (from maps) than exists about population and demographics (from the census).
The problem with this method of using streets as a proxy for demographics is that cities that occupy more surface area and with more streets do not necessarily have more people. There are several reasons for this:
Available land: Some cities are built in harder geographies where acquisition of new land for development is prohibitively difficult to acquire, such as Venice. Manhattan’s high density and land values descend, of course, from a demand for housing that far exceeds supply on an island bordered by water.
For instance, Oklahoma City covers 621 square miles with a 2018 population of only 650,000. New York City covers 302.6 square miles (half the area of Oklahoma City) and has a 2018 population of 8.4 million (thirteen times the population of Oklahoma City). Despite the major differences between these two cities – in population and surface area – the sum total of all streets if they were lined up end to end to form a continuous road is about the same for both cities. Similarly, the Manhattan grid is identical with the same street widths and block sizes from end to end of the island, even though population density in buildings within this grid varies from zero people per acre to over 200 per acre. Flexible street networks support any variety of housing types and densities, which means that street maps alone cannot reveal all the demographic nuances.
Zoning: Some municipalities are stricter than others in enforcing discrete and different land uses for residential, commercial, industrial, and mixed-use. The legal landscape of Manhattan has evolved significantly since the first zoning laws in 1916 restricted building height and density. Since then, city government has more clearly articulated rules about minimum apartment size, ventilation, fire escapes, and water supply. City government has also pulled industrial (and often more polluting) land uses away from residential areas in the name of health and safety.
Although few of these legal and zoning changes are explicitly imprinted on the street network, they have a tangible and important impact on the quality of urban life. This zoning has largely resulted in lower population density because of restrictions on landlords cramming hundreds of people into the smallest space possible for the maximum profit. Now, over 40% of all buildings on Manhattan could not be built today for violating NYC’s zoning code for at least one reason. For instance, most buildings in neighborhoods like West Village and Lower East Side have not changed in a century; there is limited demolition and reconstruction every year. However, population density has significantly fallen as apartments grow larger and rooms formerly designed for multiple people in one room now only have one or two occupants. Even if the buildings and streets don’t change, the ways they are occupied can and do. In other words, changing in zoning and land use are not necessarily visibly imprinted on the plan of streets, particularly if those streets are rigid grids.
Transportation patterns: This is the biggest factor encouraging extensive and rapid street network development with low population density – i.e. sprawl. Before the nineteenth-century inventions of railways and streetcars, and the twentieth-century’s auto-based suburbanization, transportation and commuting were prohibitively difficult. People needed to live near to where they worked in what was largely a pedestrian and walking city on unpaved streets. Transportation challenges caused urban growth to be dense and built-up near to places of employment. As a result, many cities like Paris and London might appear small on old maps and occupy only a few square miles pre-1800, even though their population and economic importance were far larger than their surface area on maps leads one to assume. Again, less developed street networks and a smaller surface area of urban development does not neccessarily mean the corresponding city is less culturally or economically important.
Before the introduction of subways in the early twentieth century, the difficulties of commuting greater distances over land and water drove a denser form of urbanism than today. Manhattan, by 1900, had over 2.3 million residents in comparison to only 1.6 million in 2020. These people were crowded into dense blocks with upward of half a million people per square mile. Over the following century, although Manhattan’s population declined by 700,000 people, the street network today is almost identical to a century ago – no smaller and no larger despite major shifts. These shifts in density and demographics simply do not show up on conventional street maps.
My animation below shows the evolution of Manhattan’s built-up area and population density from 1800 to 2010. Notice the steady upward march of street development versus the sudden spike in population density on the Lower East Side in 1910 at over 300,000 people per square mile (in contrast to less than 90,000 in 2010). For every decade after the construction of subways, there has been more urban sprawl, and the island’s population density has fallen. Notice how fluctuations in population density operate semi-independently of street-network development.
Modified from Shlomo Angel and Patrick Lamson-Hall’s NYU Stern Urbanization Project,
here and here.
The animation on the left tells one story of continuous and north-moving development, while the animation on right tells a more nuanced story of population density. The challenge is to find a graphic representation that tells both stories, as neither visualizes all the nuances of urban history.
