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Remote Sens. 2018, 10(2), 216; https://doi.org/10.3390/rs10020216

A Holistic Concept to Design Optimal Water Supply Infrastructures for Informal Settlements Using Remote Sensing Data

Chair of Fluid Systems, Technische Universität Darmstadt, Otto-Berndt-Straße 2, D-64287 Darmstadt, Germany
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Received: 22 November 2017 / Revised: 22 December 2017 / Accepted: 26 January 2018 / Published: 1 February 2018
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Abstract

Ensuring access to water and sanitation for all is Goal No. 6 of the 17 UN Sustainability Development Goals to transform our world. As one step towards this goal, we present an approach that leverages remote sensing data to plan optimal water supply networks for informal urban settlements. The concept focuses on slums within large urban areas, which are often characterized by a lack of an appropriate water supply. We apply methods of mathematical optimization aiming to find a network describing the optimal supply infrastructure. Hereby, we choose between different decentral and central approaches combining supply by motorized vehicles with supply by pipe systems. For the purposes of illustration, we apply the approach to two small slum clusters in Dhaka and Dar es Salaam. We show our optimization results, which represent the lowest cost water supply systems possible. Additionally, we compare the optimal solutions of the two clusters (also for varying input parameters, such as population densities and slum size development over time) and describe how the result of the optimization depends on the entered remote sensing data. View Full-Text
Keywords: water supply design; mathematical optimization; slum classification; remote sensing water supply design; mathematical optimization; slum classification; remote sensing
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Rausch, L.; Friesen, J.; Altherr, L.C.; Meck, M.; Pelz, P.F. A Holistic Concept to Design Optimal Water Supply Infrastructures for Informal Settlements Using Remote Sensing Data. Remote Sens. 2018, 10, 216.

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