rebecca's WIP

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digital mapping

Maps_FinalPresentation.001

Waterline is a map of a walk that I took along part of the border of Hurricane Sandy’s flood zones in New York. Using a map of the inundated areas (based on data sourced from NYC Open Data), I traced part of its edge along a route from Brooklyn Heights to Red Hook through walking. I began this project as part of my final for Digital Mapping and I hope to continue to develop it, eventually covering the entirety of the flood zone’s edge and mapping it through crowdsourced walks.

This project came out of an early assignment I did for the class, which was a simple map of the flood inundation zones from Hurricane Sandy from GeoJSON data I found online.

Maps_FinalPresentation.002

At the same time, I was (and still am) doing a lot of research around memory and urban space related to my thesis.

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I had the idea to do something related to walking, as a way to explore lived experience of geospatial data in our urban environment, as well as the relationship between the scale of data and the scale of my own body. I thought this might be an interesting way to map the invisible – the traces of something that happened, traces we can no longer see — and try to spatialize it for myself. Here are some of the questions I posed to myself:

questions

As a first attempt at answering, or at the very least complicating, some of these questions, I decided to take a walk along part of the border of the flood zone from Hurricane Sandy based on the data I had mapped. I would take the walk, document it with images, and then make my own map tracing the outline of the inundation zone by tracking my location while I walked.

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dirtyrestaurants3

The map I started making last week now lives online! I got my Mapbox account sorted and was able to push my tile designs to the cloud.

I also got my data working as I needed to, added popups and marker icons, and figured out how to customize some of the CSS on my popups. There’s more I want to do, but this is where it’s at for now.

Check out my live map here:
http://rlieberman.github.io/DigitalMappingWeek4/

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Over the past few weeks, I’ve been looking at a lot of maps and gathering the ones I love. This has been the first time I feel excited about data and the possibilities of working with geospatial information. Here is a preliminary list of my favorites (Rebecca Solnit wins for the way she juxtaposes different kinds of information in a poetic way).

Rebecca Solnit, Death and Beauty (from Infinite City)
deathandbeauty

Zach Schwartz, Death Map
http://gothamist.com/2015/10/28/death_mapped.php

Ingrid Burrington, Center for Missed Connections
http://centerformissedconnections.info/

This map by Alfred Wainwright
alfredwainwright


NYPL, Old NYC: Mapping Historical Photos from the NYPL
http://www.oldnyc.org/

GPS Self Portraits
http://www.theguardian.com/technology/blog/2008/may/25/theworldsbiggestselfportra

Kate McLean, Sensory Maps / Smellscapes
http://sensorymaps.com/
http://sensorymaps.com/wordpress/wp-content/uploads/2015/10/Smellwalk_Intro_Kit_%C2%A9KateMcLean_2015.pdf

Sharon Mattern, Maps as Media: Class Syllabus
http://www.wordsinspace.net/mapsmedia/Mattern_MapsAsMedia.pdf

MIT, Critical Cartography (so many links!)
http://slab.scripts.mit.edu/wp/links/critical-cartography/

GeoGuessr, a Google Maps guessing game
https://www.geoguessr.com/
http://www.slate.com/articles/technology/future_tense/2013/05/google_maps_guessing_game_geoguessr_tips_and_cheats_to_beat_the_game.html

Dennis Wood, Everything Sings: Maps for a Narrative Atlas
http://sigliopress.com/book/everything-sings/

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Our assignment this week was to use Mapbox Studio to create our own map tiles and add a data layer if we wanted to. To make a long story short, my Mapbox Education account isn’t yet activated so I can’t upload my custom tiles to make a basemap at this present moment. While I work stuff out with my account, here’s a post on my process along with a screenshots of my tiles, which I think are pretty lovely.

First things first, I had a dataset in mind that I found last week — a CSV file of NYC restaurants organized by inspection rating with comments — and I knew I wanted to do something with it for this week’s homework. The CSV file had all of the information I needed except for latitude and longitude, which meant I needed to use a geocoding script to turn the addresses into geospatial data.

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Danielle was also working on something similar, and she passed along this tutorial on geocoding using the GeoPy library. I used the code from this tutorial as a basis, and of course ran into a ton of errors, meaning I had to modify it a lot.

I had some issues iterating over all the rows in my CSV that Mimi was able to help with, but the weirdest errors I was getting was that GeoPy seemed to be *very* finnicky about how the original addresses were formatted in order to return a lat / long pair. For example, when something was written “West 33 Street”, I would get an error in terminal, but when I reformatted the address to “West 33rd Street”, I got back data. It was a bit annoying and very time consuming to have to manually edit all my data in this way, so I imagine there has got to be some better way to do this.

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For this week’s homework, my goal was to make a simple map with Leaflet and add geospatial data to it. I haven’t done a lot of work with data at ITP, so this was my first time really searching for interesting data sets and digging into different kinds of formats.

I spent a ton of time browsing on NYC Open Data  and I found a number of data sets that were really interesting to me (including a dataset of all the restaurants in the 5 boroughs with their sanitary ratings and comments from their inspection. Eek).

I found a dataset from the tree census in NYC that lists the location of all the trees around the 5 boroughs and I decided I wanted to map that. I was inspired by Rebecca Solnit’s maps of San Francisco, in particular the one she made that maps cypress trees alongside homicides around the city in a given year. The idea of using that kind of juxtaposition in a poetic way was really interesting to me so I wanted to replicate it.

Unfortunately, my data set of just trees in Brooklyn (geoJSON format) was way too large. It crashed my browser multiple times even just trying to look at it in a geoJSON visualizer. Somehow, I loaded it into one of the tools (I forget which one) and was able to generate this beautiful dotted map.

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I wanted to get something up and running for this week’s assignment, so I abandoned the trees temporarily and moved on to a different dataset. I decided to map the flood zones in the 5 boroughs from Hurricane Sandy. Getting the data to load was not a problem but I had issues figuring out the syntax to style the geoJSON. Mimi helped me with the styling syntax so I was able to change the color of the areas and the stroke.

Here are the results!

Screen Shot 2016-02-28 at 11.20.16 AMScreen Shot 2016-02-28 at 11.20.30 AM

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This past week, I caught up on my Digital Mapping homework and made a really simple base layer map.  I used tiles from CartoDB and mapped four different places I’ve lived. I added a simple popup to indicate the location.

My full map is here.

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Questions that came up as I was building this:

  • Do you need to add a new tile layer for each map you’re doing, even if it’s the same tiles for each one?
  • What is Mapbox API? Different than Leaflet? Does Mapbox have its own tiles? Seemed like you needed a token to use them
  • Is there any easier way to customize the Leaflet pop up styling besides this?
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