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| Main Authors: | , , |
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| Format: | Preprint |
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2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.00808 |
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| _version_ | 1866916652061294592 |
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| author | Huang, Sheng-En Suhi, Kazi Farha Farzana Islam, Md Jahidul |
| author_facet | Huang, Sheng-En Suhi, Kazi Farha Farzana Islam, Md Jahidul |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_00808 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | LightViz: Autonomous Light-field Surveying and Mapping for Distributed Light Pollution Monitoring Huang, Sheng-En Suhi, Kazi Farha Farzana Islam, Md Jahidul Image and Video Processing 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. |
| title | LightViz: Autonomous Light-field Surveying and Mapping for Distributed Light Pollution Monitoring |
| topic | Image and Video Processing |
| url | https://arxiv.org/abs/2408.00808 |