Optimization of sensor locations for a light pollution monitoring network

Light Pollution is an environmental problem that needs to be retrieved by experimental means. However, to the best of our knowledge, there is no methodology nor a quantitative procedure to determine an optimal light pollution monitoring network. In this work, we propose a methodology for locating sensors in a light pollution monitoring network by formulating an optimization problem. We introduce an objective function that measures the representativeness of a set of locations using the spatial semi-variance over an image, and different levels of monitoring needs according to the environmental vulnerability of each location. To apply the methodology to a region of interest, we consider three inputs: a Nighttime-Light Image NTLI, an Environmental Vulnerability Map, and a constrained number of sensors. The output is a set of coordinates to locate sensors that consider the intensity of luminosity in nighttime images and its environmental impact. A case study shows that the methodology locates sensors in the most vulnerable areas in which measurements may optimally represent a wide region of the studied territory.