Impossible Maps

Week 13: American Landscapes

Trash. We toss it into the bin, to the bag, to the curb, and then to who knows where? But we do it everyday, and I was curious to see the dumping grounds. What do they look like? Where are they? How much do they contain?

So I built a tool to help me visualize some of the country's solid waste landfills, around 2,450 of them. Using the Google Maps API and data sourced from the Landfill Methane Outreach Program (a voluntary EPA program that identifies potential sites for the recovery of methane emissions as a renewable energy source), I launched an Instagram bot on Earth Day, @americadumps, to share satellite images of each site along with its state, latitude and longitude, whether it's open or closed, and its trash by the tonnage. More on the why and the how (including the code) in last week's post here.

Instead of try to read all the images at once in an image editor like Lightroom, I choose Instagram because the platform is designed specifically for pictures with corresponding captions. Setting my own delivery pace allows me to spend a deliberate amount of time with each image and share them with others in the process.

Distortion accompanies any type of representation, especially and including visual ones, and certainly we've discussed in this class how satellite imagery is processed and stitched together. In spending considered time with these landfill views (as of this writing there are 416 posts) in conjunction with their stats, I appreciate how utterly flattening the landscape is collapsed into the picture space. After the flattening, I noticed the numbers. What does it mean to cover 500,000 tons of waste? 1,00,000 tons? or even 100,000,000 tons? These are awesome figures: how does one begin to understand solid waste management at this colossal scale? The views from Google Maps isolates the sites from the very communities they serve, and so my focus became: how are the landfills situated in the landscape in relation to their communities?

From the records with available data, I decided to make some pictures of the ten largest landfills from this dataset, again as tool to continue my learning process.* After trying Google Earth Pro and Bing, I visited Google Maps through my browser and employed the tilt feature to reveal the horizon and to try suggest some depth. Again it's a great distortion, but I do appreciate Google's atmospheric perspective qualities to help me attempt these points of view. I aimed to locate each landfill with a sightline to the nearest metropolitan area. If lucky, I found a baseball diamond or tennis court in the foreground to provide a sense of scale.

Following up on each site through YouTube videos and actual photographs impresses upon me the enormity of these structures, and I'm finding ever-more questions to explore, including how to scale the data so that it's human-relatable. For example, how many trash bags fit into a garbage truck? How many tons do trucks transport? How many tons are deposited in a day, a week, a year?

Six of the locations are closed or soon-to-be, and my next questions also include what happens next? Where does the trash go now? How are the old sites maintained--what about those methane emissions and the prevention of groundwater contamination from leachate? Of the closed sites posted so far on Instagram, I looked up a few to find conversions into parks for humans, environmental restorations for local flora and fauna, and developments into golf courses, resorts, and even an airport. The story continues...

*A reminder for future Ellen that you made this decision after revisiting the splendid works of the celebrated American landscape painter, Thomas Cole, at The Met. Some of his paintings preserve an idyllic version of the wilderness and others foretell environmental damage due to encroaching development. 

@americadumps
Code on Github
View Slides

Related References
How Landfills Work
Land of Waste: American Landfills and Waste Production
Garbology: Our Dirty Love Affair with Trash by Edward Humes

...added during summer:
Invisible Menace, PBS NewsHour, 7/11/18 (touching on methane & landfills) 
Designing Waste: Strategies for a Zero Waste City, Exhibition at the Center for Architecture
Zero Waste Design Guidelines (for NYC)
 

Week 12: America Dumps

During my Vintage Fountains project, I enjoyed the anticipation and reveal of each new fountain. Sure I could visit the image results page of any search engine, but with that project I found myself spending time with each individual picture, considering the life of the object(s) pictured and the photographer’s decisions. I enjoyed the extremely slowed-down, one image-at-a-time pace. But that was on Twitter, and right now Instagram rules the photo sharing scene.

I’ve been on Instagram for two weeks now learning how to scrape images from public hashtag pages, only to remix and throw them right back from whence they came (see @autoechoes). In the process of playing, I observed content from some of more popular hashtags. There’s a tag for nearly everything and plenty of skin, faces, food, and camera beautiful landscapes and lifestyles. I found the quantity of posts astonishing: at the time of this writing, over 341 million in #selfie, 435 million in #happy, 520 million in #photooftheday, 746 million in #instagood, and 1.2 billion in #love. It’s a positive place, this Instagramland. (By comparison only 870,000 in #unhappy and 24 million posts in #sad.) I found the likes and followers an alluring distraction (apparently for some the temptation is too great). I asked friends and colleagues about their Insta experiences. Many shared pics to connect with friends and family and/or to participate in threads related to interests and hobbies. Some commented on self-branders and corporate marketing strategies.

After a week it all started to look about the same (smiley, centered, saturated, squared), and I started to wonder about what I was not seeing. If so many people are using this platform (are you up to one billion, yet, Instagram?), then could it be used to bright to light places far removed from folks' like-radars? Places rarely sought out in real life, much less shared online for followers. Like landfills, for example. Waste of all kinds is universal. Humans have been burying (and sometimes building on top of) their trash for thousands of years. It’s one of the hallmarks of civilization. Why don’t we discuss it more, specifically about how it allows society to function…or in the emergence of Anthropocence, maybe eventually not so well? Is there an unsustainable cost to coveted #lifestyles?

