Evaluating the socio-environmental features of slums in Mumbai using open geodata
Jan-Jaap van Raffe
In the modern world, almost 40% of the world’s population consists of people living in inadequate living conditions. To combat the problem in areas with inadequate living conditions, data regarding the locations of inadequate living areas have to be made and updated over time. This study aims to determine the use of socio-environmental features for the monitoring of slum areas over time using open geodata. In this context, socio-environmental features are defined as features with environmental or social characteristics. Areas with inadequate living space are defined as slums.
To test the use of the selected socio-environmental features for the identification of slum areas, the city of Mumbai was analyzed for the effect of the socio-environmental features on slum density. The socio-environmental features were analyzed within the slum areas themselves. Then these results were compared to the analysis of the socio-environmental features within non-slum areas. Lastly, the relationship between the socio-environmental features and slum density was analyzed. The results showed some socio-environmental features had a different presence in slum areas compared to non-slum areas. However, the relationship showed a low correlation between the socio-environmental features and slum density.
The results suggest that the selected open geodata are not related to slum density in a significant manner to predict slum locations. Higher-resolution data or better predicted open geodata is required to do a better analysis in future research.
Keywords: Open geodata; Socio-environmental feature; slum; Mumbai; random Forest.