To cite this paper use one of the standards below:
Lightning is a stochastic phenomenon and is responsible for several fatalities every year around the world. As an attempt to reduce its effects, different risk indices have been produced over the years and different strategies are used for people safety and property protection. This work presents a lightning attractiveness index based on a digital surface model (DSM) obtained using Google Earth 3D imagery and Structure from Motion (SfM) technology. A weighted kernel was then applied to the DSM using Google Earth Engine infrastructure. The results seem to consistently emphasize areas with higher and lower attractiveness and therefore, higher and lower risk. The index is expected to help in the development of improved lightning hazard models applied to urban areas.
With nearly 200,000 papers published, Galoá empowers scholars to share and discover cutting-edge research through our streamlined and accessible academic publishing platform.
Learn more about our products:
This proceedings is identified by a DOI , for use in citations or bibliographic references. Attention: this is not a DOI for the paper and as such cannot be used in Lattes to identify a particular work.
Check the link "How to cite" in the paper's page, to see how to properly cite the paper