A group calling themselves New Urban Industrial created a project about Brooklyn’s waterfronts.

In their words:

The purpose of this project is to create an online comparison tool that spatially plots the manufacturing territories within the Significant Maritime Industrial Areas of Brooklyn and Queens in order to demonstrate their zoning implications, environmental impact, hard infrastructure, and community infrastructure systems. This tool enables these multiple elements within the three main sites of the Brooklyn Navy Yard, Gowanus and Newtown Creeks waterways to be compared to one another, allowing for analysis of industrial zones.

Similar to the Rethink the Block project 3, group members focused efforts on centralizing data for their themes. Data collection and analyses were done separately along the lines of these themes.

Some data was not immediately accessible and was processed before use:

In addition to the many of maps, which include data on watersheds, TRIs and brownfields, transportation routes, this project also contributes an important data set: a map of the locations for all the community organizations in four different community boards. This information had previously existed separately in non-­machine-readable formats (PDFs, searchable web pages, etc), and therefore was neither easily accessible, nor georeferenced. By creating a georeferenced data set for all this information and crafting an interactive map, it reveals a spatialized view of their density among their neighboring community boards. This project has created a valuable and accessible resource not only for the community boards, but, more importantly, for the communities themselves. The available technology of GIS mapping may serve as an important community agency tool. It should be noted though, this tool has its limits in that it is only able to show the “parceled” information which not always reflects accurately the complex urban dynamics on the ground.

Urban Industrial- Comparing Three NYC postindustrial spaces.

Urban Industrial- Comparing Three NYC postindustrial spaces

Conclusion

Once the data was collected for each of the themes, the themes were displayed together via three maps (one for each of the waterfront segments being considered). Here the group describes the reasoning behind this choice:

The initial goal of the project was to visually bring together three disparate sites. The sites are of interest because each are particularly reflective of the physical and social impacts of post­industrialism in New York City. Newtown Creek is one of the most polluted waterways in the country due to the decades of industrial waste dumping that has been allowed; The Gowanus Canal is also a historical dump site, and like Newtown Creek, has a large amount of brownfield areas. Furthermore, the air space around this community is especially polluted due to the dense truck traffic on the Gowanus Expressway and the Brooklyn Queens Expressway. Finally, The Brooklyn Tech Triangle, an area between Downtown Brooklyn, Dumbo and the Brooklyn Navy Yard designated by the city to attract manufacturing and tech companies, is in desperate need of a more organized, local social infrastructure as ‘outsiders’ create pressure to radically change the real estate and labor divisions in the area. It is crucial that members of these communities have access to information regarding physical dangers and complexities in their neighborhoods, as well as existing social framework opportunities in order to become more prominent actors in the changes taking place in their area. Since each site shares almost all of these post­industrial complications in some capacity, we decided that it would be more informative if we showed detailed maps of the area side­ by ­side, so these relationships could be succinctly and comprehensively understood by the viewer.

The final site uses CartoDB to host the data and maps and required some programming to get the maps to work together within the themes. There is a preview below, and the site is available @ urbanindustrial.neocities.org.

The environmental theme on the final site

The environmental theme on the final site

Data Sources

The group listed the following data sources:

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The Everyday Urbanities group created a project called The Right to the Sidewalk about street vending in New York City. In the words of the group:

The narrative surrounding New York City, until recently, has been shaped more around its vast economic wealth, opportunity, and its status as a ‘Global City’. This story continues, blinders intact, to create a vision of New York City that explicates the ‘formal’ processes of laws and political-economy; while simultaneously mystifying how many ‘informal’ processes of production, distribution, and everyday life occur within the dual city.

Our work […] attempts to make the implicit/masked/everyday processes of the city more explicit through a parallel investigation between the macro and micro, formal and informal processes, as they interact, contradict, and sometimes compliment one another.

One powerful example, and the initial focus of our transdiciplinary research, is the case of local street food vendors. Many of these local startups can be lucrative, and relatively easy entries into self owned employment. Unfortunately, the city of New York has been incredibly punitive with its regulations of where these vendors sell their wares. These restrictions have taken the form of legal obligations for vendors to locate their carts certain distances from doorways, commercial business’s, crosswalks, bus stops, fire hydrants, schools, hospitals, residences. This set of conditions is compounded by street restrictions by time, cart size/type/function specifications, and the private regulation of public space granted by city government to Business Improvement Districts (BIDs).

