Navigating Urban Complexity: Assessing socio-spatial dynamics in Household’s waste practices

Challenge With an ever-increasing population and growing consumption, waste management has become one of the most challenging problems in Indonesia. The rapid urbanisation resulted in fragmented urban planning, causing unequal access to waste disposal services within cities. Recycling and collection rates as well as disposal choices might thus differ considerably according to the socio-spatial characteristics of the city. However, data limitations and unreliable information on socio-economic factors hinder a comprehensive understanding of how waste practices change within a city. Studies used either Remote Sensing Imagery, Geographic Information Systems, Machine learning or Google Street Imagery to map informal settlements and slums. However, settlements may display characteristics that are not visible from space. Alternatively, studies integrated available data from public databases with ground-level information like interviews, but these remain a-spatial and do not provide information about the location and quantity of mismanaged waste. Methodology To address this challenge, the paper employs a geo-referenced and bottom-up approach to gather data on the socioeconomic characteristics and waste management practices within four neighbourhoods in Bandung, Indonesia. The aim of this study is twofold: firstly, to enhance and promote a more equitable waste management system by identifying areas where uncollected waste is prevalent; secondly, to understand spatial patterns and the geographical distribution of uncollected and sorted waste and whether these correspond to low-income areas. Households were randomly selected by the surveyors during data collection. We used two different types of data collection methods: a geo-questionnaire and a mobile data application. In the geo-survey, we addressed both the socio-economic level of the households and their physical attributes and surroundings (such as roof material, road condition, and clean water availability). The mobile data application was used to geolocalise uncollected waste and waste facilities around the neighbourhoods. The methodology has various links with urban citizen science and participatory mapping: it involves not just directed tasks for students but also allows for broader community involvement, active participation, and the integration of diverse perspectives. Expected results As the project is still ongoing, this abstract presents some preliminary results obtained so far and our expected results. In the geo-survey, it was observed that residences exhibiting the physical characteristics of a slum did not always correlate with lower income levels or the absence of adequate waste and wastewater systems and clean water. While it holds true that economically disadvantaged homes and community units often lack these services, the physical features of a house can vary. When it comes to plastic packaging consumption (in terms of quantities and products ), the survey reveals that it does not diff