Random forest regression exploring contributing factors to artificial night-time lights observed in VIIRS satellite imagery

ABSTRACT

Artificial night-time lights (ANTL) pose environmental, economic, and social problems. To effectively manage this issue, it is important to understand the sources that contribute to it. Previous research has presented conflicting views on the relative importance of streetlamps and spill-over light from buildings as contributors to ANTL. In this study, we used satellite images, ground surveys of streetlamps and buildings in the city of Hobart, Tasmania, Australia, to determine the major contributing sources of ANTL. Imagery from the Visible Infrared Imaging Radiometer Suite (VIIRS) satellite was used to map ANTL. We developed a predictive random forest regression (RFR) model and found that streetlamps were the major contributor, followed by the building footprint area. We also found that an increase in both the number of streetlamps and buildings leads to an increase in ANTL observable in VIIRS satellite data. The RFR model performed well with an R² of 0.94 and a median normalised root mean square error of 6.25%.

KEYWORDS:

• Artificial night-time lights
• streetlamps
• building footprint area
• Visible Infrared Imaging Radiometer Suite (VIIRS)
• random forest regression (RFR)

Acknowledgements

We would like to express our sincere gratitude to Robert Stevenson from Hobart City Council for generously providing the streetlamp’s data, which greatly contributed to the results presented in this paper. We also extend our thanks to the anonymous reviewer for their valuable comments and suggestions that helped improve the quality of the manuscript. Furthermore, we would like to acknowledge the invaluable support and guidance provided by our co-supervisors Heather Lovell and Jaganath Aryal, as well as the insightful feedback from Darren Turner during the initial review. Their contributions have been crucial in shaping the direction of this research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability statement

The data that support the findings of this study were derived from the following resources available in the public domain:

1. VIIRS Satellite Images: https://ladsweb.modaps.eosdis.nasa.gov

2. Streetlamps: https://data-1-hobartcc.opendata.arcgis.com/datasets/hobartcc::street-lighting-sample-data/about

3. Building Footprints: https://www.thelist.tas.gov.au/app/content/data/geo-meta-data-record?detailRecordUID = e5753e25-78d4-4b33-b55b-4fb41a14b1c6