To better understand the restrictions on street vending, some of the group members set out to turn data on the city’s streets that have vending restrictions into geodata. This data is generally trapped in printed pages that include lines such as “Broadway from West 32nd to West 52nd, everyday, 8am to 8pm.” The group geospatially developed these street segment expressions, and this enabled comparing the restricted streets with other dynamics such as Business Improvement Districts.

restricted streets

Streets in NYC with restrictions on street vending

Below we see the group making maps to compare BIDs (yellow), street vendor restrictions (red), Privately Owned Public Spaces (POPs, in white), and areas where street vendors are often issued tickets (black). Analysis and creation of data was done with QGIS, and the interactive maps were made with CartoDB and TileMill.

In response the to critically restrictive nature of this process, not to mention the outrageous fees and fines required and levied against these new entrepreneurs, our team took on the task of creating an interactive set of maps that would bring the complexity and contradictory nature of these regulations to light.

Bids, Pops, restricted streets, and tickets

BIDs, POPs, restricted streets, and tickets

Conclusion

While the group’s project undoubtedly had some concretely useful outcomes (such as making the restricted streets data digital) and was a productive contribution to the group’s thinking about the topic, some valid concerns ultimately arose over the utility of GIS for understanding the informal dynamics of the city:

Ryan Devlin traced the different factors that lead to informalization of street vendors, but also the informalization of their management. Today, the regulations are so convoluted that they can be instrumentalized against the vendor contextually by mobilizing the existing regulatory apparatus. Crackdowns on vendors have therefore more to do with economic and political conditions, which are challenging to map via GIS, rather than conditions in the streets. It happens in a decentralized, privatized and informal way through techniques of surveillance, intimidation and physical interventions on the sidewalks.

Drawing on Deleuze, Devlin describes it as a shift towards a post-disciplinary logic of control and urban management, where subjects deemed problematic are managed in place, case by case, block by block, and even inch by inch, rather than being targeted for reform. In other words: informal urbanism, from the top-down, which is why what we can show through GIS is quite limited. This blurriness is exactly what enables the authorities to harass the vendors. So even the map of restricted streets that we built does not, in the end, inform explicitly what is happening on the ground.

Data Sources

The group listed the following data sources:

  • NYC Open Data: Ticketing, Business Improvement Districts, 311 Food Poisoning Complaints, Street Centerlines
  • Bytes of the Big Apple: Boroughs
  • POPS in New York City
  • Restricted Streets were manually digitized based on a PDF from the Department of Consumer Affairs
  • Vendor commissaries and cart manufacturing location data were collected for this project

A group of students working under the name Rethink the Block worked on a project around housing in New York City, each member authoring their own aspects of the housing question. In their words:

Our thesis group continues to focus on the multiple and complicated layers that often emerge from the narrative surrounding housing. Since each member of the group operates from a particular lens that aims to expand upon the dominate housing narrative, the initial process of data collection and methodology required extensive discussions to ensure that information could be coherently coalesced. The end product moving forward is to create a user friendly tool that can be used by a diverse community of stakeholders committed to influencing a progressive narrative surrounding the challenges currently presented by the housing sector.

A criteria was established to define the information we wanted to capture that could help us generate a spatial visualization of areas that may be at-risk for speculation and development. This included researching data sets that would provide information on:

1. total median income
2. minority population
3. rent stabilized property
4. tax exemptions
5. percent of income allocated towards rent
6. proximity to the subway

The group set about mapping each of the above city-wide by census tract. For example, here is a map of rent-stabilized property by tract:

Rent-stabilized property by census tract

Rent-stabilized property by census tract

This data was analyzed and mapped in QGIS.

