Landform is a project that has emerged out of the developmental work behind the Waveform and Orbital Reveries projects. Whereas these earlier efforts involve aligning visual and textual data cartographies, Landform goes a stage further, by parsing satellite and drone imaging data of terrestrial landscapes into circuitous visual algorithms, which are executed subsequently by an interpreter that uses these instructions to compose n-dimensional textual structures, drawing from scientific, scholarly, and poetic texts discussing present environmental concerns.

The chief conceptual vector behind Landform is that the imaged terrestrial landscapes—as enacted at the intersection of sunlight, camera lenses, CMOS sensors, and (Java-based) script—are treated as constituting a structured schema that translates into specific compositional instructions—as a form of code, rather than their more-typical representation as a source of data values to be acted upon. The end result is something of a performance, enacting a ‘platform’ (of sorts) constituted by varied landscapes, flying vehicles, cameras, web canvas graphics, and text files—all combining for ends that are far removed from their typical utility.

The aim of Landform is to actualise a set of speculative, experimental relations between the energies, materials, and concepts involved, investigating their potential for enacting novel modes of environmental computational practice, and, thus, outline another vector for articulating the entanglements and contingencies behind our profoundly damaged planet, while staging also how these might be reworked.

Landform was first presented to a wider audience as part of the ELO 2021 Platform (Post?) Pandemic conference in May 2021. The paper accompanying this presentation can be viewed at the ELMCIP database entry here.