Abstract
Research and educational activities (R&EAs) are major forces behind modern economic growth. However, data on geographic location of such activities are often poorly reported. According to our research hypothesis, intensities and spectral properties of artificial light-at-night (ALAN) can be used for remote identification of R&EAs, due to their unique ALAN signatures. In order to develop activity identification models, we carried out a series of in situ measurements of ALAN intensities and spectral properties in a major metropolitan area in Israel. For this task, we used an illuminance CL-500A spectrophotometer that measures the total intensity and spectral irradiance of ALAN, incremented by a 1-nm pitch, from 360 to 780nm. As our analysis shows, logistic regressions, incorporating ALAN intensities at the peak or near-peak wavelengths, and geographical attributes of the measurement sites as controls, succeeded to predict correctly up to 98.6% of the actual locations of R&EAs. A digital camera satellite image, obtained from the Astronaut Photography Database, was used for the model's validation. According to the validation results, the actual locations of R&EAs coincided well with the estimated high probability areas, as confirmed by the values of Cohen's Kappa index of up to 64%, which indicate a reasonable level of agreement.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call