Bibliography

Artworks and Exhibitions

He looks up.

Daniel Schraik is always looking up at the forest canopy. He observes how much light is falling onto the forest floor, and how much the trees are swaying in the wind. He needs the forest to be at an absolute standstill to get a sharp image. He is doing a ground truth measurement. 

The machine he is using to capture the forest does not have the fast shutter of a camera. This may not be a fair comparison, of course; the two apparatuses operate on entirely different mechanisms. 

Daniel stands next to a terrestrial laser scanner. Terrestrial laser scanning is a remote sensing measuring device that creates dense point clouds of the observed object. It is the state-of-the-art standard for vegetation monitoring. The machine emits a beam of laser towards the target, which then detects the reflected beam. Measuring the time needed for the laser beam to travel, the scanner computes the distance between the target and the object, thus creating an XYZ coordinate of one point of the scene. The machine repeats the process until it finishes scanning the whole scene. The end result is an assemblage of points, a point cloud, and one that represents 3D space. 

Each scan takes a couple of minutes to complete, so it is crucial that the forest is at a standstill; otherwise, the point cloud would be recording the movement rather than the space. The slightest movement creates a ‘smudge’ in the image: noise in the data.

I look straight ahead, with my camera pointing at him. I look at him, unaware of any breeze but definitely cognizant of the swarms of mosquitoes; it is a humid summer night. I work on a different timescale than Daniel does. I set my camera shutter to 1/60 second for this kind of wide portrait, sometimes even slower — to let as much light into the camera as possible in this dim environment. I know that if Daniel stands relatively still, the shutter speed should be enough to freeze him in the frame. I click while he scans.

Photographers, of course, care about image sharpness and details, and do everything to avoid blur. To a photographic process, blur is a source of noise. Ansel Adams, a household name in photography and a member of Group F64, devised the famous zone system to maximize tonal details (Adams 1948: 18). The zone system codifies the tonal range of a scene into eleven zones, from the darkest black to the brightest white. It provides a programmatic framework for photographers to consider the optimal exposure for a given scene, so that a photograph retains the maximum amount of detail across an extensive tonal range. The visual effect is achieved using a small aperture, allowing the resulting image to contain as much detail as possible. As a result of these methods, Group F64 became known for its immaculately crisp images of natural landscape1.

Daniel waits for the wind to stop; I adjust my aperture.

Artists are celebrated, it’s because of a particularly innovative ways of creating images, of depicting the human condition. Their works are hung on museum walls for viewers to gaze upon, to ponder, to stand in front of pensively. Leonardo DaVinci, Pablo Picasso, Mark Rothko, Agnes Martin, Susan Meiselas. But artists do not have the monopoly on image-making; they never have. Scientists have been making technical images alongside artists for centuries. Their images have equal cultural significance, and sometimes more. Scientific botanical illustrations may not follow John Ruskin's artistic vision of rendering nature scenery, but they do depict accurate plant anatomy in vibrant colours and vivid details. Their nature images are also less widely acknowledged than those of some well-known artists — Anna Atkins’ botanical cyanotypes, for instance, or Karl Blossfeldt’s macrophotography images of plants. Yet, in fact, the categorical divide between artistic and scientific image-making may be as purely ideological as it is unnecessary. Taking a small step outside these artificial dichotomies, one can see that Ansel Adam’s zone system was arguably as much algorithmic as it was aesthetic. The invention of the zone system was underpinned by several factors: Adams’ attention to craftsmanship, his pursuit of beauty, and his environmentalist philosophy. But it was also motivated simply by his desire to ‘[secure] the appropriate information on the negative’ (Adams 1948: iv). In this sense, the zone system has never been just a creative tool by which artists could produce engrossing landscape photographs. It has always also been an algorithmic scheme for preserving the maximum amount of information of any real-life scenery converted into placement on flat, photosensitive surfaces. The pursuit of informational accuracy and visual aesthetics have never been mutually exclusive.

