Known Surfaces is a series of reliefs and photographs derived from SAR (Synthetic Aperture Radar) data gathered over satellite calibration sites. Translating remote sensing data into sculptural and image form, the works focus on the default landscapes of planetary observation: dry lakebeds, desert grids, and other terrains valued for how consistently they can be measured. A few dozen such sites, agreed upon by the scientific community, underwrite every other image satellites will make, providing the stable reference conditions against which orbital imaging systems establish their ground truth. Every imaging satellite entering orbit is required to scan a subset of these terrains upon deployment and at regular intervals thereafter, making them a core part of the Earth observation infrastructure.

Within this series, Harun Farocki's notion of the operative image, the image produced to enable action through technological communication rather than be looked at, acquires a geography: these calibration sites are operative landscapes, places shaped by the demand that they be measurable, known, computable. Known Surfaces returns these terrains to an aesthetic register, holding open the question of what a landscape valued only for its legibility might otherwise be.

The series currently contains six works produced in different media, created from satellite data obtained at the following satellite calibration sites: Salar de Uyuni, Namib Desert #2, White Sands Missile Range, Lunar Lake Playa, Rogers Dry Lake, Railroad Valley Playa.

Within End of Signal, calibration sites are where Argus, the work's unreliable narrator satellite, first establishes its relation to truthfulness, setting the ground truth it will later come to distort.

Still Nothing is part of "End of Signal", a research-based body of work which examines the epistemic implications of AI deployed at scale, staged through a speculative future in which a satellite becomes an unreliable narrator of the reality on the ground. The project investigates what I term "technological underdetermination": a condition enabled by generative artificial intelligence, in which the unknown is produced by a surplus of plausible explanations rooted in existing ground truths, rather than by a scarcity of information.