LightViz: autonomous light-field sensing, mapping, and assessment for distributed light pollution monitoring

Existing technologies for distributed light-field mapping and light pollution monitoring (LPM) rely on either remote satellite imagery or manual light surveying with single-point sensors such as SQMs (sky quality meters). These modalities offer low-resolution data that are not informative for dense light-field mapping, pollutant identification, or sustainable policy implementation. In this work, we propose LightViz-an interactive software interface to survey, simulate, and visualize light pollution maps in real time. As opposed to manual error-prone methods, LightViz (i) automates the light-field data collection and mapping processes; (ii) provides a platform to simulate various light sources and intensity attenuation models; and (iii) facilitates effective policy identification for conservation. To validate the end-to-end computational pipeline, we design a distributed light-field sensor suite, collect data on Florida coasts, and visualize the distributed light-field maps. In particular, we perform a case study at St. Johns County in Florida, which has a two-decade conservation program for lighting ordinances. The experimental results demonstrate that LightViz can offer high-resolution light-field mapping and provide interactive features to simulate and formulate community policies for light pollution mitigation. We also propose a mathematical formulation for "light footprint" evaluation, which we integrated into LightViz for targeted LPM in vulnerable communities. LightViz system design and software is available at https://robopi.ece.ufl.edu/lightviz.html .