{"id":10224,"date":"2018-08-01T00:03:49","date_gmt":"2018-08-01T04:03:49","guid":{"rendered":"http:\/\/studentwork.prattsi.org\/infovis\/?p=10224"},"modified":"2018-08-03T12:21:19","modified_gmt":"2018-08-03T16:21:19","slug":"impact-of-landmarks-designations-on-surrounding-areas-in-brooklyn","status":"publish","type":"post","link":"https:\/\/studentwork.prattsi.org\/infovis\/projects\/impact-of-landmarks-designations-on-surrounding-areas-in-brooklyn\/","title":{"rendered":"Impact of Landmarks Designations on Surrounding Areas in Brooklyn"},"content":{"rendered":"
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Poster featuring small multiples.<\/p><\/div>\n

Introduction<\/h2>\n

The demolition of one of New York City’s most iconic structures, Penn Station, led to the Landmarks Law and the creation of the NYC Landmarks Preservation Commission (LPC). Created in 1965, the LPC is charged with protecting historic and culturally significant\u00a0sites throughout the five boroughs.\u00a0 This is done by identifying landmarks and historic districts then regulating them after designation.\u00a0 Besides safeguarding historical value, the goal is\u00a0also to stabilize and improve property values of these areas since most of them are vulnerable to advancing urban development.<\/p>\n

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Southeast view of Penn Station. Library of Congress.<\/p><\/div>\n

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Madison Square Garden is built on the site of the old Penn Station. Wikipedia.org<\/p><\/div>\n

I was interested in exploring whether or not being landmarked had made the impact on properties as the LPC intended.\u00a0 Could landmarking have a positive effect on not only home value but the community? And if so, what data would illustrate it? I also wondered about the impact on residents.<\/p>\n

I began by looking through the current historic districts and their dates of designation. I noticed that the most recently designated ones have been in areas where gentrification has been the strongest. I decided to focus on the borough of Brooklyn since it looked to be the most active.\u00a0 I also chose Brooklyn for personal reasons since I live in the Crown Heights North Historic District. This made it easy to discuss the impact of Landmarks with the residents.<\/p>\n

For visual inspiration, I looked at the NewYorkitecture<\/a> site which is a great resource for learning about historical sites in the city.\u00a0 I also viewed the NYC LPC’s “Discover New York City Landmarks<\/a>” page that allows you to browse through information on several designated buildings and districts when you click on marked locations on the city map.\u00a0 I liked the focused simplicity of NewYorkitecture’s specific google maps but the pop-ups on the LPC site adds a great deal of information in a single map.<\/p>\n

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NewYorkitecture’s Google Map for Noho<\/p><\/div>\n

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NYC LPC’s “Discover New York City Landmarks” Interactive Map<\/p><\/div>\n

Process<\/h2>\n

Data Collection<\/strong><\/p>\n

Focusing on Brooklyn due to the spike in both population and home prices, I decided to map data on the block level since this was the most comparable in size to historic districts and would provide the most insights.\u00a0 All of the current landmarked areas were designated before 2012, so I felt that looking at the 5-YR average from 2012-2016 should give a good picture of any growing impact.\u00a0\u00a0Using the Fact Finder site that utilizes U.S. Census information, I looked at median home values, owner-occupied residences versus renters and length of residency.\u00a0 I hoped that mapping this information against the historic district boundaries would show some relationship between these values.<\/div>\n
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New York City Census Blocks. NYC Open Data<\/p><\/div>\n<\/div>\n

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After downloading the datasets from FactFinder, I needed to find a shapefile with a corresponding identifying field.\u00a0 This proved to be challenging because many of the shapefiles I downloaded from NYC Open Data did not use the same naming system to identify the census blocks.<\/div>\n
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The biggest challenge in my collection of datasets was finding ones that were compatible. I did not easily find a shapefile that fit the datasets for the block level for the FactFinder data. I first looked to NYC Open Data for their census block shapefile. Looking at their descriptions, one would think they would be a perfect match.\u00a0 Both claimed to be from the 2010 U.S. Census. There were several issues.<\/div>\n
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The first being that the Open Data ID field used a single digit number for the borough\/county whereas the ASA dataset used a five digit county number. The tract numbers seemed to be in the same format but I hit another hurdle when it came to the block numbers. ASA gave them a single number and NYC Open Data gave them four digits with the first number being the borough number. After identifying a pattern, I changed the block ID in the ASA dataset to match the format of the Open Data map in OpenRefine using GREL.\u00a0 Applying the dataset in Carto only showed roughly half of the blocks.\u00a0 After trying a few rearrangements of ID fields in OpenRefine, I renewed my search for another census block map.<\/div>\n
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Missing census blocks when appending FactFinder dataset against NYC Open Data shapefile. So frustrating…<\/p><\/div>\n<\/div>\n

I eventually looked for another resource and discovered the TIGER\/Lines site that matched one of the ID fields from the U.S. Census sites.\u00a0 Although the FactFinder site had referenced the 2010 Census block map, I found that a 2017 map from the new site matched easily with the dataset.<\/div>\n
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I also needed to do some massaging of the data through OpenDefine since the information wasn’t in a format I could use right away.\u00a0 I created new columns using GREL to create percentages for long-term residents and owner-occupied homes.<\/div>\n
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Interviews<\/strong><\/div>\n
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Two brownstones in the historic district with obvious landmark violations. Google Streets.<\/p><\/div>\n

Speaking to residents, I got a few different perspectives on Landmarks that aren’t evident in the datasets I worked with. Annette had lived in Crown Heights for 15 years and worked with the community to designate Crown Heights North as a historic district. She spoke mostly of residents that attached garages or painted their brownstones garish colors.\u00a0 It seemed that the upside for her was that landmark regulation would work much like an HOA in a suburban neighborhood.<\/p>\n

Other residents, such as Janine, saw landmarking as a way to stop developers from coming in and driving up the prices.\u00a0 A brownstone in a landmarked area cannot be demolished and replaced with a modern building.\u00a0 This makes homes in\u00a0historic districts less attractive to investors. Not everyone sees it as a good thing. Lorin is a real estate lawyer in the same area. He finds that the LPC can be obtuse when it comes to aesthetics versus safety.\u00a0 In one case, a client had replaced a front door with a more secure one due to criminal activity. LPC insisted the old door be installed and his client apply for a new door before installing it.\u00a0 He felt this put the families inside in danger for the sake of historic integrity.\u00a0 Lorin also mentioned that some residents felt that landmarks prevented the creation of more affordable housing by inhibiting development.\u00a0 Of course, by my own observation, any new buildings in the area do not seem to target this income group.<\/p>\n

Data Visualization<\/strong><\/p>\n

I created small multiples in Carto to illustrate how the areas around and within historic districts varied in regard to home value, home ownership and length of residency.\u00a0 I brought in the shapefile of the historic districts form NYC Open Data and used it to create outlines on the top layer.\u00a0 After importing the datasets from FactFinder, I linked them with the shapefile containing the census blocks.\u00a0 I used monotone colors to show intensity.\u00a0 With the shaded areas of census blocks against the boundaries of the districts, a viewer could see a relationship, if any exists, between census data and landmarked areas.<\/p>\n

Tools<\/strong><\/p>\n

Carto<\/div>\n
Google Sheets<\/div>\n
OpenRefine (GREL)<\/div>\n
Evernote<\/div>\n

Sources<\/strong><\/p>\n

United States Census American FactFinder<\/a><\/div>\n