22000507's blog

Tag: fieldwork

  • further developed investigation

    Following the feedback from my recent tutorial, I returned to Purchese Street for a second site observation. This time, I noticed a whole new range of discarded items along the pavement that I hadn’t documented before. 
    I used my camera to photograph these newly discovered waste items in detail, capturing their material properties, brand logos, and condition. To prepare for a more structured visual analysis, I also took precise screenshots of my GPS location on Google Maps for every item I photographed. These location coordinates will serve as the foundation for creating a comprehensive site map in the next stage, helping me explore potential correlations between specific waste items and their spatial surroundings. 

    In addition to individual litter items, I also spent time identifying and mapping the static infrastructure along the street—specifically public trash cans and clusters of bulky fly-tipping. I recorded their exact GPS coordinates on Google Maps alongside the photographs. 
    My goal now is to overlay these two maps: one showing the distribution of everyday street litter, and the other marking public bins and large abandoned items. By comparing these spatial layers, I hope to uncover potential patterns and gaps—such as whether litter accumulates in specific “blind spots” far from public trash cans, or if the presence of bulky waste actively encourages further illegal dumping in the immediate area. 

    To move away from sorting things just by how they look, I tried a new way of grouping the waste based on what the items actually are: drinks, snacks, and tobacco/vaping packaging.
    Sorting them like this made a big difference. It instantly showed what people are usually buying and consuming on the street. Instead of looking at them as random trash, grouping items by product type helped me see how everyday habits directly shape what gets left behind on the pavement.

    Following my tutor’s feedback, I also carried out a deeper material and economic audit of the collected waste. I analysed each item based on its brand, estimated price point, and material composition. 
    To make sense of these relationships, I created a data visualisation mapping all the items onto an X/Y scatter plot. The X-axis measures recyclability (ranging from fully recyclable to non-recyclable), while the Y-axis tracks the price range of the original products. By plotting these elements together, I aim to uncover whether there is a correlation between low-cost disposable items, brand accessibility, and their eventual likelihood of ending up as non-recyclable street litter. 

    10.2 Tutorial Feedback

    During my latest tutorial, my tutor pointed out that my current color-based knolling remains somewhat on the surface—functioning more as a standard visual archive than a personal research tool. To transform this raw data into something uniquely my own, my tutor suggested a more intimate, graphic approach: high-resolution scanning. By scanning the collected packaging instead of just photographing it, I can zoom in on tactile details—focusing on local typography, brand logos, print textures, and signs of wear-and-tear.
    To help me move beyond superficial classification, my tutor introduced two key reference works:
    1.Batia Suter (Parallel Encyclopedia 2): Demonstrates how juxtaposing scanned images and visual fragments can build unexpected narratives beyond mere categorization.
    2.Anthony Burrill (Look & See): Shows how zooming in on everyday vernacular typography and graphic language can uncover the cultural personality of a place.
    Inspired by these approaches, I am shifting my knolling process from a passive sorting exercise into an active method of visual storytelling. By curating and reassembling these scanned graphic components—logos, text fragments, and material textures—I aim to develop a distinctive graphic language that reflects the street’s socioeconomic identity while making the work truly my own.

  • Site: Purchese Street

    Located close to King’s Cross, Purchese Street sits within a very different social and commercial landscape. Despite their physical proximity, the two areas reveal contrasting forms of retail, public space and everyday consumption.

    Spatial Observation

    View towards King’s Cross from Purchese Street.

    Method 1: Knolling

    My initial fieldwork began with a stark spatial contrast: as I walked away from the privately managed King’s Cross area into Purchese Street, I noticed a sudden surge in street litter. To document this visual anomaly, I photographed the abandoned items, printed and hand-cut their forms, and organised them into color-coordinated knolling layouts in my sketchbook. This tactile mapping process allowed me to analyse both their material composition and visual presence.

    Method 2: Mapping human movement

    After looking at street waste, I turned my focus to the people walking through the neighborhood. To record how people move along Purchese Street, I created a simple drawing system. A straight line shows someone walking at a steady speed, while a wavy line shows them slowing down or hesitating. When someone stops or looks around, I marked it with star points or side-to-side arrows. Instead of just tracking where people were going, this method helped me notice how the street environment naturally changes people’s walking pace. 

    Method 3: Documenting Bulky Fly-Tipping on the Street

    Beside small packaging, I also noticed larger discarded items along the street, like pillows, a washing machine, a trash can, a scooter, and a shopping trolley. I photographed these bulky items and categorized them in my sketchbook along a scale. Seeing intimate domestic objects and heavy appliances left out on the pavement highlights how private household waste overflows directly into public spaces. 

    9.25 Tutorial Feedback

    During my tutorial on September 25, I shared my initial experiments with color-based knolling and received some insightful feedback from both my tutor and peers.
    My tutor noted that while arranging waste by color is a strong visual starting point, I shouldn’t limit myself to just one dimension. They suggested pushing the analysis further by categorising items through brand identity, materiality, and price point. Meanwhile, my peers recommended taking a more spatial approach by mapping the exact locations where each item was found and recording their physical dimensions.
    Taking these suggestions forward, my next step is to analyze the collected waste by brand and price, while mapping their precise locations on site. My goal is to see what new spatial patterns and socioeconomic stories might emerge from these deeper layers of data.