Discussing this problem of street networks with professor Kenneth Jackson, he suggested looking at building Floor Area Ratio (abbreviated FAR), which is the building height and size relative to the amount of land the building occupies. A skyscraper has high FAR. A trailer park has low FAR.
This method of representing urban growth would, in theory, produce three sets of maps: 1) a map of street network development; 2) a density map of people living per square mile; 3) a map of building height and size. This would complicate things but produce a far more accurate representation of urban growth (how to represent this and if enough data exists is another matter).
These three factors – streets, FAR, and population density – act semi-independently of each other. Different urban typologies will share a different mixture of these three factors. Only through analysis of the relationship between these three factors can one begin to understand the underlying demographic, economic, zoning, and historical differences between neighborhoods. For instance:
Downtown commercial district like Lower Manhattan: low population density but high FAR. In this case, FAR operates in inverse proportion to residential population density. Buildings can be dozens of stories but have no residents. There is a high density of tall buildings (i.e. high FAR) but low population density.
Slum like South Bronx in the 1980s: extensive (though poorly-maintained) street network development, high density, but low FAR because slum dwellings are typically informal without the construction quality required to build high. Buildings might be fewer than six stories and without elevators, as in the Lower East Side, but can contain hundreds or thousands of residents over the tenement’s lifespan. There is low density of tall buildings (i.e. low FAR) but high population density.
Suburb like Forest Hills, Queens: extensive (and well-maintained) street network development, low density, and low FAR. In wealthier suburbs, in particular, FAR is kept prohibitively low. Restrictions on minimum lot size required to build, minimum house size, and legal hurdles on subdividing larger lots into smaller ones all serve to enforce a certain quality and price of residential construction that often prices-out lower-income communities of color. There is low density development with numerous green spaces between free-standing homes (i.e. low FAR) and low population density.
Left: NYC population by day in 2015. Right: NYC population by night in 2015. The population doubles by day.
The two density maps above are one illustration of FAR and help nuance Manhattan’s historical development. Areas with the highest FAR tend to be commercial areas with daytime office workers and commuters. The left map shows the daytime population density of the over two million commuters. The areas with highest worker density neatly map onto the same areas of Lower Manhattan and Midtown with skyscraper clusters (i.e. high FAR). The right map shows nighttime population density of residential areas, which also neatly map onto areas with generally lower building height and density (i.e. low FAR). Notice the gray-colored zones in Lower Manhattan and Midtown with an almost zero nighttime population density, which are incidentally the areas with the highest daytime population density and the tallest buildings.
In twenty-first-century New York City, it is quite easy to examine the relationship between these three factors – street network, population density, and FAR – as the datasets are readily available from NYC Open Data. Yet, this all becomes more difficult – perhaps prohibitively difficult – for historical mapping. Calculating FAR for historical Manhattan is certainly possible through scrutinizing digitized historical Sanborn fire insurance maps that go so far as to specify building footprint, materials, and height. However, at the moment, this data is not easily accessible. Historical building footprints and FAR must be calculated through manually scanning, tracing, and inputting data from the New York Public Library’s collection. This must be done for thousands (even millions of buildings) over hundreds of years.
As technology improves, it may be possible in a few decades to translate historical maps into data files that reveal FAR. If historical maps could be scanned and immediately transformed from image files to geospatial data files, the possibilities of using historical maps to inform contemporary research are endless. If and when there is the data on historical FAR, it may be possible to create a new paradigm for studying urban history.
New York City Population Density in 1900
Author’s illustration based on population per municipal ward from 1900 Federal census
Abstract: The Berlin Evolution Animation visualizes the development of this city’s street network and infrastructure from 1415 to the present-day, using an overlay of historic maps. The resulting short film presents a series of 17 “cartographic snapshots” of the urban area at intervals of every 30-40 years. This process highlights Berlin’s urban development over 600 years, the rapid explosion of industry and population in the nineteenth-century, followed by the destruction and violence of two world wars and then the Cold War on Berlin’s urban fabric.
Animation der Wandlung Berlins
Zusammenfassung: Auf der Grundlage von historischen Karten visualisiert die „Animation der Wandelung Berlins“ die Entwicklung des Straßennetzwerks und der Infrastruktur Berlins von 1415 bis heute. In diesem kurzen Video wird eine Serie von 17 „kartographischen Momentaufnahmen“ der Stadt in einem Intervall von 30 – 40 Jahren präsentiert. Dadurch wird die Entwicklung der Stadt Berlin über 600 Jahre, das rapide Wachstum der Industrie und Bevölkerung im 19. Jahrhundert, die Zerstörung und Gewalt der zwei Weltkriege und abschließend des Kalten Krieges auf Berlins Stadtbild verdeutlicht.