Much advancement in image-making is motivated by scientific curiosity. From telescopes to microscopes, terrestrial laser scanners to the Event Horizon Telescope, scientists have made images of the infinitely big to the infinitesimally small, arresting nature, whether visible or invisible, near or far in front of our eyes.  Writing about Harold Edgerton's high-speed photographs of water splashes and bullets frozen in mid-air, James R. Killian expressed his amazement at photography's ability to make the invisible visible. (Edgerton and Killian 1954) Edgerton is not the first person to freeze a water splash. Working at the dawn of modern photography, British physicist Arthur Worthington attempted to freeze a water splash with his own eyes (Worthington 1895). He devised a spark-producing apparatus that flashes at the moment the water drop hits the surface. In a dim room, he would observe the water splash in pulses of light and record the shape of the splash that was imprinted onto his eye at the split second. He abandoned his drawing practice after discovering the modern camera. Upon looking at the photographs, he realized how wrong his drawings were. The perfect symmetrical form of water splashes he thought he saw was indeed irregular. In his confession, he praised the "objective view" of the camera.

Since its inception, writers have given different accounts to explain the objectivity of the camera. William Fox Talbot wrote about automatic drawing (Talbot 1844). John Szarkowski remarks that a photograph has a unique physical connection to reality, as it records the imprint of light patterns cast by the objects in front of the lens (Szarkowski 2012) . Others emphasize the unrivalled detail of a photo print. Many early photography accounts in the nineteenth and twentieth century emphasize its automatism and proximity to nature, often brushing over human intervention in the photographic process. Talbot was famously known for his botanical 'sun drawings'. However, at the same period, as he was developing the calotype, he also discovered the "delight" of artistically arranged pictures. Talbot experimented with staging photographs with some servants posing as fruit sellers in his estate in Lacock Abbey (Talbot & Jones 1845)2. The French artist Hippolyte Bayard made a staged self-portrait in which he posed as a drowned man in 1840 – one of the many early examples of creative uses of photography.

With my camera pointing at Daniel, I asked him to stop what he is doing and hold his pose for a while. I did not stage the photograph, but the photograph is not objective either. I frame, I compose, I intervene, but my intervention does not make what is on the photograph a complete lie. Image is always a partial truth and a partial illusion. Different paradigms have their own way of validating the truth within the image while normalizing its artifice. Philosopher Louis Althusser remarked that while images constitute an illusion, "they make allusion to reality and they need only be 'interpreted' to discover the reality of the world behind their imaginary representation of that world." (Althusser 1999: 320) The realism in an image is supported by an ideology. As Althusser may phrase it, images are the material manifestation of the ideological apparatus, representing the imaginary relationship between individuals and their real conditions of existence.

On this particular field trip to the Hyytiälä field station, I took several landscape photographs. Landscapes are pictures that depict natural scenery. Early photography theorists considered photographs to be an anomaly in the pictorial tradition because they do not merely capture Nature, as in drawing; rather, as Daguerre claimed, photographs "give her the power to reproduce herself" (Batchen 1999:66). The realism of a landscape is sustained by the ideology that the photograph replicates nature with minimal human intervention — that a piece of landscape photography is nature itself. 

Reconfiguring this imaginary relationship is central to the arguments of writers like Geoffrey Batchen and Rosalind Krauss, who have instead argued that landscape is mediated nature rather than pure natural view (Batchen 1999, Krauss 1982). Batchen, for instance, has noted that concurrent to the invention of photography, landscape was considered under the aesthetic regime of the picturesque. The picturesque put forth rules about framing and composition "expressive of that peculiar kind of beauty which is agreeable in a picture", forming a technical language and conceptual framework by which nature is considered to be translated onto an image (Batchen 1999: 72). 

From early photography to today, landscape — even with its aim centering on the capturing of nature — is neither objective nor natural. Rather it embodies the nature-culture, ideal-real paradox that underpins visual representation. According to Batchen, the paradox is apparent as early as the nineteenth century; it can be found in Talbot’s writings, among others. Talbot wrote that photography is both a mode of drawing and a system of representation in which no drawing takes place. His inability to pin down a singular definition hinted at the multifaceted nature of photography as something simultaneously both natural and cultural.

Daniel and I are in nature together, but we are creating different landscapes at the same time. Holding a camera, I, perhaps subconsciously, direct my eyes in the manner of the picturesque, concentrating on composing with the zone system. Daniel, operating a laser scanner, is concerned with gathering accurate data for the development of a model.

