Augmenting data for Urban Metabolism of cities Tool using Machine learning and Satellite Image Analysis of city

Abstract

We use image analysis to augment data about a city’s material flow or material stock.We take existing data about cities such as energy consumption,biomass,water consumption,energy production and construction material either at the city level or national level and add data from satellite based remote sensing. From remote sensing we can get data like built area,population distribution across the region,and night light intensities.

We do this by coupling the insights from images which indicate a proxy for where resources are concentrated.We increase data available for the Urban metabolism tool database in resources correlated to satellite data. We show how data can be collected and may be integrated.