Launched in honor of Earth Day, @americandumps posts satellite views of some 2,450 solid waste landfills in the United States. Included with each image is its state, latitude and longitude, whether it's open or closed, and the amount of waste in place* in tons. All data was sourced from Google Maps and the February 2018 Data Files from the Landfill Methane Outreach Program, a voluntary EPA program. LMOP “works cooperatively with industry stakeholders and waste officials to reduce or avoid methane emissions from landfills” by “[encouraging] the recovery and beneficial use of biogas generated from organic municipal solid waste. According to their database, the total amount of tonnage for sites in which that data is available, is currently over 11 billion tons of trash.

My project uses two scripts: one to retrieve the satellite image of each site and the other to upload it to Instagram. A bit about my process (all code linked below): 

  1. After retrieving the LMOP data, I added my own ID field, changed state abbreviations to full names, removed spaces from those full names to prep them for the hashtags, and duplicated the latitude and longitude columns, inserting “Data Missing” into the empty fields (also for Instagram caption display). Afterwards, I formatted the file as CSV and then converted it to JSON
  2. Next, I wrote get_images.py to iterate through each landfill record in the JSON file and call the Google API with the latitude and longitude coordinates of each site. 
  3. With that working, I downloaded all of the images at two different zoom levels, 15 and 16, to compare. Though I prefer the detail at zoom 16, sites are less likely to get cropped at 15. In addition, 15 provides greater context, showing how each landfill is situated within the landscape and its size compared to any surrounding community.** 
  4. Then, I built upload_images.py to retrieve each satellite image and post it to Instagram along with corresponding information. Hashtags were chosen because of their relevance and popularity: combined their total posts sum to over one billion. 

Of note, I came across this error early during upload testing:

Request return 400 error!
{u'status': u'fail', u'message': u"Uploaded image isn't in the right format"}

Turns out that Instagram refused photos straight out of Google Maps. Somehow it occurred to me to try opening and saving the images as new files using the Pillow library in get_images.py, and that did the trick.

*This report defines waste in place “as all waste that was landfilled in the thirty-year period before the inventory year, calculated as a function of population and per capita waste generation.” 
**Unfortunately I forgot to switch the zoom back to 15 until 157 images were posted.

@americandumps
Code on Github

Week 11: Impossible Representations

 Screenshot from  Esri's Satellite Map

Screenshot from Esri's Satellite Map

D’Ignazio’s 2015 article, "What Would Feminist Data Visualization Look Like?", gets right to the heart at why maps are so darn impossible. Her design proposals for “more responsible representation” in data visualization ask us to consider how to make known the uncertainties, the missing, as well as the flawed methods and tools employed in their construction. She calls for a display of the motivations and decision-making process, as well. Finally, she asks how representations might allow for interrogation—in the context of this class: how can we make make maps that are fluid and capable of presenting “alternative views and realities?” 

She describes interactive data visualizations as “currently limited to selecting some filters, sliding some sliders, and viewing how the picture shifts and changes from one stable image to another as a result.” Again considering this class, how can we imagine maps to be more interactive than providing similar cosmetic choices (perhaps a better word to use is, reactive). I’ve enjoyed considering interactivity during my studies at ITP, and for me it it goes beyond pressing a button to light a LED or walking back and forth in front of a responsive projection of myself. Interactivity is a medium of expression, and its meaning arrives out of connecting and engaging with others. So then how can we imagine maps to be interactive? (Wait, does my Waze app count? Maybe. I would call it more useful than meaningful or expressive, though.)

Speaking of challenging the representation of data, this first reading was a useful primer for the next: part of an introduction to Kurgan’s book, Close Up at a Distance: Mapping, Technology, and Politics, in which she illuminates some historical motivations and work behind the production of satellite imagery, noting that they are “come to us as already interpreted images, and in a way that obscures the data that as built them.” Though we’re now used to seemingly seamless high-resolution imagery of our Google Earth globe, it’s really a collage of heavily rendered composite photographs from a variety sources and rendering methods. Renderings that are as much scientific as they are artistic. There is always a distortion in any representation, and certainly in any image (ah, the impossibility of photographs). The question is how to somehow deliver the metadata and decisions with the imagery to help viewers understand their own interpretations in the context of those distortions. 

For my final project, I’m interested in working more with satellite imagery, but in what capacity I’m currently unsure. Curious, I found a map of the satellites orbiting the planet. There are A LOT, nearly 17,000 with more on the way. I also wondered about the breakdown between the artistic and scientific processing of satellite imagery. I read the mentioned Charlie Loyd article, “Processing Landsat 8 Using Open-Source Tools, which describes many decisions for processing satellite imagery (brightness, contrast, adjusting midtones and individual color channels, and sharpening), similar to developing digital photos in Photoshop or Lightroom and not objective. (What exactly are the scientific aspects of this type of processing anyway?) Making my own map tiles seems ambitious to tackle, but it's fun to consider covering the world in imagery of my own design. A conversation with a classmate sparked ideas about collecting and comparing imagery from different periods in time over the Rio Grande (ooh, representations of nation state borders). Finally, a random but connected thought: so how long until we get to see live global satellite video? What happens (has it already?) when you can’t commune with nature alone because of the eyeballs above? You can already watch a livestream from the International Space Station here (and screenshots from 4/13/18 at 1:30am below). I'm looking forward to considering all of this further!