Objectivity assumes a view from nowhere, or a neutral apparatus from which the world can be observed. This imaginary relationship between the world and the individual is an ontology — one that suggests that the observing subject is independent of the observed, and that the acts of observation and use of the apparatus through which one observes do not affect reality. Images are the material existence that sustains this ideology of objectivity. People have been attempting the invention of such machines that produce ‘objective’ images for centuries. Worthington and others in the history of photography praised the camera for its objectivity. But in truth, machines are not objective. Machines measure. They are simply manifestations of human intention. Human intention is what decides their programming and their uses. 

The portrait I am making of Daniel is not nature itself. It will always contain my intention to communicate my experience. It is not a sign, but a signpost pointing towards the world. Photographers such as Worthington believed the camera was objective — that its images allowed for a truer depiction of reality, one that could counteract the flaws of the human eye. But technical vision does not guarantee better vision. It seems so only when people abiding by a representational system accept its artifices; the adjusting of exposure is standard, the adding of colour filters is acceptable.

At the same time, other inventions are considered to go too far, to interfere with realism. Digital cloning is one, for instance — considered a violation of the realism of a photograph. These rules are historical and contingent, constantly changing according to current trends and technological developments. Photography scholar John Tagg remarked that "realism is a social practice of representation, an overall form of discursive production, a normality which allows a strictly delimited range of variations" (Tagg 1999: 271). To continue his line of thought under this specific context, realism is the process in which what is really culture is imagined to become nature. It is a discursive process in which a cultural artefact becomes conflated with nature itself, an imaginary relationship naturalized and institutionalized. Nineteenth-century realist paintings, the Tank-Man photograph, the digital image of the M87 black hole created using data captured by the Event Horizon Telescope — are all ‘real’. Still, their realisms are sustained within different epistemological paradigms. An image is a symptom of an ideological apparatus that configures ‘the imaginary’ and ‘reality’. A photograph is one manifestation; a point cloud is another. As Daniel and I engage in an interdisciplinary dialogue, we look back into the parallel apparatuses we operate, and thinking through each of our entanglements between image and reality. 

*******

On this summer night, Daniel and I are standing on a forest plot at Hyytiälä field station in the middle of Finland. We are both observing from the ground level, but for different reasons. Daniel belongs to a team of remote sensing researchers led by associate professor Miina Rautiainen. The official aim of their research project, ‘From needles to landscapes: a novel approach to scaling forest spectra’, is to develop a better model for the interpretation of multi-sensor satellite images of forests (Hovi et al 2019). Remote sensing is the technique of near real-time environmental monitoring using open access data without on-site observation (Schraik 2022: 15). Remote sensing frequently refers to planetary observation. For instance, the Opportunity Rover, equipped with a panoramic camera capable of photographing a scene with thirteen colour filters, was designed as a remote sensing endeavour to explore the extra-terrestrial landscape of Mars. On Earth, orbiting satellites collect data on environmental elements from surface temperature to vegetation coverage through multispectral sensors. The network of satellites forms a planetary sensorial system monitoring Earth in real-time. Each satellite imagery is telepresence: relaying the top-down view once imagined as a supernatural power, now becomes accessible to the human eye.

Photography is also a form of telepresence, but one mostly confined to the visible light spectrum. Media theorist Marshall McLuhan described media as an extension of the human senses (McLuhan 1964). In that sense, a photograph is a tool able to transport perspective from a single position, be it geographical, socioeconomic or political, to another. Scientific photography, space photography, remote sensing all do this uniquely.

The Sentinel satellites, for instance, record images of multiple spectrums — from high-resolution optical photographs to radar and infrared imaging. The satellite’s gaze dissects the Earth into multiple electromagnetic spectra, each with its own visibilities and invisibilities. Optical light is natural to the human eye but is easily obstructed by the Earth’s atmosphere; Infrared light is sensitive to photosynthetic surfaces but has poor spatial resolution. Researchers switch between different data layers, triangulating useful information from the complementary spectrums. 

I like to think of remote sensing as vision escaping the human body. The sensorial organ expands to a distributed global network, and perception escapes the visual cortex to be incorporated into algorithms. The information contained in an image is no longer confined to the humanly perceptible, but now, to the machine-readable (Bratton 2015, Hansen 2015).

