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arXiv · 2408.00808

LightViz: Autonomous Light-field Surveying and Mapping for Distributed Light Pollution Monitoring

Sheng-En Huang·Kazi Farha Farzana Suhi·Md Jahidul Islam
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Abstract

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 factor 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 suit, 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. A test-case of the LightViz software release is available at: https://github.com/uf-robopi/LightViz.

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Sheng-En Huang, Kazi Farha Farzana Suhi, Md Jahidul Islam. 2024-07-31. LightViz: Autonomous Light-field Surveying and Mapping for Distributed Light Pollution Monitoring. https://doi.org/10.1007/s10661-025-13862-5

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