I’ve been looking for places to extend my TrainPans project beyond its current focus on the North-East. Los Angeles seemed an interesting place to try. This iconic bastion of automotive suburban sprawl has an ambitious multi-decade plan to build out the public rail system of Greater LA, both the metro and regional systems. Importantly from my point-of-view, much of LA Metro, the local version of a ‘subway’, actually runs on the surface which frankly is much more engaging photographically than your typical ‘underground’. On my first working trip in February of 2018 I did a little bit of everything, taking the pulse on 6 of the Metro lines as well as the MetroLink commuter rail, which connects Union Station in downtown LA to San Bernardino, Irvine, Lancaster and Ventura and other points.
There is something different about the LA images compared to what I’m getting when working in the North-East – space for one thing. There is so much of it in LA and it makes the images different; longer, thinner feeling, not jammed up like out East. And this stretched out, repetitive quality is emphasized by the flatness of the land where you can see out to the horizon in the distance. Walls are another thing – there are so many. They line the tracks, sometimes up close, but often 50 yards away. That’s how much space there is. You don’t feel the pressure to build right up at the edge of the tracks. The trains are different too. MetroLinks are double-decker, which changes your point-of-view. You’re looking over walls and down from above. Then, in the places where there are no walls lining the rails, there are the industrial walls – the endless container transfer facilities and big box stores one after the other. I suppose it’s unsurprising that the physical and social geography of the city imposes itself so strongly even on a photographic process where the photographer’s ability to shape the photos is strongly constrained by a rule set, and where the images themselves are produced by an agnostic algorithm. The way the resulting images just feel different points out how fundamental the space we live in is in the human condition.
See also: TrainPans – LA for additional images.
TrainPans: Glitch Stitch contains a selection of related work, mostly from the project in the North-East.
TrainPans – Process Overview
The TrainPans project is a way of exploring, or mapping, digital-visual threads of impressions into long horizontal images using the iPhone’s panoramic photo stitching feature. This camera setting works a bit like a Xerox copier, first recording and then sequentially pasting together many thin photographic slices in order to create a final image. My approach, attaching the camera to the train so it moves perpendicular to the subject matter moving by outside, ‘breaks’ the camera’s algorithms and the resulting photos are ‘Distressed Compressions’ which as a whole document the entire trip. The individual images don’t happen in an instant. They take from just several seconds up to more than a minute to expose. The train might travel 100 yards or several miles in a single image. It depends upon the subject matter passing by outside. I don’t manipulate the images other than cropping and color correction.
This ‘glitch stitching’ process can be used from any moving vehicle. I use the rail system as a platform to provide a structural underpinning to the work. Rail both cuts through, and joins, a city and region – the movement of the train maps time to distance/space. In the North-East there is also a ‘historical time’ element to this process, but less so in LA – there is just so much space and the overall cityscape so ‘new’ that you don’t have the sense of looking back a century as you do traveling up the Hudson, passing factories and power plants built in the era of Thomas Edison. In short, I’m using a city’s commuter rail system as both an organizing principle and metaphor for movement and connectivity. These rails cut through cities. You move fast. You don’t dwell on the particular. Looking outside, a cascade of sequences/impressions move inexorably past, sometimes rapid fire, sometimes evolving slowly at a distance.
The human hand, my hand, is most clearly seen in the editing. While the generation of the images is based on a conceptual framework, I edit with a social eye for meaningful context. In other words, while the visual-conceptual idea I’m working with here is based on a compression of layers of time and space, the best images have a viewpoint. There is the minuscule man at the shore of a vast concrete LA River, the clean, white, empty space of a Target warehouse jammed up against a suburban crush of homes, the anonymous car pieces zipping down the freeway with patches of home and bedroom windows floating above, the road and a distant endless wall hovering like a mirage in the desert.
At times I wonder who’s doing this project, the computer camera/algorithms or myself. I’ve structured the work/capture process to be somewhat mechanical and out of my control – starting each new capture as soon as the one before completes, i.e. not purposely framing images or timing the process. Yet I do the editing, choosing a single image out of thousands of impressions the camera/algorithms have recorded for me to review. I think that’s an interesting question. There is a symbiosis, but ultimately, I have a hard time seeing Artificial Intelligence coming up with the ability to understand the meaning that individual images have to the human viewer. It’s ultimately not just about structure in a frame, but about what an impression speaks to the human condition.