Conclusion

In sum, the data was averaged by census tract, and the tracts with higher rankings were deemed more at-risk of development. Averages were mapped using CartoDB, which you can see @ their site. This was a cohesive, effective way to incorporate each member’s interests and make a statement in aggregate that would be challenging to make otherwise. The results were also relatively intuitive:

The group's final, interactive map

Rethink the Block’s interactive map

As we begin to compare the ranking for each data set, we were able to produce a map of the city that identifies the nodes we found have the highest possibility for displacement because of speculation and ultimately gentrification of the area.

We began to produce maps using data such as neighborhood demographics, average median income, occupancy types, rent controlled properties, etc. The creation of these various maps was part of our methodology for the final project. Each map ranks the city census track and according to how high or low their rank is signifies their potential for re-development.

The maps we created will contribute extensively to our thesis research. They are breaking down the complex data and facts that highlight the various reasons for housing inequality and housing unaffordability in New York City. The data that we found is particularly important in disclosing the inequalities and supporting our claims with analytical data.

Data Sources

The group listed the following data sources:

The Common Praxis group attempted to map the “potential for commons” in a rather large portion of Brooklyn. In the words of the group in their narrative:

The Commons is a social method to collectively hold and manage resources: it cuts across all sectors of society. Common Praxis, our thesis group, studied commoning as it occurs in six different sectors in five community districts of Brooklyn, New York. Key features chosen for each of those sectors became layers in our map. Despite their difference, we hypothesized that commoning practices may thread through them. Representative layers are: affordable housing stock, hospitals, buildings with boilers that will need to be replaced, industrial zones, transportation, and contingent workers by industry.

The corridor we chose stretches from Williamsburg, through Greenpoint and Bushwick, Bedford Stuyvesant and into Brownsville and East New York.

The part of Brooklyn that Commons Praxis studied for this project

The part of Brooklyn that Common Praxis studied for this project, including subway lines. Census tracts are shaded by median household income.

Each group member had specific data layers that they developed within the region defined above. The group’s narrative continues:

By overlapping these layers of activity we developed several key findings concerning a larger Urban Commons. Our goals were to show what areas of the city this type of activity would be most pertinent, and what those regions show us about urban processes now, and potential for the future. Two main areas of potential activity surfaced- Broadway Triangle and Broadway Junction. Both areas are generally considered marginalized communities. Unexpectedly, we found that holistic community health could be a central motivation for commons activity in those areas.

With community health in mind, we see that Urban Commons have great potential throughout the corridor we chose, as it is fostered through community wealth building, environmental justice initiatives, permanently affordable housing, cooperative production and energy and involvement from key health institutions.

Conclusion

By looking at the data geographically and at a scale that includes various neighborhoods in Brooklyn, the group came to conclusions that more typical neighborhood-level (or -centric) analyses might miss. Specifically, the group found that community health is an area that holds potential for urban commons and there exist anchors at the nexus of these neighborhoods that might foster these commons.

When one takes a broader lens at North East Brooklyn, new focal points of activity and opportunity emerge that defy these frames. At the meeting point of Bed­Stuy, Williamsburg and Bushwick, Broadway Triangle is one of these sites. As it happens, this is an area in which several group members are already helping with organizing, although they consider themselves only ‘Bushwick focussed’. In this area we find a dynamic set of conditions that make it a potential anchorpoint of common activity. Anchored by Woodhull Medical Center, the area is also home to a convergence of many other layers. We believe this may indicate the creation of a broader urban commons that transcends neighborhood borders and brings together community organizations into coalitions that go beyond typical areas of action.

Considering the consolidation of these layers, we are ready to propose community health and wellbeing as a potential center point for further organizing. This realisation came out of several geographic iterations, where we began to think about ways to organize between neighborhood identities. This gave direction to our final map, which focuses on health centers as a point of organizing potential cooperative and community oriented activities.

It also led to the finding of the Broadway Junction concentration of key commons elements. Once this iterative process unfolded, this new space became another important organizing space. In many ways, it is possible that this could become a new terrain for displacement. Key organizing between the two spaces, with health institutions, and around health issues, like outdated boilers, and manufacturing zones that are both a health threat and an opportunity to place businesses seeded by anchor institution funding.

