💻 I took several completely independent datasets and "pitted" them against each other. One of the results is shown in this chart: the more "concrete" (roads, buildings, parking lots) my machine learning model identified in a community, the higher the surface temperature recorded by the thermal sensor.
🔥 The result: Data from different sources confirm one another. The difference in surface temperature between "green" and "concrete" residential areas averages 8–10°C throughout the summer. On certain days, this gap is likely even wider.
📉 This chart shows only established residential communities. If industrial zones were included, the trend would be even more dramatic. While modeling errors certainly exist, the overall physical pattern is undeniable.
#Calgary #OpenData #UrbanHeat #LULC #DataScience #ClimateAction #YYC #GreennesOfCalgary #ClimateEquity #EnvironmentalEquity #CityPlanning #MachineLearning #RemoteSensing #RStats #Sentinel1 #Sentinel2 #Landsat #fossgis