German translations by Richard Zhou and Carl von Hardenberg
|Year, Event and Estimated Population
1415 – Medieval Berlin – 7,000
1648 – Thirty Years War – 6,000
1688 – Berlin Fortress – 19,000
1720 – Rise of Prussian Empire – 65,000
1740 – War with Austria – 90,000
1786 – Age of Enlightenment – 147,000
1806 – Napoleonic Wars – 155,000
1840 – Industrial Revolution – 329,000
1875 – German Empire – 967,000
1920 – Greater Berlin – 3,879,000
1932 – Rise of Fascism – 4,274,000
1945 – Extent of Bomb Damage – 2,807,000
1950 – Germania – World Capital
1953 – Recovery from War – 3,367,000
1961 – Berlin Wall – 3,253,000
1988 – A City Divided – 3,353,000
Contemporary – A City United
|Jahr, Ereignis und geschätzte Anzahl von Bewohnern
1415 – Berlin im Mittelalter – 7,000
1648 – Der Dreißigjährige Krieg – 6.000
1688 – Die Festung Berlin – 19.000
1720 – Der Aufstieg des Königreichs Preußen – 65,000
1740 – Der Österreichische Erbfolgekrieg – 90.000
1786 – Das Zeitalter der Aufklärung – 147.000
1806 – Die Koalitionskriege – 155.000
1840 – Die industrielle Revolution – 329.000
1875 – Das Deutsche Kaiserreich – 967.000
1920 – Groß-Berlin – 3.879.000
1932 – Der Aufstieg des Faschismus – 4.274.000
1945 – Die Spuren des 2. Weltkrieges – 2.807.000
1950 – Germania – Welthauptstadt
1953 – Deutsches Wirtschaftswunder – 3.367.000
1961 – Die Berliner Mauer – 3.253.000
1988 – Eine geteilte Stadt – 3.353.000
Heute – Eine wiedervereinte Stadt
Jahr der Volkszählung
Methodology and Sources
I chose not to represent urban development before 1415 for three reasons: Firstly, there are too few accurate maps of the city before this time. Secondly, I needed to find accurate maps that had visual style consistent with later years, to enable easier comparison of development over time. Thirdly, the extent of urban development and population is limited (fewer than 10,000 Berliners).
There are numerous maps showing Berlin’s urban growth. Yet, few of them are drawn to the same scale, orientation and color palette. This makes it more difficult to observe changes to the city form over time. Fortunately, three map resources show this development with consistent style.
The Historischer Atlas von Berlin (by Johann Marius Friedrich Schmidt) published 1835 represents Berlin in the selected years of: 1415, 1648, 1688, 1720, 1740, 1786. This atlas is available, free to view and download, at this link.
After the year 1786, I rely on three books from cartographer Gerd Gauglitz:
Berlin – Geschichte des Stadtgebietsin vier Karten
Contains four beautiful maps of Berlin from 1806, 1920, 1988 and 2020. Read article.
Berlin – Vier Stadtpläne im Vergleich
Contains four maps from 1742, 1875, 1932 and 2017. Read article.
Berlin – Vier Stadtpläne im VergleichErgänzungspläne
Contains four maps from 1840,1953, 1988 and 1950. The last map from 1950 is purely speculative and shows Berlin as it would have looked had Germany won WWII and executed Albert Speer’s plans for rebuilding the city, named “Germania.” Read article.
Gerd Gaulitz’s three map books can be purchased from Schropp Land & Karte.
I also show the estimated extent of WWII bomb damage to Berlin. This map is sourced from an infographic dated 8 May 2015 in the Berliner Morgenpost. View original infographic. This infographic is, in turn, based on bombing maps produced by the British Royal Air Force during WWII (and Albert Speer’s c.1950 plan for Berlin).
