Urban metabolism is an active field of research that deals with the estimation of emissions and resource consumption from urban regions. The analysis could be carried out through a manual surveyor by the implementation of elegant machine learning algorithms. In this exploratory work, we estimate the water consumption by the buildings in the region captured by satellite imagery. To this end, we break our analysis into three parts: i) Identification of building pixels, given a satellite image, followed by ii) identification of the building type (residential/non-residential) from the building pixels, and finally iii) using the building pixels along with their type to estimate the water consumption using the average per unit area consumption for different building types as obtained from municipal surveys.
@article{arxiv.2205.02932,
title = {Understanding Urban Water Consumption using Remotely Sensed Data},
author = {Shaswat Mohanty and Anirudh Vijay and Shailesh Deshpande},
journal= {arXiv preprint arXiv:2205.02932},
year = {2023}
}