The portrait I have taken of Daniel, I have scanned at 3200ppi in 16 bits RGB, occupying 360.8 MB of memory. The image on the negative is 68mm by 56mm. The digital scan is a matrix of 8540 by 7040 pixels. Each pixel contains information that expresses one of 65,536 possible tonal variations on an RGB scale. The colour depth gives an illusion of smooth tones even though the image comprises discrete squares of colours. 

The satellite image taken by Sentinel 2 using a multispectral instrument on 7 May 2021 is 665.96 MB. The image, covering an area of 100 square kilometres, contains the reflectance map of multiple spectral bands. Each map records the intensity of a certain wave spectrum as reflected back from Earth’s surface to the satellite. Some spectrums are invisible to the human eye. Each image contains deep layers of information. The information of a map can be translated to a value in one of each RGB channel, which, when combined, form a colour image. This type of image is also called a false colour image because the optical layer is an interpretation of the data rather than the physical spectrum registered by the sensors. The red in a false colour image does not have a direct physical relationship with the world as we experience the colour red; here it signifies the reflectance of an invisible wave. 

In these practices, a camera is a measuring apparatus. A photograph depicts the geometric measurement of visible light in a given direction for each pixel (Yiu and Schraik 2022). From the scientist’s point of view, the informational capability of a photograph eclipses its aesthetic quality. This view is further exemplified by the digitization of the medium and the advent of novel computational techniques. Artist/theorists such as Harun Farocki also investigate the varied social roles of images, as in his well-known trilogy Eye/Machine that examined the military-industrial complex (Farocki 2003). Farocki’s notion of ‘operational image’ succinctly points out the new functionalities of photography beyond mere representation, drawing attention to fields in which images are embedded into a computer vision system and used as interfaces to simulate combat and target moving objects. Farocki’s works are frequently referenced in a new wave of exploratory thinking that shifts the focus from the visual to the unvisual, work that scrutinizes the computational dimension (Ingrid and Hoelzl 2015, Beller 2016); and also, its underlying networked infrastructure (Sluis and Rubinstein 2008, MacKenzie and Munster 2019).

These practices stand in stark contrast to traditional, narrow, optical, or parochial views of photography. (Rubinstein 2020: 5). Contrary to contemplation of the individual aesthetic piece, they address images from a systemic perspective. They theorize the image not as the representation of reality, but as ‘a button with a picture’ (Bratton 2015: 224). Those who work in such areas are deliberately attempting to rid themselves of the ocular-centric, the perspectival, and the representational baggage. Such work constitutes what is often known as post-representational photography theory (Rubinstein 2018: 8-18).

Daniel describes a pixel as a coordinate on an image, from which he is able to manipulate and extract information. Thus a pixel serves as a repository for data. Data, while it encodes information, also stands in for our absence, and thus becomes a proxy of the world. Satellite images, for instance, are signs of the presence of data and the absence of the human witness. Most satellite images depict wavelengths invisible to humans, collected by non-human agents. executing pre-written programmes. How can one justify the sporadic absence of humans in the process of information acquisition? 

This is a question that is equally relevant to photography, even as there the absence of the human may be less obvious given that photographers maintain more direct contact with the camera. At the same time, my finger on the shutter does not give me more control over the internal automatic camera mechanism. The camera remains a black box. Articulating a new paradigm in photography, Daniel Rubinstein has recently written that "[w]hether a camera or computer, a black box is a device with an input and an output. If you feed data into a black box, it will be output as information" (Rubinstein 2020: 4). No matter how thoroughly a photograph imitates the human visual experience of the world, it does not disguise the fact that the photograph is a stand-in for something the viewer did not experience physically. Photography is, thus, remote sensing in the broadest sense. Both mediums require an imaginary relationship between the image and reality to justify the human absence. In both cases, human presence can be either emphasized or minimized in the creation of respective realisms.

On a summer night, I took a photograph of Daniel conducting a laser scanning measurement on the forest floor. I was with him; I witnessed his fieldwork in person. The mosquito bites on my legs were my proof. The pixels on the digital scan of his portrait suggest the same evidence of the same event. The difference is that the photograph lasts longer; the bites fade away. The photograph also exists outside my body, becoming a proxy of my existence. 

