Esri, TomTom, Garmin, FAO, NOAA, USGS, EPA, USFWS | Global Energy Observatory, Google, KTH Royal Institute of Technology in Stockholm, Enipedia, World Resources Institute. 2018. Global Power Plant Database. Published on Resource Watch and Google Earth Engine
Source: http://datasets.wri.org/dataset/globalpowerplantdatabase
This app illustrates the effect of clustering on high density point data. Global power plants are clustered and categorized by fuel type. Clustering summarizes the layer's renderer so you can see the spatial density of features at a glance.