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Abstract:
Background: Light exposure significantly impacts various aspects of human physiology, including cognition and the circadian clock. Light is detected by the retinal photoreceptors, cones and rods, which enable us to see the world, and the ipRGCs, which signal the intensity of ambient illumination. The world around us is complex in its visual at- tributes, differing in spectrum, intensity, color, spatial articulation and temporal properties. To comprehensively characterize the world around us vis-à-vis its visual and non-visual physiologically relevant properties, we started an image-capture campaign to map out the spectral, spatial and temporal properties of indoor and outdoor natural scenes across a wide range of geographical and seasonal contexts. Methods: We developed a multi- modal, minimal-parallax image capture setup for capturing natural scenes comprehensively. We are collecting radiance images using an α-opic imaging radiometer ( 40◦ × 48◦ FOV, 2712 × 3388 px2), spectral irradiance measurements using a high-resolution spectrora- diometer (380–780 nm, 1 nm resolution), illuminance and colorimetric (xy) measurements (~8 Hz), depth information using a depth camera (15 fps), and uncalibrated wide-field RGB videos (60 fps). All measurement devices controlled are integrated into a compact box (42 × 32 × 27 cm3), which can be mounted on a tripod and controlled by a laptop. Power is supplied through external batteries, making the system suitable for indoor and outdoor use. In addition to the primary light-based data, we comprehensively describe the scenes using a novel metadata schema containing location, weather and other information. We collect natural scene data using two distinct protocols. First, we collect data from the same scene over a day in a time-lapse protocol. Second, in a trajectory protocol, we are simulating a hypothetical trajectory of an individual throughout the day, thereby capturing plausible natural scenes that people might be exposed to throughout the day. Results: We have finished piloting and technical checks and are now collecting time-lapse data across various natural scenes. We have subjected our image-capture setup to a rigorous cross-validation check, indicating high between-device agreement for related quantities. Our setup has been proven portable for field measurements, facilitating the development of a geographically diverse dataset, with planned measurements taking place in Germany, Czech Republic, France and Canada in the first wave. Conclusions: Our data collection campaign will yield a highly significant, geographically spread, worldwide database for developing novel approaches to understanding illumination and scenes in the real world. All data captured with our system are converted to physiologically relevant cone-, rod- and melanopsin-based quantities and metrics to relate our data to lighting recommendations and guidelines supporting human health. The data will be carefully documented and pub- lished openly, creating the first open-access reference resource for natural scenes’ spectral, spatial and temporal properties, indoors and outdoors.
