Reading drosscapes:
As Computational Atlas
of Post-industrial Landscapes
by Marta Morato
Santiago de Compostela - New York
2025
Santiago
de Compostela
Santiago
de Compostela
The Drosscape Atlas is not conceived as a static collection of maps, but as an evolving computational instrument. Rather than representing residual landscapes in nothern Spain as fixed objects, the atlas is built through a series of scripts, datasets, and iterative visualizations that allow these territories to be continuously processed, compared, and re-read.
Drawing from methodologies similar to those developed in material-based research environments, the atlas treats territory as a form of data that can be extracted, classified, and reassembled. In this sense, mapping becomes less about depiction and more about fabrication: each map is produced through a pipeline of operations, from data acquisition to geometric translation and visual encoding.
The construction of the atlas relies on a combination of geospatial datasets (topography, land use, infrastructure, environmental indicators) and parametric tools. Through scripting environments—such as Grasshopper, Python, or GIS-based processes—these inputs are translated into layered geometries that register not only form, but also intensity, accumulation, and transformation over time.
This approach allows the atlas to operate across scales simultaneously. At the territorial level, it identifies large-scale patterns of extraction, abandonment, and logistical occupation. At the local level, it isolates specific material conditions—soil composition, surface textures, hydrological traces—treating them as active agents rather than passive backgrounds. In this way, the atlas begins to overlap with a material practice: the ground is no longer neutral, but something that can be read, processed, and ultimately designed with.
Coding is therefore not a representational tool, but a design method. Scripts are used to filter noise, detect anomalies, and construct relationships between datasets that are not immediately visible. The atlas is constantly rewritten: parameters shift, thresholds are adjusted, and new layers are introduced, allowing the system to remain open and responsive rather than definitive.
By structuring the atlas as a reproducible workflow, it becomes transferable across contexts. The same logic can be applied to post-industrial landscapes in Galicia, logistical terrains in New York, or evolving urban conditions in Ahmedabad. What changes is not the method, but the data—and with it, the specific material and spatial expressions that emerge.
Ultimately, the Drosscapes Atlas operates as both a reading and a projective tool. It does not aim to stabilize the territory into a final image, but to construct a framework through which residual landscapes can be continuously analyzed, compared, and activated as sites of design potential in the north of Spain.
by MartaMorato
@drosscape
MMC Computational Design