The Universal Texture


Images via Clement Valla.

These artists (...) counter the database, understood as a structure of dehumanized power, with the collection, as a form of idiosyncratic, unsystematic, and human memory. They collect what interests them, whatever they feel can and should be included in a meaning system. They describe, critique, and finally challenge the dynamics of the database, forcing it to evolve.1

I collect Google Earth images. I discovered them by accident, these particularly strange snapshots, where the illusion of a seamless and accurate representation of the Earth’s surface seems to break down. I was Google Earth-ing, when I noticed that a striking number of buildings looked like they were upside down. I could tell there were two competing visual inputs here —the 3D model that formed the surface of the earth, and the mapping of the aerial photography; they didn't match up. Depth cues in the aerial photographs, like shadows and lighting, were not aligning with the depth cues of the 3D model.

The competing visual inputs I had noticed produced some exceptional imagery, and I began to find more and start a collection.  At first, I thought they were glitches, or errors in the algorithm, but looking closer, I realized the situation was actually more interesting — these images are not glitches. They are the absolute logical result of the system. They are an edge condition—an anomaly within the system, a nonstandard, an outlier, even, but not an error. These jarring moments expose how Google Earth works, focusing our attention on the software. They are seams which reveal a new model of seeing and of representing our world - as dynamic, ever-changing data from a myriad of different sources – endlessly combined, constantly updated, creating a seamless illusion.

3D Images like those in Google Earth are generated through a process called texture mapping....