This essential, although unexpected finding, means that Community health may be an in common motivation in producing the Urban Commons. This is a vital addition to our overall research, in that it locates a large scale collective endeavor in the body. Health is highly personal, so much so that we often hide our health problems from each other. But if these health issues are connected to urban phenomena, as with an asthma corridor, then we can bridge the personal and the collective; plurality with what we have in common. It is no surprise that detailed data on health deteriorating elements in the city is some of the most sparse.

The group's data layered using CartoDB

The group’s data layered using CartoDB

Data Sources

The group listed the following data sources:

  • NYC Open Data: Hospital and Health Care Centers, NYCHA housing information, Cool Roofs, Boilers
  • BYTES of the Big Apple: Community District boundaries, Industrial Zones
  • US Census Bureau: Census Track information for Median Income
  • Office of the New York City Comptroller: Mitchell-­Lama housing layer

This week we covered another topic that would be useful for many of the projects happening in the class: geocoding.

To introduce the subject expansive subject of addressing (and by extension, geocoding), we took a quick look at Frank’s Compulsive Guide to Postal Addresses which prompted a conversation about what is an address specifically. We compared USPS and its utilization of things like Handwritten Address Interpretation (HWAI) to systems common to other countries, especially Japan where addressing is based not on blocks per se, but buildings’ age.

Following this overview of addressing at global and national levels, we took a look at the larger process of geocoding- essentially transforming an address expression of location to something very useful in GIS- a point possessing Latitude and Longitude attributes. We discussed geocoding ‘start to finish’; that is, data collection & formation | Address Expression > Geocode Engine > Spatial Expression:

Geocode Process- Address to Points Features

Geocode Process- Address to Points Features

Further, we covered several different approaches to geocoding ranging from a relatively robust desktop system found in, say, ESRI’s ArcGIS platform to numerous online options. For this week’s lab and assignment, we utilized Geocommon’s geocoding service for its ease and accessibility; and then segued to working with points in QGIS following a successful geocode.

Texas A&M Geoservices Geocode List

Texas A&M Geoservices Geocode List

For the geoweb perspective of geocoding, we talked about how forward and reverse geocoding are used on the web, whether you’re searching for an address on Google Maps or asking Foursquare where the pizza shops near you are. Very briefly: forward geocoding gives you a point for a place name or address, and reverse geocoding gives you a place or neighborhood for a point.

Then, similarly to last week’s discussion of BBLs, we looked at a dataset on NYC Open Data that contains addresses but no geodata. In this case we used CartoDB‘s geocoder to quickly locate a handful of the dataset’s features. It didn’t take much to run into weird addresses that threw off the geocoder:

Northwest Corner of 3rd Ave, Bronx, Kansas City

Northwest Corner of 3rd Ave, Bronx, Kansas City

Having covered the concept and mechanics of geocoding, we talked briefly about reverse geocoding. While it would not likely be useful for the projects happening in this class, it is an important part of the geoweb and the way in which place is being (re)defined by data, software, and programmers. To that end, we looked at Flickr’s Alpha Shapes and Foursquare / David Blackman‘s Twofishes reverse geocoder and briefly contrasted their approaches (eg, the former lets neighborhood polygons overlap and the latter does not).

Alpha Shape for Texas

Alpha Shape for Texas

This week we talked about a few very practical techniques that would be clearly applicable to final course projects- late in the semester, soon to be fully developed. Specifically, mapping density via QGIS; utilizing NYC’s BBLs as a common key to access a variety of NYC data, and finally, collecting data with Field Papers.

Density surfaces are an excellent mapping technique involving an usually acceptable compromise between specific XY locational data and predictive, continuous raster surfaces. They are very helpful in capturing trends across urban spaces for a variety of variables- often crime and socio-econ statistics.

As an introduction, we took a look at Doug McCune’s captivating work of a few year’s ago- ‘crime as elevation’ in San Francisco. It just so happens that SF makes public very detailed, well formed data for crime, easily accessible and perfect for processing through with QGIS. We had a fun time guessing in class the following ‘crime elevation’:

Narcotics as SF Elevations

Narcotics as SF Elevations

We also took at look at Floating Sheep’s ‘Geographic of Hate’ utilizing tweets with locational attributes as densities. This raised ALOT of questions and controversy in class regarding the methodology not so much for the density raster itself, but how the authors organized and categorized the tweets data, deeming a tweet ‘hateful’.