There are many reasons people tend to believe in photography: the sharpness, the details, the physical imprint of lights, the similarities to human visual experience, the trust in the photographer, the reputation of the newspaper in which the photo is published. However, the advent of digital photography in the 1990s has in fact added another layer of artifice to photographic realism. Art historian Geoffrey Batchen has rightfully pointed out that in the digital image, the referent in a visual work is no longer the physical world but "differential circuits and abstracted data banks of information" (Batchen 2002: 140). Photography becomes programmable, networked, and non-human (Beller 2016, Rubinstein and Sluis 2008, Zylinska 2017). Each pixel contains not physical light as in earlier stages of photography, but encoded data. In this sense, a digital photograph is really a false colour image optimized for the human eye. It does not share a direct causal relationship with the human perception of the physical world. 

Despite its artifice being frequently pointed and from multiple directions, photography nonetheless remains a dominant social medium of truth and evidence that something has occurred in reality. In a speech he gave at the Sorbonne on the occasion of celebrating the centenary of photography on 7 January 1939, French poet Paul Valery reminded of pre-photographic time when facts were established simply by sufficient numbers of people testifying as to their observations. Within the century, photography eroded these channels of knowledge, with one snapshot proof enough to destroy the testimony of some hundred people who had seen an event first-hand. (Trachtenberg 1980: 196). 

Photography's authority in relation to ‘truth’ had been foreshadowed precisely one hundred years earlier, in a different speech, given by a different Frenchman theorizing on the image. In 1839, Louis Daguerre presented his invention at the Academy of Science in Paris. He asserted the uniqueness of the daguerreotype, an early prototype of modern photography, in its ability to empower nature to reproduce itself (ibid: 66). Daguerre’s characterized for the audience the photographic process as automatic physical and chemical imprint capable of producing stunning details, without any idea of drawing and unalterable by light. This explanation maintained its primacy through evidentiary power for decades to come. Through this same period, the ‘truth claim’ of photography has persisted throughout its history, often challenged but never overturned. As photography moved from the physical-chemically based at its birth to its data-based form in the digital era, the truth claim has shifted in reasoning, but not in assertion. One thing that has remained the same is that as reality has been ever increasingly mediated, the medium exerts power over the naked eye as to what ‘really’ happened. In a perpetually-mediated world, the photographic image is taken as ground truth.

Valery raised a good point about the nature of truth, reality, and evidence in his 1930s speech. In the most original sense, ‘ground truth’ means reality as experienced first-hand rather than by report. By definition, ground truth is embodied and non-transferable. But as photography has become irreversibly interwoven into military surveillance, scientific exploration, and the judiciary system as the proxy of truth, photographs have become ground truth. Such photographs, intended to communicate reality, are referred to as documentaries. When Susan Meiselas photographed a man throwing a Molotov cocktail at the Nicaraguan National Guard fortress in 1979, she was mediating that image through her first-hand experience of the Nicaraguan Revolution as a photojournalist (Meiselas 1979). The iconic photograph, known as the Molotov Man, could have been staged — photography has always been susceptible to manipulation since the medium's inception even before the digital era. But underpinned by the photo-documentary tradition, a suspension of disbelief occurs. The viewer ignores the possible artifice and begins to believe in the photograph's realism; they see it and so it must be true. To take a photograph as ground truth is to accept the imaginary relationship between the image and reality.

The term ground truth did not come up in my own mind when I took the photograph of Daniel; rather, he mentioned it while explaining the history of his discipline to me. In remote sensing, ground truth refers to data collected on-site, which is then used to calibrate, to build models, to decipher information from images, or to spot a tree from a pixel. Yet even such data has its limitations. Despite state-of-the-art image sensors, infrared and near-infrared imaging, due to the nature of waveband, is limited by spatial resolution. Longer wavelengths, which are useful in detecting foliage, tend to have lower energy. This means that a pixel needs to cover a larger area than the optical wavelengths it represents, if it is to receive enough energy for a satellite sensor to register any useful activity. For certain wavebands, a pixel may need to cover dozens of square meters of land. 

On a human scale, a pixel is much smaller than the object that it represents. A common modern digital display has over 200 pixels packed in every inch; each side of the pixel is smaller than one-tenth of a millimetre. On a planetary scale, spatial resolution breaks illusion. Objects are hidden underneath pixels. To ‘see’ a tree through a satellite image is analogous to counting skin cells from a portrait. At resolution limits, seeing as a way of knowing breaks down. And the interpretation of data becomes that much more crucial. 

