Review discusses synthetic aperture radar's impact on data interpretation and governance in a changing visual landscape.
Over time, humans have developed the capability to distinguish and capture finer portions of the electromagnetic spectrum at higher resolutions. Modern optical sensors can resolve the Earth in detailed color at resolutions of up to 10 cm. This type of passive remote sensing mimics human vision by recording spectral information, or light. Yet another technique which does not measure spectral information, synthetic aperture radar (SAR), is increasingly used in military, commercial, and scientific applications. SAR satellites shoot microwave pulses of energy, which penetrate clouds and darkness, at the Earth’s surface and measure the returned signal, or backscatter. This electromagnetic data allows consistent interpretation of surface properties, structure, and motion, regardless of the weather or time of day. Although often visualized as an image, SAR data does not lend itself well to orthodox spatial intuition, and its production and interpretation require advanced technical skills. Theorizing the political and epistemic consequences of SAR necessitates transcending visual critiques of remote sensing, which have largely considered optical satellite imagery, because SAR is iconoclastic. The technology upends the preeminence of the divine view of the “blue marble” of Earth and instead values the invisible and electric. Herein, we review SAR and offer a more-than-visual critique of its data to problematize how it makes sense of the world – and the haptic, shadowy world it is setting into motion, where information transparency is disappearing even as more data are captured than ever before. SAR imagery is tricky for laypeople to interpret, which may challenge democratic accountability at a time when the data increasingly informs governance. The rise of SAR also shifts politics upstream from the interpretation of optical images based on a relatively shared visual vocabulary to the production of imagery inferred from electromagnetic signals.
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Bennett et al. (2026) studied this question.
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