DynaSlum

Data-driven modeling and decision support for slums

Image: Dharavi slum, Mumbai, India – by nozomiiqel https://www.flickr.com/photos/nozomiiqel/3409174642/in/photolist-7U4fW-7U4fV-7U4fX-6cbKTD-6cfUR9-6cfZqw-6cbPh2-6cbNKz-6cbQq4-6cfYfN-6cfTHo

Today, over half of the world’s population lives in urban areas and by the middle of this century 7 out of 10 people will live in a city. This increased urbanization has also lead to more and more people residing in informal settlements, generally known as slums.

The challenge of slums

The proliferation of slums is a worldwide problem that the UN-habitat had coined “The challenge of Slums” in 2003. While there are many different definitions of what constitutes a slum, for residents the reality is often inadequate shelter, poor sanitation, insufficient access to healthcare and in general a poor quality of life.

By the middle of the 21st century, it is estimated that the urban population of developing countries will more than double, increasing from 2.5 billion in 2009 to almost 5.2 billion in 2050. In India (2011) roughly 13.7 million households, or 17.4% of urban Indian households, were considered to be part of a slum. Each slum in a city suffers from varying degrees of depravity.

Growth dynamics of slums

This project aims to build high-resolution agent-based models that can describe the growth dynamics of slums in Bangalore. Such a model will create a virtual slum that decision-makers, and researchers, can use to explore how different policies would influence the growth, development or contraction of slums.

The project team plans to build on their existing work and develop a decision support system for slums in general, which will help guide experts when evaluating or designing policies to improve conditions within slums. This involves developing new computational methods for analyzing satellite images and new data visualization techniques for simulation steering.

Reusable software

Through extending the existing decision support prototype, and applying it to a new domain of slum policy, the hope is to generalize the current software. Therefore, this proposal will aim to develop a reusable software framework for decision support and disseminate it to other users.

Participating organisations

Environment & Sustainability
Environment & Sustainability
Netherlands eScience Center
University of Amsterdam

Impact

Output

Team

ML
Michael Lees
Principal investigator
University of Amsterdam
Berend Weel
Berend Weel
eScience Research Engineer
Netherlands eScience Center
Bouwe Andela
eScience Research Engineer
Netherlands eScience Center
DR
Debraj Roy
Elena Ranguelova
Elena Ranguelova
eScience Coordinator
Netherlands eScience Center
AM
Adriënne Mendrik
eScience Coordinator
Netherlands eScience Center

Related projects

Enhance Your Research Alliance (EYRA) Benchmark Platform

Supporting researchers to easily set-up benchmarks

Updated 15 months ago
Finished

Visual Storytelling of Big Imaging Data

Storytelling as a means of visual data communication

Updated 18 months ago
Finished

Algorithmic Geo-visualization

From theory to practice

Updated 20 months ago
Finished

SIM-CITY

Decision support for urban social economic complexity

Updated 16 months ago
Finished

Summer in the City

Forecasting and mapping human thermal comfort in urban areas

Updated 15 months ago
Finished

Generic eScience Technologies

Making breakthroughs in data-driven research

Updated 16 months ago
Finished

Related software

Osmium

OS

Start, stop and monitor applications remotely via a HTTP interface.

Updated 24 months ago
2

Satsense

SA

A Python library for land use classification based in satellite images.

Updated 24 months ago
8