By Christianna Bennett
Artist Roni Horn once commented on the fallacies in her own work, stating that the photos of water she captures depict a solidity on the page that stands in stark contrast to the reality she perceives while taking them. (1) Similarly, many ecological systems undergo visual, physical, and structural changes adhering to timescales that are difficult, if not impossible, to perceive directly by the human eye.
Recent technologies have been proposed that will parse out the choreographies of these black-box ecological systems, identifying as precise data points the many liquids, sediments, and atmospheres that come together under the veil of the medium’s surface tension. Intensive tools have been created to allow us to observe the elusive granular structures that escape our senses at the one-to-one scale. Machine-sensing processes generate passive models that resemble ecological Jackson Pollock paintings.
It is important to note that machine sensing capabilities can arrive at strange observations that are very different from those of our human senses. A landscape-sensing machine transforms information through several planes of translation before providing recurring articulated responses. For instance, the machine first gathers information from the environment that is immediately translated into a specific virtual representation of reality. This is later, if not simultaneously, retranslated to represent itself as “what is real.” These instantaneous translations generate an unpredictable and inherently blurry feedback loop in the process, wherein alternate and unforeseen versions of reality are reproduced and begin to emerge as new incarnations of past realities and bizarre partial truths.
The following visual essay, “The CLIO Scans,” imagines what the long-term studies of one such landscape-sensing machine could yield and what kinds of abnormalities or representations might arise from these kinds of interactions, in order to offer an understanding of what real-time adaptive landscape management might look like.
CLIO2307(CLIO)’s early scans test “simple” abstraction techniques. Her initial searches scan ground conditions in an effort to neutralize the distinctions between “natural” and “human-made” interfaces. Her visualization strategies are at times rudimentary, assigning markers to mundane barriers, living and non-living alike. Matrices of strange organizations begin to occur.
CLIO doesn’t normally capture a “moment in time” as we might choose to understand it. Instead she is programmed to read a constant stream of multifaceted, temporal x-rays. CLIO’s specialty is removing material specificity from her imaging in search of the complexity of the vertical layering of living and non-living ground systems. Her scans erase the value of solidity to reveal layer diversity across multiple timescales, ephemera, and locations. CLIO’s current range is 2,307 constant kilometres and forty-eight years and her operating lifespan is anticipated to be 1,300 years.
CLIO’s neural networks churn through clarity of flow and streams of energy during her counting exercises. These are often privileged in the programming for years at a time. Counts occur simultaneously with the countless other records she is keeping, of course. Counting individual plant specimens, she records each plant and each leaf instantaneously. She is especially interested in finding shades of red and pink, even though she has not been assigned a system of values favouring certain pigments over others.
CLIO is constantly at battle with her hyper-sensitive precision settings versus finding meaning in the documentation. When asked to produce concrete imagery associated with her tasks, CLIO registers a single poppy specimen to be as important to the imaging as multiple poppies and their interference species, and all of these instances are just as important as each leaf she meticulously counts. Typically, her leaf counts occur in 3 km batches.
CLIO’s more advanced visualizations of temporal sequences over time conflate solid, liquid, boundary, and instance. In comparison to her early tests, which were made to obscure categorizations of the human-made from the naturally occurring, later scans reveal streams of permanence and impermanence divorced from material reality. Chemical plumes inhabiting aquifers travel for decades across grounds and through layers and persist through time. Short lived, yet significant to her readings, are individual plant species. She simultaneously marks the lifespans of numerous perennial flowers in her temporal readings. Markers are also placed to register inanimate markers on the ground: boundaries, interfaces, foundations, poles, paths, and striping. No matter the artificiality or other forms of legitimacy of the trace, CLIO picks up the evidence.
Created primarily for simultaneous physical and environmental morphological analysis of human and non-human ground layers, CLIO will, on occasion, be asked to cross-reference her monitoring activities with text-based analyses of research papers or performance scores. These readings are often prompted by the various programmers’ input over time to test for misidentification bugs. It is particularly challenging for CLIO’s declassifying systems to parse out her signature high-precision and abstract readings from information embedded in a linguistic task. CLIO’s analysis of text, after all, is completely removed from its given symbols, signs, and meanings as these characteristics are assigned for the use of language, a function she does not perform. Rather, CLIO will typically produce
a structural analysis of the text as a series of visual overlays, with limited associative distinctions and an emphasis on contingencies in her temporal scans. Text readings are therefore sophisticated matrices of definition, declassification, and remediated scores of meaning concerning the vocabulary and the environmental monitoring data.
CLIO will automatically assess her monitoring standards by running several tests. One of the most common assessments is the Pattern Recognition Scan. By repeating the reading of layered data sets multiple times, CLIO will self-detect incongruities in the recordings. Not to be taken lightly, the Pattern Recognition Scanning and its assessment must be done as time continues to go on and thus, as new recordings fold into the frame. The assessment attempts to understand trajectories of materials from past to present, thus honing CLIO’s ability to inform the kindred Time Machine Pan Series in its tasks aimed at predicting future hybrid human, non-human, living, and non-living materials and other future oeuvres.
All images by Christianna Bennett
(1) Roni Horn, Another Water (Göttingen: Steidl Verlag, 2011), 125–127.
Christianna Bennett is a landscape designer and instructor in Troy, New York. She is spearheading research that focuses on interpreting conditions and representations of water, including research of living water ecologies and visual and temporal bodies of knowledge related to past and present aqueous phenomena. Related studies include provocations for defining expanded systems of public landscapes in peripheral areas, and reconsidering programmatic performance over time in contested and ambiguous territories.