Floating Sheep's 'Geography of Hate'

Floating Sheep’s ‘Geography of Hate’

In the first lab portion for this week, we produced a few tests density rasters paying particular attention to the technicalities of the process via QGIS- projection issues, search radius determination, decay ratios, ect. Following class, students gathered whatever points data they could find via many NYC data sources, from 311 complaints to physical characteristics of the city, and produces an unique density raster for their variable/feature of choice.

Charles W. | Boiler Density & Age, Brooklyn, NY

Charles W. | Boiler Density & Age, Brooklyn, NY

Charles C. | Hurricane Sandy- Trees Felled

Charles C. | Hurricane Sandy- Trees Felled

For the geoweb portion of this lecture we talked about two (2) practical techniques for accessing and creating geodata.

The first is very New York-specific: borough, block, and lot numbers (BBLs), which are the identifiers that the city assigns to each parcel of land in the city. BBLs are useful to know about when working with New York’s data because some datasets on NYC Open Data do not contain geodata but do contain BBLs, and BBLs can be joined with MapPLUTO to get polygons for the parcels being referred to.

MapPLUTO BBLs

A snapshot of MapPLUTO in Brooklyn and some of the BBLs in it

One small complication with using BBLs to join a dataset with MapPLUTO is that many datasets do not have the BBLs assembled but rather have them split up into their constituent parts (borough number, block number, and lot number), for example see the Bronx Vacant Lots Cleaned table. This was a good excuse to use OpenRefine again, and we used it in class and in an assignment to zero-pad the BBL parts and concatenate them. From there, joining in QGIS is straightforward and a number of datasets on NYC Open Data are unlocked for mapping.

Next we shifted gears to Field Papers, which lets you create printable “atlases” that you can trace data on with pen, scan back in, and then trace in QGIS, OpenStreetMap, or other GIS systems.

We looked at the mechanics of how Field Papers works, then quickly looked at two examples of how it has been used: Map Kibera and Stamen’s mapping of private buses between San Francisco and Silicon Valley.

Field Papers in Kibera

Field Papers in Kibera

Field Papers being used to map private bus networks in the Bay Area

Field Papers being used to map private bus networks in the Bay Area

During this week’s assignment some students experienced issues with Field Papers, both when creating atlases to print and uploading traced and scanned atlases. These were mostly fixed quickly, and the scanned maps varied from very personal maps to case studies of areas of interest for the final projects. Even when the data collected was not useful in itself, many students found Field Papers to be a useful methodical way to look at a small area while walking.

Bonnie N.'s traced Field Papers atlas

Bonnie N.’s traced Field Papers atlas

This week we covered ‘Georeferencing’ with QGIS, and explored both the history and potential of JavaScript for the geoweb.

In order to introduce the process of georeferencing or ‘rectification’, we utilized NYPL’s MapWarper service, contemporary Manhattan and Sanborn’s historical insurance maps. Several students had extensive knowledge of Sanborn maps, and we had an interesting discussion about information that can be derived from historical maps, especially when rectified with contemporary geospatial features within a GIS.

As the general concepts of rectification were introduced, we delved into the specific steps that lead to a successful georeferenced raster utilzing GIS, in our case of course QGIS. We covered control points, displacement links; discussed the transformation types from linear to more complex transformations.

points_georef

During the lab and assignment portions of this week, some students utilized the process effectively to both enliven the Sanborn maps available for Chelsea and parts of Brooklyn, as well as rasters specific to final project and ongoing thesis themes.

Luisa M | Sanborn's recitified to Post-War housing development, NYC

Luisa M | Sanborn’s recitified to Post-War housing development, NYC

Gabrielle A. | Rectification of street use map to NYC grid

Gabrielle A. | Rectification of street use map to NYC grid

Aubrey M | georeferencing the Exon Plume to NYC grid

Aubrey M | georeferencing the Exon Plume to NYC grid