Understanding Urban Water Consumption using Remotely Sensed Data

TL;DR

This paper presents a method to estimate urban water consumption by analyzing satellite imagery to identify buildings, classify their types, and apply average consumption rates, enabling scalable water use assessment.

Contribution

It introduces a novel approach combining satellite imagery analysis with municipal data to estimate water consumption at the building level.

Findings

Accurate identification of building pixels from satellite images.

Effective classification of residential and non-residential buildings.

Reliable water consumption estimates based on building type and area.

Abstract

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.