Daniel collects ground truth data by documenting the spatial topology of the forest using terrestrial laser scanning. Comparing ground truth data with satellite data, his team establishes their mathematical correlation – a model that deciphers the forest landscape underneath the pixel. When the scanning finished, Daniel shows me the resulting image on the scanner's viewer. The collection of red dots of different shades depicts trees and the undergrowth of the forest floor. I understand immediately that I am looking at a 3D representation of the forest. A point cloud depicts the forest as a constellation of countless discrete points, as if seeing through the eyes of an extraterrestrial species. For Daniel, the point cloud is a raw material for building a better interpretation model. I am looking at an image; he is building a model. I see it as the end; he sees it as a means to an end. Both point toward the reality we share, oscillating on three realisms – experience as ground truth, images as ground truth, data as ground truth.

Daniel's point cloud, the laser scanner that produces it, the field trip we took to capture it and the research funding that supports it belongs to a social practice of representation I refer to as data realism. Different from photographic representation, however, this form of realism posits that the relationships between data formulated through mathematical operations represent our lived reality. Data realism is sustained by computational models. The common aphorism goes, 'all models are wrong, but some are useful.' A useful model has predictive power over reality. Models improve with more data and rigorous measurements. The point cloud of the forest is only one piece of the puzzle for the model called the reflectance model. By measuring the spatial topology of the forest, Daniel aims to formulate its mathematical correlation with the satellite's multispectral data. His colleagues meticulously measure the spectral properties of tree shoots under a goniometer to understand the way leaves reflect a certain band of electromagnetic waves.3 These measurements are recorded not only in photographs but also as point clouds, spectral graphs, and bitmap scans. And then the point cloud of the forest is only one piece of the puzzle for the model called the reflectance model. In fact, thousands of data points make up a reflectance model — creating a mathematical description of the interaction between sunlight and tree.4

In data realism, models become nature itself. Unable to contain the full complexity of the world, statistical models are prone to uncertainty. Uncertainty can be somewhat tamed with sufficient data and reiterative computation, such that models can create accurate estimation of reality: close enough to factual reality to be considered good enough to justify the human absence in the act of observation.

Data realism is further sustained by social networks and neural networks. Global network infrastructure facilitates the collection of data, while machine learning refines reiteration computation. Like polishing a mirror, remote sensing constantly tries to use data to improve models to better reflect reality. However, if Batchen was right about the visual no longer representing the real world but merely representing data, then that mirror no longer signifies an unmediated reality for which photography strove for centuries. Instead, it has become a metaphor for "a dynamic enfoldment of opposites, a movement that incorporates without synthesizing the conceptual poles nature-culture, real-ideal, general-particular, science-art, object-subject, reflection-expression" (Batchen 1999: 81).

Daniel and I are looking in opposite directions. I look forward, with my optical lens. I look through the viewfinder at him. I press the shutter, already having a good idea as to how the photograph will turn out. Daniel looks backwards, with his model. He began with the data from a satellite image. Using a reflectance model and ground truth data, he works backwards to decipher the original scene, that creates the image we are both able to take in different forms. 

I embalm our presence; he resurrects a tree.

All images besides the author’s own artwork are derived from two sources. Some are archival images from the Finnish Forest Museum acquired by the author. Other images are part of the dataset generously shared by a remote sensing research group based at Aalto University (‘From needles to landscapes: a novel approach to scaling forest spectra’). This data is licensed according to the open science principle and under the Creative Commons license CC-BY 4.0. 

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Althusser, Louis, ‘Ideology and Ideological State Apparatuses’, in Visual Culture: The Reader, ed. by Jessica Evans and Stuart Hall (Thousand Oaks: SAGE, 1999)

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Sheung Yiu

Spotting A Tree From A Pixel (With Remote Sensing Researchers)

Ground Truth [n.]

1. In everyday life, the reality of a situation as experienced first-hand rather than by report.

2. In remote sensing, information collected on location. Information that then allows image data to be related to real features and materials on the ground.

3. In statistics and machine learning, ground truth means checking the results of machine learning for accuracy against human-drawn results.

4. In remote sensing, actual data as ascertainable through direct observation rather than through inference.

Excerpt of the original cloud index of one tree measurement. Each row represents one point, each number (from left to right) represents the XYX coordinate, RGB value and intensity respectively.