Below is an interactive map I created of the Berlin Wall’s route and the four Allied occupation areas:
Population statistics in the 17 “cartographic snapshots” are estimates. The historical development of Berlin’s population is known for a few years. For other years, the population is estimated with regards to the two censuses between which the year of the “snapshot” falls.
Developed with Gergely Baics, urban historian at Barnard College
New York City has some of the world’s cleanest drinking water. It is one of only a few American cities (and among those cities the largest) to supply completely unfiltered drinking water to nine million people. This system collects water from around 2,000 square miles of forest and farms in Upstate New York, transports this water in up to 125 miles of buried aqueducts, and delivers one billion gallons per day, enough to fill a cube ~300 feet to a side, or the volume of the Empire State Building. This is one of America’s largest and most ambitious infrastructure projects. It remains, however, largely invisible and taken for granted. When they drink a glass of water or wash their hands, few New Yorkers remind themselves of this marvel in civil engineering they benefit from.
This animated map illustrates the visual history of this important American infrastructure.
Sound of water and ambient music from Freesound
New York City is surrounded by saltwater and has few sources of natural freshwater. From the early days, settlers dug wells and used local streams. As the population grew, these sources became polluted. Water shortages allowed disease and fire to threaten the city’s future. In response, city leaders looked north, to the undeveloped forests and rivers of Upstate New York. This began the 200-year-long search for clean water for the growing city.
Gergely Baics – advice on GIS skills and animating water history
Kenneth T. Jackson – infrastructure history
Juan F. Martinez and Wright Kennedy – data
I created this animation with information from New York City Open Data about the construction and location of water supply infrastructure. Aqueduct routes are traced from publicly-available satellite imagery and old maps in NYPL map archives. Thanks is also due to Juan F. Martinez, who created this visualization.
Explore water features in the interactive map below. Click color-coded features to reveal detail.
Watersheds Subsurface Aqueducts Surface Aqueducts Water Distribution Tunnels City Limits
▼ For map legend, press arrow key below.
For such an important and public infrastructure, the data about this water supply, aqueduct routes, and pumping stations is kept surprisingly secret in a post 9/11 world. However, the data presented here is extracted from publicly-available sources online, and through analysis of visible infrastructure features on satellite imagery when actual vector file data or raster maps are unavailable from NYC government.
Encyclopedia of the City of New York – Kenneth T. Jackson
Audio narration – Myles Zhang
California Waterscape animates the development of this state’s water delivery infrastructure from 1913 to 2019, using geo-referenced aqueduct route data, land use maps, and statistics on reservoir capacity. The resulting film presents a series of “cartographic snapshots” of every year since the opening of the Los Angeles Aqueduct in 1913. This process visualizes the rapid growth of this state’s population, cities, agriculture, and water needs.
Music: Panning the Sands by Patrick O’Hearn
Dams and Reservoirs
^ Created with open data from the US Bureau of Transportation Statistics and visualized in Tableau Public. This map includes all dams in California that are “50 feet or more in height, or with a normal storage capacity of 5,000 acre-feet or more, or with a maximum storage capacity of 25,000 acre-feet or more.” Dams are georeferenced and sized according to their storage capacity in acre-feet. One acre-foot is the amount required to cover one acre of land to a depth of one foot (equal to 325,851 gallons or 1.233 ● 106 liters). This is the unit of measurement California uses to estimate water availability and use.
Aqueducts and Canals
^ Created with open data from the California Department of Water Resources, with additional water features manually added in QGIS and visualized in Tableau Public. All data on routes, lengths, and years completed is an estimate. This map includes all the major water infrastructure features; it is not comprehensive of all features.
Method and Sources
The most important data sources consulted are listed below:
This map excludes the following categories of aqueducts and canals:
- Features built and managed by individual farmers and which extend for a length of only a few hundred feet. These features are too small and numerous to map for the entire state and to animate by their date completed. This level of information does not exist or is too difficult to locate.
- Features built but later abandoned or demolished. This includes no longer extant aqueducts built by Spanish colonists, early American settlers, etc.
- Features created by deepening, widening, or otherwise expanding the path of an existing and naturally flowing waterway. Many California rivers and streams were dredged and widened to become canals, and many more rivers turned into “canals” remain unlined along their path. Determining the construction date for these semi-natural features is therefore difficult. So, for the purposes of simplicity and to aid viewers in seeing only manmade water features, these water features are excluded.