Pros and cons of gaussian filters versus step filters for light pollution monitoring

TL;DR

This paper compares gaussian and step filters in light pollution monitoring, emphasizing their spectral sensitivity, availability, and deployment efficiency for large-scale environmental assessment.

Contribution

It evaluates the advantages and disadvantages of gaussian versus step filters for light pollution measurement, highlighting their suitability for different spectral and practical requirements.

Findings

Gaussian filters are optimal for human perception-based assessments.

Step filters better characterize certain environmental impacts.

Both filter types have distinct advantages depending on monitoring goals.

Abstract

There is debate about which indicators should currently be used to monitor levels of artificial light pollution. To be most valuable, methods need to be sensitive to variation in the spectral composition of light emissions (which are changing rapidly, particularly through increasing use of light-emitting diode [LED] lamps), to be readily available, to be capable of being used on a large spatial scale and of being deployed rapidly. Two sets of photometric systems are the most spread in the world currently, the RGB colors from DSLR cameras that are based on typical gaussian filters and RGB step filters. The first set of filters are optimum for human perception and calculation of most of the most popular environmental impacts although, some of these environmental impacts are better characterized by the step filters.