▘welcome to urban vein! click anywhere to continue, or read more about this project below:
by mapping the material composition of new york city’s buildings, we can uncover patterns of urban transformation that inform preservation, demolition, and future construction decisions.
what is urban vein?
urban vein is a dynamic web platform that reimagines new york city’s evolving identity through the lens of its building materials. this project bridges computation, design, and storytelling, offering spatial decision-makers the tools to identify trends and uncover patterns. it visualizes material archetypes across scales and explores temporal dimensions through historical and speculative narratives. at stake is the question of sustainability and urban memory. urban vein invites us to consider how material knowledge might guide responsible design practices in an ever-changing cityscape.
why is this important?
urban vein is an analytic and narrative tool that explores material histories, promotes sustainable urban practices, and challenges conventional demolition-preservation dynamics. it operates across scales—from the micro (individual buildings) to the macro (city-wide trends)—while fostering new practices in spatial storytelling.
through its focus on material life cycles and speculative timelines, urban vein invites users to engage with critical questions of sustainability and urban identity, presenting data in an interactive, participatory manner. the platform prioritizes user accessibility and narrative clarity, aiming to inspire informed decision-making for the built environment.
how does it work?
urban vein uses open data to estimate material compositions for the majority of its buildings. machine learning models analyze building age, size, and use to identify material archetypes, leveraging reference data where exact information is unavailable. these material archetypes inform a dynamic d3.js-based visualization that overlays five material layers.
this computational workflow affords granular insights into urban material trends. it enables seamless user interaction with layered data, offering toggles, hover functions, and future timeline animations. these methods transform abstract data into tangible actions to aid contextualizing material flows.
▘material estimation method
▘visualization archive
▘options
▘if a hexagon grid only has...
like the flatiron building,
it would look like this:
like one57,
it would look like this:
like the brooklyn navy yard,
it would look like this:
ABOUT
STORIES
EXPLORER
🞳
brick by brick
urban vein is developed by hao lee for the computational design practices program at gsapp columbia. the project was guided by (in semester & alphabetical orders) william martin, violet witney, laura kurgan, snoweria zhang, catherine griffith, and seth thompson.
of memory & vision
urban vein explores new york city through its building materials—their composition, distribution, and transformation. it examines what exists, what is being lost, and what should be built. urban vein is a lens into the city's evolving urban identity.
building material distribution
this map utilizes machine learning to analyze nyc buliding data from public sources and inferred the building archetypes to create a material dataset. each dot represents a specific building material, like steel, for a grouping of bulidings.
DATA
MEDIA
REFERENCES
PAST
PRESENT
FUTURE
LEGEND
TIMELINE
LAYERS
compare 🞃
▘material estimate 🞃
nyc buliding material estimate data
by hao lee
▘base map
nyc pluto data
by nyc department of city planning
nyc building footprints
by nyc opendata
▘base map background
new york state civil boundaries
by new york state gis resources
coastline (2012) of new jersey
by njdep bureau of gis
▘map layers
nyc gis zoning features
by the department of city planning (dcp)
nyc subway lines
by the metropolitan transportation authority (mta)
construction demolition registrants
by nyc opendata
geospatial data for bedrock elevation and overburden thickness maps of the five boroughs, new york city, new york
by laura m.demott, frederick stumm, and jason s. finkelstein, in cooperation with the new york city department of design and construction
▘visualization archive 🞃
one of the key challenges of this project was to develop a clear and effective visual style for overlaying multiple layers of material information onto a single map. the goal was to ensure that users could easily distinguish and interact with each layer. the visualization process was mainly conducted in qgis, culminating in a web presentation format using d3.js.
▘colloquium ii: review poster 🞂🞂
this is the poster for the Colloquium II end-of-semester review, designed as a 24" x 36" printed piece.
▘colloquium i: guerilla urbanism 🞂🞂
this is colloquium i's project website, which consists of two material-related speculative projects, booleanify and balloonify.
▘graphic/visuals
climate-conflict-vulnerability index
by moritz stefaner
marathon
by bungie
g4dp f24 precedent presentations
are.na channel curated by the fall '24 gis for design practices group at gsapp columbia
▘gis/mapping
gis for design practices
by dare brawley and mario giampieri
mapping historical new york
by center for spatial research
asian american dot density map
by jia zhang
nyc construction dashboard 2022
by dob analytics
▘material estimation & circular economy
city-scale assessment of the material and environmental footprint of buildings using an advanced building information model: a case study from canberra, australia
by natthanij soonsawad, raymundo marcos-martinez, and heinz schandl
materials passports - best practices
by matthias heinrich and werner lang
estimating the recoverable value of in-situ building materials
by aida mollaei, chris bachmann, and carl haas
rsmeans data
by gordian
circularise
by circularise
zestimate
by zillow
▘speculation
roadmap 2050
by oma
▘js libraries
leaflet
originally created by volodymyr agafonkin
d3
by mike bostock and observable, inc.
geohexgrid
by alex raichev at mrcagney
chart
by evert timberg and github contributors
sortable
by lebedev konstantin and github contributors
splide
by naotoshi fujita
▘columbia gsapp m.s.cdp
▘historical nyc
using materials to identify key decisions in city planning and urban development.
▘demolition materials
demolition activity from the 1980s to 2023.
▘intro to URBAN VEIN
what is urban vein? why is it important?
▘underground nyc
concrete foundations.
▘the carbon impact of bulidilng materials
the carbon footprint of our built environment.
▘the united material kingdoms
identifying material clusters.
timeline here
▘drag to reorganize map layers
add transparency control here
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☰buliding material geojson
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☰satellite imagery tile
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☰openstreetmap tile
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☰nyc zoning districts geojson
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bedrock elevationgeojson -
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demolition mapgeojson -
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carbon footprintsgeojson
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nyc subway lines geojson
▘quantitative classification
this map uses individual quantile classifications for each material instead of a universal one. this decision is based on several key considerations:▘data precision and integrity
the dataset is based on approximations and educated estimates rather than precise measurements. as such, it is essential to avoid creating over-confident visual representations that could imply a level of accuracy that the data does not possess.▘material weight differences
different materials, such as steel, concrete, or brick, have vastly different densities. these differences make it inaccurate to compare the values of one material to another using a universal bin. a direct comparison between materials could distort the understanding of their distribution, as the weight and volume of each material influence its presence in the dataset.instead, by using separate bins for each material, each material’s distribution is evaluated within its own context. this method allows for a comparison of a single material against its own distribution (color,) ensuring that variations in material properties do not skew the analysis.